Impact of Service Innovation Capabilities on Business

ii

Impact of Service Innovation Capabilities on Business Model

Innovation: A Dual Moderated Mediation Analysis

By

MALKAH NOOR KIANI

(1431178)

A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE

REQUIREMENT FOR THE DEGREE OF

DOCTORATE OF PHILOSOPHY

IN MANAGEMENT SCIENCES

TO

DEPARTMENT OF MANAGEMENT SCIENCES

Shaheed Zulfikar Ali Bhutto Institute of Science and Technology

(SZABIST), Islamabad

February, 2020

iii

CERTIFICATE OF APPROVAL

iv

DISSERTATION AND DEFENSE APPROVAL FORM

The undersigned certify that they have read the following dissertation, examined the defense, are

satisfied with the overall exam performance and recommend the dissertation to the Department of

Management Sciences SZABIST for acceptance:

Dissertation Title: Impact of Service Innovation Capabilities on Business Model

Innovation: A Dual Moderated Mediation Analysis

Submitted by: Malkah Noor Kiani Registration # 1431178

Doctorate of Philosophy

Department of Management Sciences

Dr. Mehboob Ahmad _

Name of the research supervisor Signature of the Research Supervisor

Dr. Mehboob Ahmad _

Name of the Program Manager Signature of the Program Manager

Dr. Muhammad Asif Khan _

Name of the Head of Department Signature of the HOD

Khusro Pervaiz Khan _

Name of the Head of Campus Signature of the HOC

v

AUTHOR’S DECLARATION

I, Malkah Noor Kiani D/o Sultan Farid Kiani, Registration # 1431178, hereby state that my PhD thesis

titled, “Impact of Service Innovation Capabilities on Business Model Innovation: A Dual Moderated

Mediation Analysis” is my own work and has not been submitted previously by me for taking any degree

from this University (Shaheed Zulfikar Ali Bhutto Institute of Science and Technology (SZABIST) or

anywhere else in the country world.

At any time if my statement is found to be incorrect even after my Graduate the university has the right

to withdraw my PhD degree.

Signature:

____________________

Name: Malkah Noor Kiani

Dated: 27th February 2020 _____

vi

PLAGIARISM UNDERTAKING

I solemnly declare that research work presented in the thesis titled, “Impact of Service Innovation

Capabilities on Business Model Innovation: A Dual Moderated Mediation Analysis” is solely my

research work with no significant contribution from any other person. Small contribution/help wherever

taken has been duly acknowledged and that complete thesis has been written by me.

I understand the zero tolerance policy of the HEC and University (Shaheed Zulfikar Ali Bhutto Institute

of Science and Technology (SZABIST) towards plagiarism. Therefore, I as an Author of the above titled

thesis declare that no portion of my thesis has been plagiarized and any material used as reference is

properly referred/cited.

I undertake that if I am found guilty of any formal plagiarism in the above titled thesis even after award of

PhD degree, the University reserves the rights to withdraw/revoke my PhD degree and that HEC and the

University has the right to publish my name on the HEC/University Website on which names of students

are placed who submitted plagiarized thesis.

Student/ Author Signature: _________________

Name: Malkah Noor Kiani

Registration #:_1431178

vii

Copyright © 2020 MALKAH NOOR KIANI

All rights reserved. No part of the publication may be reproduced in any form by print, photo

print, microfilm or any means without written permission from the author

viii

DEDICATION

This research work is dedicated to my parents (late), husband and my kids who comforted me,

groomed me, supported me and lead me in my life.

I dedicate this work to my mother (late) who had always been the source of inspiration, emotional

enthusiasm till her last breath. She had always motivated me for the completion of my Ph.D. degree

program. Her prayers were the real essence for all my academic and professional achievements

and made me proud of what I am today.

I dedicate this work to my husband who always supported me in every walk of life including the

hard journey of this degree program. His love, trust, support, and faith have enabled me to

accomplish my studies.

Lastly, my research work is dedicated to my little sun-shines, Ali and Zainab. They are the reasons

behind my struggles and efforts for the persuasion of my academic goals. They are my real

emotional strength, no matter how hard and complicated this doctoral journey was for me. They

comforted me and relieved me from the exhaustion and tiredness experienced during this

challenging journey.

May ALLAH bless them all! (Ameen).

ix

ACKNOWLEDGMENTS

Innumerable thanks to Almighty Allah, for giving me the courage, empowering me with the

knowledge and confidence to accomplish this research work. First of all, I would like to express

my deep gratitude to my supervisor Dr. Mehboob Ahmad for his precious comments and guidance

has laid the groundwork for this Ph.D. dissertation. His guidance and encouragement from the

basics to the final level has enabled me to develop an understanding of the topic of this research

work. His knowledge and leadership provides a priceless model for my own career. I am very

thankful to my teachers and faculty of management sciences who have groomed me and enable

me to work on a research dissertation. I am very grateful to head of department, Dr. Muhammad

Asif Khan, for providing students such a desirable learning environment to pursue their MS /

Doctorate degrees. Acknowledging, it is the endeavors of our respected head of department that

enables the students foster learning with more enthusiasm, devotion and passion. Thanking him

for allowing all the students, the space to not only have dialogue, but be creative with our learning

as well. Words are powerless to express my gratitude to all of them for their steadfast diligence to

the noble profession of teaching.

I am grateful to my parents (late) who had always encouraged me and prayed for my success. I am

tremendously grateful to my family for being a constant source of inspiration, motivation and

emotional stimulation that added both to my enthusiasm and research work.

x

ABSTRACT

Cellular firms are compelled to innovate in terms of business model innovation. The introduction

of IT-enabled services to the general public of Pakistan has provided the cellular firms with new

business opportunities by opening new avenues of market competition. With an objective to ensure

the sustainability in growing trends of market competition, cellular firms are now engaged in other

subtle business models such as mobile banking service, G2P payment mechanisms, P2P payment

mechanism, utility bill payments, e-commerce, etc. in parallel with the parental business model

(of provision of mobile phone connection). Therefore, it is essential to study what are constituents

of business model innovation and what are the factors that shape the business model innovation.

The review of extensive literature further indicated the six important research gaps that form the

foundations and groundwork of this study. In order to address these research gaps, six research

objectives and research questions have been established. The data has been collected via a

questionnaire survey from the 427 upper and middle managers of four cellular firms (namely

Mobilink – Warid, Telenor, Ufone, and Zong) through simple random sampling strategy.

Regression-based conditional process analysis by Hayes (2018) is used for hypothesis testing.

Structural equal modeling is also implied for overall testing the model fitness of the hypothesized

theoretical framework.

The results show that service innovation capabilities directly affects the overall business

model innovation. It is also found that service innovation capabilities also indirectly affect the

business model innovation through the positive mediation of service innovation success. This

positive mediation effect is further positively moderated by the management entrepreneurial

orientation and negatively moderated by employee resistance to change. Furthermore, it is also

found that the management entrepreneurial orientation also positively moderates the direct effect

of service innovation capabilities on business model innovation. In addition, the negative

moderation effect of employee resistance to change on the direct effect of service innovation

capabilities and business model innovation is also found. Thus, this study attempts to contribute

the novelty by empirically testing the strategic entrepreneurship perspective through the lens of

the force field of changes. As previous researches indicated that there is a need to further

investigate the strategic entrepreneurship perspective in combination with the diverse theoretical

perspectives (Mazzei, Ketchen & Shook, 2016; Covin & Lumpkin, 2011). In addition, this study

contributes the novelty by addressing the identified six literature-based research gaps through deep

xi

empirical testing. Key findings for the practitioners of cellular firms of Pakistan are also

proclaimed to achieve a higher degree of business model innovation. Moreover, it is also

recommended for future researches to enrich this study by further investigating the other

contextual and organizational factor that may influence the business model innovation.

Comparative studies of cellular firms on the extent of business model innovation and its

implications on their competitive positioning also recommended for future researches.

xii

TABLE OF CONTENTS

DEDICATION………………………………………………………………………………..viii

ACKNOWLEDGMENTS ..…………………... …………………………………………...…ix

ABSTRACT……………………………………………………………………………………..x

TABLE OF CONTENTS ……………………………………..……………………………....xii

LIST OF APPENDICES ……………………………………….…………………………….xvi

LIST OF TABLES ………………………………………… ….………………………….....xvii

LIST OF FIGURES ……...………………………………… ….…………………………….xix

CHAPTER 1 - INTRODUCTION ............................................................................................... 1

1.1. BACKGROUND OF STUDY .................................................................................................. 1

1.2. GAP ANALYSIS...................................................................................................................... 3

1.3. PROBLEM STATEMENT ....................................................................................................... 6

1.4. OBJECTIVES OF RESEARCH STUDY ................................................................................ 7

1.5. RESEARCH QUESTIONS ...................................................................................................... 7

1.6. CONTRIBUTION OF STUDY ................................................................................................ 8

1.7. DISSERTATION STRUCTURE ........................................................................................... 10

1.8. CHAPTER SUMMARY ........................................................................................................ 11

CHAPTER 2 - LITERATURE REVIEW ................................................................................. 14

2.1. THEORETICAL FOUNDATIONS OF STUDY ................................................................... 14

2.1.1. Strategic Entrepreneurship Theory ............................................................................... 14

2.1.2. Force Field Theory of Change ..................................................................................... 15

2.2. CONCEPTS, DEFINITIONS AND ESTABLISHED RESEARCHES ................................. 15

2.2.1. Business Model Innovation (Dependent Variable). ..................................................... 16

2.2.1.1. Dimensions of Business Model Innovation. ........................................................ 17

2.2.1.2. Research Gap - 1: Operationalization of BMI Needs Empirical Validation ...... 21

2.2.2. Service Innovation Capabilities (Independent Variable). ............................................ 24

2.2.2.1. Review of Recent Theoratical Framework...…………………………………...27

2.2.2.2. Dimensions of Service Innovation Capabilities. ................................................. 30

2.2.2.3. Innovation Capabilities Concept Needs To Be Validated.. ................................. 37

2.2.3. Service Innovation Success (Mediating Variable). ...................................................... 38

2.2.4. Employee Resistance To Change (Moderating Variable - 1) ....................................... 43

xiii

2.2.5. Management Entrepreneurial Orientation (Moderating Variable - 2). ......................... 46

2.3. PROPOSED ASSOCIATION OF STUDY VARIABLES .................................................... 52

2.3.1. Relationship of Innovation Capabilities and Business Model Innovation (Research

Gap-2). .................................................................................................................................... 52

2.3.2 Relationship Of Innovation Capabilities and Service Innovation Success. .................. 54

2.3.3. Relationship of Service Innovation Success and Business Model Innovation. ............ 55

2.3.4. Service Innovation Success As Mediator (Research Gap – 3). .................................... 57

2.3.5. Moderation Effect of Employee Resistance To Change (Research Gap-4). ................ 59

2.3.6. Moderation Effect of Management Entrepreneurial Orientation (Research Gap – 5). 61

2.4. ANTECEDENT OF BMI NEEDS TO BE EXPLORED (RESEARCH GAP-6) .................. 63

2.5. CHAPTER SUMMARY ........................................................................................................ 67

CHAPTER 3 - RESEARCH METHODOLOGY ..................................................................... 68

3.1. RESEARCH PARADIGM AND PHILOSOPHY….……………………………………….68

3.1.1. Ontological Stance of Study. ........................................................................................ 68

3.1.2. Epistomological Stance of Study. ................................................................................ 69

3.1.3. Axiological Stance of Study. ........................................................................................ 70

3.1.4. Hypothesized Theoratical FrameworK ........................................................................ 71

3.2. RESEARCH DESIGN ............................................................................................................ 74

3.3. OPERATIONALIZATION OF RESEARCH INSTRUMENT AND MEASUREMENT .... 74

3.3.1. Service Innovation Capabilities. ................................................................................... 74

3.3.2. Service Innovation Success. ......................................................................................... 76

3.3.3. Business Model Innovation. ......................................................................................... 77

3.3.4. Management Entrepreneurial Orientation. ................................................................... 78

3.3.5. Employee Resistance To Change. ................................................................................ 79

3.3.6. Finalization of Research Instrument. ............................................................................ 79

3.4. POPULATION AND SAMPLE OF STUDY ........................................................................ 80

3.4.1. Unit of Analysis. ........................................................................................................... 81

3.4.2. Determination of Sample Size. ..................................................................................... 83

3.4.3. Selection of Sample and Sampling Technique. ............................................................ 84

3.4.4. Data Collection ............................................................................................................. 85

3.5. RELIABILITY AND VALIDITY OF RESEARCH INSTRUMENT ................................... 85

3.5.1. Face Validity. ............................................................................................................... 86

3.5.2. Content Validity. .......................................................................................................... 86

xiv

3.5.3. Construct Validity (Exploratory Factor Analysis). ...................................................... 86

3.5.4. Construct Reliability (Cronbach Alpha). ...................................................................... 98

3.5.5. Convergent Validity And Item Reliability (Confirmatory Factor Analysis). ............ 100

3.5.6. Discriminate Validity (Fornell-Lacker Criterion). ..................................................... 102

3.6. STATISTICAL TECHNIQUES ........................................................................................... 111

3.7. CHAPTER SUMMARY ...................................................................................................... 112

CHAPTER 4 - DATA ANALYSIS & RESULTS ................................................................... 114

4.1. DEMOGRAPHIC CHARACTERISTICS............................................................................ 114

4.2. DESCRIPTIVE ANALYSIS ................................................................................................ 114

4.3. CORRELATION ANALYSIS AMONG STUDY VARIABLES ....................................... 115

4.4. HYPOTHESES TESTING - REGRESSION BASED CONDITIONAL PROCESS

ANALYSIS.................................................................................................................................. 116

4.4.1. Assumptions of Regression Analysis. ........................................................................ 118

4.4.1.1. Data Normality. ................................................................................................ 118

4.4.1.2. Linearity of Residuals. ...................................................................................... 119

4.4.1.3. Multicollinearity. .............................................................................................. 120

4.4.2. Addressing Gap-II - Testing the Effect of ‘X’ on ‘Y’(H-1) ....................................... 121

4.4.3. Addressing Gap-III - Testing the Mediation Effect of ‘M’ on Relationship of ‘X’ on

‘Y’ ........................................................................................................................................ 121

4.4.4. Addressing Gap-IV -Testing the Moderation Effect of Employee Resistance ‘W’. .. 123

4.4.4.1. Testing the Moderation Effect of ‘W’ on Relationship of ‘X’ on ‘Y’. ................ 123

4.4.4.2. Testing the Moderation Effect of ‘W’ on Relationship of ‘X’ and ‘M’. ............. 126

4.4.5. Addressing Gap-V -Testing the Moderation Effect of ‘Z’. ........................................ 128

4.4.5.1. Testing the Moderation Effect of ‘Z’ on Relationship of ‘X’ on ‘Y’. ................ 128

4.4.5.2. Testing the Moderation Effect of ‘Z’ on Relationship of ‘X’ and ‘M’. ............. 130

4.4.6. Addresing Gap-VI - Testing the Antecedents of Business Model Innovation….…..132

4.4.6.1. Testing the Dual Moderation Effect of “W” and “Z” on Relationship of “X”

on “Y”with Putative Mediator Held Constant. ............................................................ 135

4.4.6.2. Testing the Dual Moderated Mediation Effect of “W” “Z” and “M” on

Relationship of “X” on “Y”. ........................................................................................ 135

4.5. CHECKING FITNESS INDICES OF DUAL MODERATED MEDIATION

FRAMEWORK ........................................................................................................................... 138

4.6. CHAPTER SUMMARY ...................................................................................................... 140

xv

CHAPTER 5 - DISCUSSION, RECOMMENDATION AND CONCLUSION................... 143

5.1. DISCUSSION ....................................................................................................................... 143

5.1.1. Research Objective 1……...………………………………………………………..143






5.2. RECOMMENDATIONS ...................................................................................................... 149

5.2.1. Managerial Implications ............................................................................................. 149

5.2.2. Limitations and Future Research Directions .............................................................. 154

5.3. CONCLUSION….………………………………………………………………………....155

REFERENCES .......................................................................................................................... 158

APPENDICES ............................................................................................................................ 184

xvi

LIST OF APPENDICES

Appendix - I (Research Survey Questionnaire) ........................................................................... 184

Appendix - II (Confirmatory Factor Analysis of all Constructs) ................................................ 189

xvii

LIST OF TABLES

Table no Table Descriptions Page no

Table 1.1. Summarizing Research Gaps and Derivation of Research Hypotheses of Study ......... 12

Table 2.1. Survey evidence pertaining to the conceptualization of business model ..................... 23

Table 2.2. Survey evidence pertaining to the antecedents of business model innovation ............. 64

Table 3.1. Exploratory Factor Analysis for the Scale of Innovation Capabilities ......................... 87

Table 3.2. Exploratory Factor Analysis for the Scale of Service Innovation Success .................. 88

Table 3.3. Exploratory Factor Analysis for Management Entrepreneurial Orientation Scale ....... 90

Table 3.4. Exploratory Factor Analysis for Employee Resistance Scale ...................................... 92

Table 3.5. Exploratory Factor Analysis for Business Model Innovation Scale ............................. 95

Table 3.6. Summarizing the Overall Results of Exploratory Factor Analysis .............................. 97

Table 3.7. Reliability Analysis of Constructs and Sub-constructs after Extraction ...................... 99

Table 3.9. Discriminate Analysis of innovation capabilities scale .............................................. 103

Table 3.10. Discriminate Analysis of innovation success scale .................................................. 104

Table 3.11. Discriminate Analysis of entrepreneurial orientation scale ...................................... 105

Table 3.12. Discriminate Analysis of employee resistance scale ................................................ 106

Table 3.13. Discriminate Analysis of business model innovation scale ...................................... 108

Table 3.14. Summarizing the Reliability and Validity Iteration Outcome .................................. 110

Table 4.1. Demographic Analysis of Research Survey Participants ........................................... 114

Table 4.2. Descriptive Analysis among Study Variables ............................................................ 115

Table 4.3. Correlation Analysis among Study Variables ............................................................ 116

Table 4.4. Results of Data Normality .......................................................................................... 119

Table 4.5. Multicollinearity Statistics of Study Variables ........................................................... 121

Table 4.6. Regressing IV against DV in Simple Linear Regression ........................................... 121

Table 4.7 Mediation Model Coefficients of Study Variables ...................................................... 122

Table 4.8. Total Effect, Direct and Indirect Model of Mediation Analysis ................................. 123

Table 4.9. Model Coefficients for Moderation Effect of Employee Resistance on X and Y ...... 124

Table 4.10. Conditional Effect of X on Y at values of Employee Resistance (W) ..................... 125

Table 4.11. Model Coefficients for Moderation Effect of Employee Resistance on X and M ... 127

Table 4.12. Model Coefficients for Moderation Effect of Entrepreneurial Orientation on X and Y

..................................................................................................................................................... 128

Table 4.13. Conditional effect of X on Y at values of Entrepreneurial Orientation (Z) ............. 129

xviii

Table 4.14. Model Coefficient for Moderation Effect of Entrepreneurial Orientation on X and M

..................................................................................................................................................... 131

Table 4.15. Moderation Effects of W and Z with Putative Mediator Held Constant .................. 133

Table 4.16. Conditional Effect of X on Y at values of Both Moderators W and Z ..................... 134

Table 4.17. Coefficients for Hypothesized Research Model of Study ........................................ 136

Table 4.18. Conditional Direct, Indirect Effect of X on Y at values of Moderators ................... 137

Table 4.19. Model Fitness Summary of Hypothesized Theoretical Framework ......................... 138

Table 4.20. Summarizing Results of Research Hypotheses ........................................................ 141

xix

LIST OF FIGURES

Figure no Figure Descriptions Page no

Figure 3.1. Hypothesized Conceptual Framework of Research Study .......................................... 73

Figure 3.2. Scree Plot for Innovation Capabilities Scale ............................................................... 88

Figure 3.3. Scree Plot for Innovation Success Scale ..................................................................... 90

Figure 3.4. Scree Plot for Management Entrepreneurial Orientation Scale .................................. 92

Figure 3.5. Scree Plot for Employee Resistance Scale .................................................................. 94

Figure 3.6. Scree Plot for Business Model Innovation Scale ........................................................ 97

Figure 4.1. Scatterplot depicting Linearity of Residuals ............................................................. 120

Figure 4.2. Statistical Diagram of Table 4.7 ................................................................................ 122

Figure 4.3. Statistical Diagram of Table 4.9 ................................................................................ 124

Figure 4.4. Moderating effect of W on relationship of X and Y ................................................. 125

Figure 4.5. Statistical Diagram of Table 4.11 .............................................................................. 127


Figure 4.7. Moderating effect of Z on relationship of X and Y ................................................... 130



Figure 4.10. Statistical Diagram of Table 4.17 ............................................................................ 136

Figure 4.11. Single Measurement Model of Hypothesized Research Model .............................. 139

IMPACT OF SIC ON BMI: A DUAL MODERATED MEDIATION ANALYSIS

1

CHAPTER 1

INTRODUCTION

Today is the era of growing technological advancements. Organizations are constantly

striving for running their business in new ways. It is a need for organizations to further innovate

in the domain of business model itself (Chung, Choi & Du, 2017). Globalization has also opened

new ways of doing business for the organizations. Therefore, the sustainability of continuous

innovation in business models is something very critical among the market players. This opens the

question that how an organization can sustain innovation in existing business models and the

success of new services among such ever-changing market dynamics?

This research work aims to study the factors and enablers of business model innovation

and their nature of complex interaction among each other specifically in the cultural context of

Pakistan. This section briefly discusses the background of the research study, identification of gap

analysis, the specific problem statement of this research study, objectives of the research study,

research questions, the contribution of this research study and lastly, the dissertation structure.

1.1. Background of the Study

Growing market competition, increasing technological advances, and globalization itself

have led the organizations to pursue innovation for sustainability. The essence of bringing change

in business models is thought to be essential for overall business success (Spieth & Meissner Nee

Schuchert, 2018). It reflects that the business model(s) may not be viewed as persistent with static

nature in the current world. Business model innovation posits the new ways of doing business with

an objective to create, capture and deliver value to customers as well as other stakeholders (Bashir

& Verma, 2019). The organizations have recognized that innovation in the business model(s)

necessitates a viable extent of profitability. Now, the organizations are needed to capitalize in

emerging market opportunities in order to meet the evolving wants of customers and potential

markets in a valued manner. Subsequently, it essential to illustrate that business model innovation

is a means for an organization to grow profitably (Teece, 2018).


2

In addition, the present intense competitive market dynamics of organizations further calls

the need for them to behave quite vibrant in innovation capabilities for capturing the on-going

technological developments. In pursuit of sustaining the existing market share piece, the

organizations need to get more malleable towards their capabilities for the creation of value in the

existing business model (Teece, 2018). Innovating the existing business model and adopting the

new business model in parallel with an existing parental business model are the emerging

approaches of the organization to endure the market competition. Therefore, it can be said that the

business model innovation may be largely determined and influenced by the innovation

capabilities of the organization (Teece, 2018). The planning, developing, crafting, implementation

and altering the business models are also sequential to the innovation capabilities of the

organization (Teece, 2018). However, there exists very little empirical evidences on the

consequential influence of innovation capabilities.

Innovation capabilities may bring innovation outcomes in delivered services to the

customer with more satisfaction. Steadily streams of researches are attempting to identify the

factors that contribute to innovation success. However, it is necessary to state that “service

innovation success” may not be confused with “innovativeness” as it is something different from

it. Service innovation success reflects the outcome of innovation process in terms of success

achieved in new launched or offered service (Riel, Lemmink & Ouwersloot, 2004; Baker &

Sinkula, 2009) while on the other hand, innovativeness refers to the extent of openness of an

organization towards the new ideas (Hult & Ketchen, 2001; Hamel, 2000; Verhees & Meulenberg,

2004). The researches from the discipline of strategic management and corporate entrepreneurship

are manifest with the fact that the service innovation success is a principal means through which

an organization manages to expand its consumer base as well as service markets. However, the

literature evidence that service innovation success may not contribute to the overall profitability

of the organization (Pelham, 1997; Baker & Sinkula, 2009). The success of the new service itself

represents an excellent performance of new service but contextually, at the expense of existing

services i.e. such as cannibalization (Chandy & Tellis, 1998). It may further pave the way for the

business model innovation for the organization.

Besides that, there might be multiple elements from corporate entrepreneurship discipline

that are also linked with business model innovation and even some are highlighted in literature-


3

based bibliographic researches documented for future avenues of research (Scheinder & Speith,

2014; Bashir & Verma, 2019). Among those, management entrepreneurial orientation and

employee resistance to change are the prominent notions that are pinpointed by recent researches

on business model innovation that needs to be studied further (Foss & Saebi, 2018).

It would not be incorrect to proclaim that innovation lies at the heart of entrepreneurship,

however, all forms of innovation are not the result of strong entrepreneurial orientation. Each and

every organization or firm regulate the innovation routinely i.e. may be newness brought in

response to competitors action. However, the entrepreneurial orientation triggered innovations is

somewhat more than the adaptation or responses to ongoing market trends. The innovation

triggered by entrepreneurial orientation is basically rejuvenation, redefining the concepts and

renewal in nature (Covin & Miles, 1999) that may influence the overall business model of the

organization. The organizations with strong entrepreneurial orientation are more indulged in

activities to establish new service concepts aiming to address the present on-going customer needs

(Baker & Sinkula, 2009). However, it may not be as simple as it could be assumed. Organizations

operating in real-world hinge on the human capital (employee) for the successful transaction of

activities. These employees are the ones who carry the cognitive and behavioral processes for the

pursuit of personal as well as organizational goals. There exists a vast amount of literature since

the late 1950s that advocates that the resistance from employees is something natural obstacle in

ways of change or implementation of something new or better version. This fact is also pointed by

a researcher to be further explored. Vaznyte and Andries (2019) pointed out that more empirical

researches are needed to investigate the effect of employee resistance in effecting the extent of

business model innovation.

1.2. Gap Analysis

The review of the literature reveals that the notion of business model innovation is the

recently evolved (Bashir & Verma, 2019; Spieth & Schneider, 2016). The researches on this

recently evolved construct have failed to achieve the consensus and general belief that what are

the factors that constitute the business model innovation (Mintzberg, 2017; Saebi, Lien, & Foss,

2017; Trapp, Voigt, & Brem, 2018; Bashir & Verma, 2019). The existing researches on business

model innovation are not harmonized with each other (Bashir & Verma, 2019; Scheinder & Speith,

2014). There exists incoherency in the dimensions of business model innovation among


4

researchers in various different directions (Bashir & Verma, 2019; Foss & Saebi, 2017; Scheinder

& Speith, 2014). This issue of incoherence among the studies may be obvious because the concept

of business model innovation is the recently evolved construct and presentation of different

aspects, viewpoints and debates serve as the foundation for the knowledge building mechanism

(Spieth, Schneckenberg, & Ricart, 2014). Resultantly, this may not be fruitful for the general

agreement on the operationalization of concept over the newly emerging concept. This has created

a gap in the existing knowledge body as well as the managers to understand the mechanism of

business model innovation in the real world. The understanding of what constitutes and contributes

to the business model innovation is something essential for the managers or practitioners to be

familiar with. Some of the researches have presented their viewpoints on the elements or

constituents of business model innovation, but no or negligible empirical evidence of these

viewpoints further doubts the generalizability of their statement (Bashir & Verma, 2019; Foss &

Saebi, 2018). A very little is also known on the matter that what are the factors that instigate or

influences this business model innovation in the organization (Bashir & Verma, 2019; Teece,

2018; Foss & Saebi, 2018; Hossain, 2018; Geissdoerfer et al., 2018). This highlights that the

problems exist in the existing literature of business model innovation.

Furthermore, the review of extensive literature on business model innovation reveals that

most of them have adopted the qualitative research method and limited or few researches are

available with empirical testing of the operationalization. This also indicates a gap in the literature

body. Geissdoerfer, Vladimirova, Van Fossen and Evans (2018) also debated that future researches

necessarily needs to validate the dimensions of business model innovation through empirical

analysis in different cultural contexts. Scheinder and Speith (2014) also argued that more cross-

cultural empirical researches are needed to validate the adaption of business model innovation in

different cultural contexts. There is a need for future researches to bring coherence and legalize

the components that constitute the business model innovation through empirical analysis (Bashir

& Verma, 2019; Foss & Saebi, 2017, 2018). This establishes the need to empirically validate the

dimensions of business model innovation in pursuance of goal to generate foci of

operationalization in a specific direction for the overall uniformity (Bashir & Verma, 2019;

Hossain, 2018; Geissdoerfer et al., 2018). This also serves as a research gap in the existing body

of knowledge. It is also crucial to state that the economies of western counterparts are different

than the developing economies in their institution, infrastructural and economic structures. The


5

researches on business model innovation conducted in the West need to be reconsidered, validated

and tested for further modification, alteration, and extension of theories/conception among the

developing countries. This fact is also argued earlier by Hofstede (2001) who conducted the

research in a global context. Hosfstede (2001) found that Pakistan, being the state in South-Asian

region, possess the score of 70 for preference to avoid the uncertainty that was too high in

comparison to other countries like the United States (46), Canada (48), Denmark (23) and United

Kingdom (35). This reflects that the cultural context of Pakistan is less keen towards innovation

due to the higher preference of avoiding uncertainty in comparison to the West (Hofstede, 2001)

leading to the need to empirically validate the operationalization of business model innovation in

Pakistani cultural setting.

The extensive of recent researches discloses that the researches on the enablers of business

model innovation are scarce in the present literature body and thus, it paves the further avenues

for forthcoming researches (Bashir & Verma, 2019; Foss & Saebi, 2018, 2017; Scheider & Speith,

2014; Teece, 2018). This stresses a need for forthcoming researches to examine the enablers of

business model innovation (Geissdoerfer et al., 2018; Hossain, 2018; Bashir & Verma, 2019).

Scheider and Speith (2014) also pinpointed certain challenging research questions for forthcoming

researches that also states the need to investigate the factors of business model innovation in

different cultural settings? Teece (2018) has argued that the innovation capabilities may play an

influential role in determining the business model innovation and thus, needs to be further

empirically explored. Similarly, some of the researches have also argued that the complex

interaction of innovation capabilities and business model innovation needs to be further

empirically studied concerning some performance indicator i.e. innovation success (Bashir &

Verma, 2019; Teece, 2018). Thus, they serve as research gaps that may pave the way towards the

development of the research objectives of study.

Foss and Saebi (2018) posed three crucial research challenges for investigating the

antecedent of business model innovation in future researches. These posed research challenges

state that (i) there is a need to study the influence of capabilities as the internal drivers of business

model innovation (Teece, 2018; Bashir & Verma, 2019; Foss & Saebi, 2018), (ii) there is a need

to explore the effect of entrepreneurial orientation or vision in predicting the business model

innovation (Vaznyte & Andries, 2019; Foss & Saebi, 2018), and (iii) there is a need to empirically


6

study the effect of employee resistance in effecting the extent of business model innovation

(Muller, 2019; Foss & Saebi, 2018). Thus, there is a need to study the tentative effect of these

factors on the business model innovation of an organization that serves as a research gap in the

existing body of knowledge.

It is pertinent to mention that the concept of business model innovation falls in the domain

of strategic entrepreneurship. The proponents of the strategic entrepreneurship perspective (Hitt et

al., 2001; Ireland et al., 2003, 2009, 2011) advocate a multi-theoretic approach towards the

strategic entrepreneurship perspective for future avenues of researches. It is because the theory-

based approach allows the new stream of researches to investigate and elaborate on the conceptual

insight phenomenon and enables the researches to illustrate the scientific and systematic reasoning

of some occurrence or non-occurrences. Corley and Gioia (2011) also indicate that the theories are

the instrument by which the investigators enhance the understandings of concepts, paradigms and

their complex nature of association. Thus it surfaces the avenues for exploration and illustration

of new knowledge by apprehending the different viewpoints of concepts, paradigms or

phenomenon through different theoretical approaches or lense (Corley & Gioia, 2011). Prior

researches have called for new researches to empirically study the theory of strategic

entrepreneurship through the lens of different existing foundational theories (Covin & Lumpkin,

2011; Ireland et al., 2003, 2009, 2011; Miller, 2011). Therefore, this research work focuses to

contribute the novelty by investigating the strategic entrepreneurship initiative of business model

innovation through theoretical perspective of force field of change.

1.3. Problem Statement

The problem statement of this work lies in the scope of the strategic entrepreneurship

theoretical perspective (i.e. advancement of knowledge relating business model innovation). The

review of the extensive body of knowledge reveals that there exist some research gaps that need

to be researched for the progression of knowledge in a specific direction. These research gaps are

briefly elaborated in the gap analysis section. In order to fill these identified gaps of the reviewed

literature, this dissertation aims to study the enablers and different factors influencing the business

model innovation specifically in Pakistani cultural context. The problem statement guiding this

research work is as follows;


7

“There is a need to empirically investigate the effect of innovation capabilities on business

model innovation. In addition, there is also a need to further empirically investigate the

mediation effect of service innovation success on the direct effect of innovation capabilities

and business model innovation. Furthermore, there is also a need to further empirically

investigate the moderating effect of employee resistance and management entrepreneurial

orientation on the direct relationship of innovation capabilities and business model

innovation in the cultural context of Pakistan. These are the guiding statement of the

problem of this research study”.

1.4. Objectives of the Research Study

The objectives of this dissertation are as follows;

i. To empirically test the dimensions of business model innovation in the cultural context of

Pakistan.

ii. To examine the role of service innovation capabilities being the predictor of business model

innovation.

iii. To examine the indirect mediation impact of service innovation success on the association

of service innovation capabilities and business model innovation.

iv. To examine the moderation impact of employee resistance on the direct and indirect

association of service innovation capabilities and business model innovation.

v. To examine the moderation impact of management entrepreneurial orientation on the

direct and indirect association of service innovation capabilities and business model

innovation

vi. To examine the overall indirect effect of service innovation capabilities on business model

innovation (through mediation effect of service innovation success) that are further

moderated by employee resistance and management entrepreneurial orientation.

1.5. Research Questions

This research study addresses the answers of following six research questions;


8

RQ 1: What are the main factors that explain the operationalization of business model

innovation among cellular companies in Pakistan?

RQ 2: Do service innovation capabilities associate with business model innovation?

RQ 3: Does service innovation success mediate the relationship between service innovation

capabilities and business model innovation?

RQ 4: Does employee resistance to change moderate the direct and indirect effect of service

innovation capabilities on business model innovation?

RQ 5: Does management entrepreneurial orientation moderate the direct and indirect effect

of service innovation capabilities on business model innovation?

RQ 6: Do the innovation capabilities indirectly affect (through significant mediation effect of

innovation success) the business model innovation, which is further moderated by

employee resistance to change and management entrepreneurial orientation?

1.6. Contribution of the Study

This research work carries six major contributions. Primarily, this research study

contributes to the existing literature body by empirically testing the operationalization of business

model innovation. It is crucial to inform that the majority of previous researches on business model

innovation are found to be qualitative in nature and very few or limited researches have been

carried earlier on the empirical testing of the dimensions of business model innovation up-til-now.

Furthermore, the researchers on the business model innovation do not carry any coherence and

harmony with each other in relevance to the elements of business model innovation. Some of the

researches have also argued that future researches may need to bring coherence and legalize the

components that constitute the business model innovation through empirical analysis (Bashir &

Verma, 2019; Foss & Saebi, 2018, 2017; Geissdoerfer et al., 2018; Clauss, 2017; Scheinder &

Speith, 2014). Thus, the novelty of this work is manifest with the fact that this work will be solitary

that empirically testifies dimensions of BMI in the cultural context of Pakistan.

Secondly, this research work aims to contribute to the body of knowledge by further

exploring the antecedents of business model innovation as the conception of business model


9

innovation is newly emerged and underutilized in the present literature (Bashir & Verma, 2019;

Teece, 2018; Foss & Saebi, 2018, 2017; Geissdoerfer et al., 2018; Speith & Meissner, 2018).

Future researches also indicate the need to further investigate the factors that influences the

interaction and influencing effects of factors on the business model innovation also constitutes as

a research gap in the body of literature (Bashir & Verma, 2019; Teece, 2018; Foss & Saebi, 2018,

2017; Geissdoerfer et al., 2018; Speith & Meissner, 2018). The significance of this work is evident

from the fact that this study attempts to address this gap by investigating some of the antecedent

factors of construct business model innovation.

Thirdly, this research study also contributes to the existing body of literature by attempting

to address some of the identified literary gaps posed by some recent researches (Speith & Messner,

2019; Foss & Saebi, 2018; Teece, 2018; Muller, 2019; Scheinder & Speith, 2014; Bashir & Verma,

2019). These identified research gaps state that there is need to investigate (i) the role of innovation

capabilities as internal driver of business model innovation (Speith & Messner, 2019; Teece,

2018), (ii) the role of entrepreneurial orientation or vision in determining business model

innovation (Vaznyte & Andries, 2019; Foss & Saebi, 2018), and (iii) the role of employee

resistance in influencing the business model innovation of the organization (Foss & Saebi, 2018;

Muller, 2019). This research work has contributed to the body of literature by closing these posed

future research avenues by certain recent research studies.

Fourthly, this research work attempts to contribute to the existing theoretical body of

knowledge as there is no such agreement or consensus by researchers in existing literature on what

are those factors that determine the innovation capabilities for the attainment and assurance of

service success and business model innovation (Chamsuk et al., 2017; Teece, 2018; Narcizo et al.,

2017). Furthermore, the existing literature does not also pertain to the general consensus on the

particular definition of the concept of service innovation capabilities and there is further need to

validate the concept of service innovative capabilities among different contexts (Chamsuk et al.,

2017; Narcizo et al., 2017). Thus, this research work contributes to the body of knowledge by

validating the concept of innovation capabilities in the cultural context of Pakistan. Furthermore,

this research work is one of the prior researches that have studied the dimensions of innovation

capabilities in the cultural context of Pakistan as no or negligible related research has previously

been conducted.


10

Fifthly, this study attempts to contribute to the body of knowledge by validating, testing

and reconsidering the measures of some crucial constructs (i.e. employee resistance, management

entrepreneurial orientation, and service innovation success) in Pakistani cultural settings. It is

essential to state that these research measures are developed and tested in the West. They require

further modification, alteration, and extension for the application in the Pakistani’s cultural

settings. Moreover, the cultural dynamics of a Western counterpart (in which the conception and

theory of these measures have been developed) are different from Eastern countries like Pakistan

(Hofstede, 1991). Therefore, there is a need to reconsider and validate these measures in Pakistani

culture. This research work is considered to be a pioneer in exploring and studying the relationship

of innovation capabilities, service success, employee resistance, entrepreneurial orientation, and

business model innovation in Pakistani cultural settings.

Lastly, this study signifies itself with the fact that it carries some essential understandings

for the practitioners relating what enables their organization to perform business model innovation.

This information might be beneficial for the managers to understand what are the essential

elements to achieve service innovation success and business model innovation more healthily.

1.7. Dissertation Structure

This dissertation is planned to consist of five chapters.

Chapter 1 namely ‘Introduction’ discusses in detail the background of the study, problem

identification or problem statement, aim/objectives of conducting this research, research questions

and significance/contribution of this research work.

Chapter 2 namely ‘Literature Review’ covers all major past research literature reviews and

theories relating to the research construct. Past and recent researches, theories and concepts

relevant to topic and research constructs collected through primary and secondary sources are

studied, analyzed and reviewed. These instances of reviewed literature are then quoted and

critically presented in this chapter. Then, the research gap is discussed in light of quoted literature.

Based on the identified gap from literature, the hypothesized conceptual framework is discussed

and the hypotheses are drawn reflecting the nature of the relationship between dependent,

independent and mediating/moderating variables of the research work.


11

Chapter 3 namely ‘Research Methodology’ briefly discusses the theoretical underpinnings

of the proposed research model of this study. The theoretical framework, study variables, and

nature of the relationship among the variables are discussed in this chapter. Then, the key study

variables of this research work along with the operational definitions are explained. Then it depicts

in-depth the methodology adopted in this work illustrating the research design, population and

sample frames, sampling strategy used, sample size drawn, research instrument development, and

information about the analytical techniques.

Chapter 4 namely ‘Data Analysis and Results’ covers the analytical/statistical results

drawn by conducting the statistical techniques to check the hypothesized relationships of research

constructs. Descriptive statistics are computed and demographic analysis of respondents is also

tabulated to elaborate on the characteristics of participants. The results of statistical tests conducted

to check the research hypothesis are discussed in the end.

Chapter 5 namely ‘Discussion, Recommendation, and Conclusion’ includes the important

literature review quoted in association with the posed research question and purpose of the study.

The hypothesized relationships of research variables are discussed in link with the analytical

results drawn and the existing theories/researches of vast literature bodies. Then, the major

conclusion of this research work illustrated on the basis of the arguments made in the previous

chapter. Lastly, the practical and managerial implications along with the future research

dimensions are discussed.

1.8. Chapter Summary

Table 1.1 illustrates the research gaps of this study and further explains a mechanism

carried to address these research gaps as,

Table 1.1.

Illustrating Research Gaps and Formulation of Proposed Hypotheses

Research gaps refer

by researcher A mechanism to address the research gap

Contribution

to previous

theories


12

Gap – 1 :

The operationalization of business model

innovation needs empirical analysis as the

majority of the previous researches have opted

for qualitative approach with no or less

empirical analysis (Foss & Saebi, 2018, 2017;

Bashir & Verma, 2019; Geissdoerfer et al.,

2018; Hossain, 2018; Scheider & Spieth, 2014).

• Research objective 1 and research question 1

have been established to address this gap.

• Similarly, the concept of business model

innovation is empirically validated by

conducting the detailed reliability and validity

analysis and composite reliability of the

research instrument of the construct.

S.E Theory

Gap – 2 :

It is vital to investigate influence of innovation

capabilities as a driver of BMI with empirical

analysis (Scheinder & Speith, 2014; Foss &

Saebi, 2018, 2017; Teece, 2018).


have been formed.

• Hypothesis 1, will be formed to address this

research gap. This identified gap may be

addressed by empirically testing this hypothesis

1.

S.E Theory

Gap – 3 :

More empirical researches are needed to testify

the relationships of business model innovation

with the performance indicator i.e. maybe

innovation success (Teece, 2018; Speith &

Messner, 2019).


have been established to address this gap.

• Hypotheses 3 and 4 will be established to

address this research gap. Hypotheses 2 will also

be developed in provision of hypothesis 4. This

identified gap may be addressed by empirically

testing these three hypotheses.

S.E Theory

Gap – 4 :

It is essential to testify the role of employee

resistance on business model innovation

(Muller, 2019; Foss & Saebi, 2018). There is

also a need to explore the moderation effect (i.e.

employee resistance) among innovation

capabilities and service success (Hao & Yu,

2011; Muller, 2019)


have been established.

• Hypotheses 5 and 6 will be formed to address

this research gap. This identified gap may be

addressed by empirically testing these

hypotheses.

S.E Theory

and

F.F Theory

of Change

Gap – 5 :

It is essential to testify the influence of

management entrepreneurial orientation in

shaping business model innovation (Foss &

Saebi, 2018; Vaznyte & Andries, 2019).


have been established.

• Hypotheses 7 and 8 will be formed to address

this research gap. This identified gap may be

addressed by empirically testing these

hypotheses.

S.E Theory

and

F.F Theory

of Change

Gap – 6 :

There is a need to bring deep insight into the

antecedents of the business model innovation.

The number of researches indicated that no

researches have been carried up-till-now relating

the antecedents of the business model

• Research objective 6, research question 6 is

formed to address this gap. Further, hypotheses 9

and 10 will be formulated to testify the overall

research model of this research work.

S.E Theory

and

F.F Theory

of Change


13

innovation. Thus it also serves as a research gap.

Business model innovation needs to be explored

as a dependent variable in future researches

(Foss & Saebi, 2018; Bashir & Verma, 2019;

Geissdoerfer et al., 2018; Speith & Meissner,

2018; Hossain, 2018; Saebi, Lien & Foss, 2017).

*whereas S.E Theory =Strategic entrepreneurship theory (Hitt, Ireland & Camp 2001; Ireland, Hitt & Sirmon, 2003; 2011); F.F Theory of

Change = Force Field Theory of Change (Lewin, 1951).

The mentioned six research gaps are further deeply explained and illustrated in light of

extensive literature review in consequent chapter two.


14

CHAPTER 2

LITERATURE REVIEW

This section briefly discusses the existing theories, literature, and researches on study

variables that are business model innovation, service innovation success, innovation capabilities,

management entrepreneurial orientation and employee resistance to change. The critical review of

the theoretical aspect and nature of the relationship among the study variables are also discussed.

The discussion on the association of study variables and hypotheses development further pave the

way towards the formation of a theoretical model of this work.

2.1. Theoretical Foundations of Study

This research work efforts to view strategic entrepreneurship perspective (Hitt et al., 2001;

Ireland et al., 2003, 2009, 2011) through the lens of force field of changes (Lewin, 1951).

2.1.1. Strategic Entrepreneurship Perspective

A strategic entrepreneurship perspective has evolved as the intersection of strategic

management and entrepreneurship by Ireland and colleagues (2001). Strategic entrepreneurship

theory is illustrated as the interplay of strategic and entrepreneurial initiatives that intend to attain

strategic performance in the competitive external environment by focusing on the emerging market

opportunities (Ireland et al., 2001). Pursuing an entrepreneurial mindset along with the regulation

of entrepreneurial culture within the organization with an intention to sense the emerging market

opportunities and then exercising the existing capabilities with effective utilization of resources

for the enhancement of business innovation are some essential parameters of strategic

entrepreneurship initiatives (Ireland et al., 2001, 2003). Mazzei, Ketchen, and Shook (2016)

explained the strategic entrepreneurship theory as a combination of behavior seeking for the new

opportunities as well as the emerging advantages from these opportunities. The scope of strategic

entrepreneurship theory falls in the domain of management body of knowledge. But, there still

exists the necessity to examine this theory in blend with other varied theoretical perspectives

(Mazzei et al., 2016).


15

2.1.2. Force Field Theory of Change

Force field theory of change by Kurt Lewin (1951) is one of the most established, referred

and leading theories of change management. The work of Lewin (1951) states that there are forces

who shape and influence the behaviors of organizational members and these forces are generally

termed as ‘driving forces’. The mere emphasis of Lewin’s work lies at the dynamic or status quo

nature of context that determines the behaviors of organizational members including managers.

The force field theory of change explains that there are two forms of forces (driving forces and

resistive forces) that surround the members working in any organization. These two forces efforts

in the opposite direction to each other, consequently determining the behavior of organizational

members. The theory further explains that when these two opposite forces (driving forces and

resistive forces) are equal in magnitude within the organization, then it creates a state of inertia

(also termed as quasi-stationary equilibrium). The organization can foster no change during this

state of inertia. Lewin (1951) further explains that when the field of these two forces fluctuates

with the change in their magnitudes (i.e. resistive forces higher or lower than the driving forces)

then the behaviors of the organizational members also change. For the organization who pursues

the change implementation, it is desirable that the driving forces should be higher in magnitude in

comparison to resistive forces (Lewin, 1951). The theory further explains that the organization

needs to break the inertia state before introducing the novel changes. At first instance, the

organization requires to identify its current state by knowing the magnitude of the resistance level

and driving forces and pursue to create awareness for the necessity of novel changes. On successful

declaration and acceptance of the necessity of novel changes, an organization needs to implement

its planned action by further involving the members act in a participative manner. Once the desired

novel changes have successfully introduced within the organization, this further paves the way to

ensure the sustainability of these changes by their permanent incorporation (Lewin, 1951). Dent

and Goldberg (1999), Cameron and Green (2015) indicate that the concept of employee resistance

to change originates from the work of Lewin (1951).

2.2. Concepts, Definitions, and Established Researches

This section explains the critical review of different theoretical and conceptual frameworks

of all the study variables of this research work that are innovation capabilities, management


16

entrepreneurial orientation, business model innovation, employee resistance to change and

innovation success. In this section, different standpoints on this variable are discussed in different

ways with an objective to provide deep insight into constructs.

2.2.1. Business Model Innovation (Dependent variable).

The concept of the business model in several decades old (Bellman, 1957) that was thought

to be static in nature. This concept has been originated from the field of corporate practice (George

& Bock, 2011). Notwithstanding the scholars and researchers have invested their considerations

in this field, however no regularly acknowledged definition and comprehension of business model

innovation have yet been established (Saeibi et al., 2017; Bashir & Verma, 2019; Scheinder &

Speith, 2014). The reason behind this diversity in the researcher’s advancement was the missing

association among their concurrent thought – process (Bashir & Verma, 2019; Zott, Amit & Massa,

2011). The existing researches are scattered and were not found to be linked with each other for

the advancement of concept clarity (Saeibi et al., 2017; Bashir & Verma, 2019; Scheinder &

Speith, 2014).

The concept of business model innovation is basically the extension of the existing concept

of a business model. The static business model conception gradually emerged into dynamic

business model innovation when the researchers of entrepreneurship and strategy (in the early

years of the twenty-first century) explained the static concept as a holistic illustration of key

business processes (Zott et al., 2011). Researches on business model innovation have gained great

momentum in present periods. It is vital to inform that the call for research by special issue editions

of the “Long Range Planning” journal in the year of 2013 has primarily played the role of catalyst

for researches on the emergence of business model innovation. Later on, further call for research

from two special issues of “R & D Management” journal and “Global Strategy” journal in the year

of 2015 transparently paved the emergence of business model innovation conception from the

older static business model concept. Thus, it would not be incorrect to proclaim that business

model innovation is the recently evolved concept and that needs to be explored (in terms of concept

clarity, factors driving it and its consequent effects) as also indicated by some researchers

Scheinder and Speith (2014) Foss and Saeibi (2018, 2017) Clauss (2017).


17

The concept of the business model is no more static in the present era. It is something that

needs to managed, sustained and developed with the passage of time (Hedman & Kalling, 2003).

This development is necessary as the external market dynamics of the organization became more

competitive with market shifts and technological advancements. This requires the organization to

improve and develop their existing business models in order to sustain in present competitive

market dynamics. Thus, the business models are the one that seems to be dynamic in nature now

(Teece, 2018; Morris, Schindehutte & Allen, 2005). The continuous changes (in terms of

development) may be denoted as business model innovation.

The review of the existing literature has revealed that different authors have elaborated on

the phenomenon of business model innovation in different aspects. Witell and Lofgren (2013)

explained the business model innovation as the extent of changes in the current business model

either incremental or radical in nature. The researcher explained that the business model innovation

enables the organization to accelerate product and service innovation. This concept is related and

important for the practitioners and academicians due to some reasons. First of all, the business

model innovation reflects an underused cause of value creation. Secondly, the rivals also regard it

difficult to replicate and lastly, the business model innovation can also serve as an essential

competitive tool for the organization (Witell & Lofgren, 2013).

Apart from this illustration of business model innovation in literature, Teece (2018, 2010)

claimed that the business models deceptively look simpler but they cannot be patented. This further

supports the argument that the business models are difficult to replicate by the rivals but due to

some other possible causes. The concept of business model innovation scopes beyond the domain

of product or service innovation only, rather it serves as a tool for attaining a competitive advantage

by strengthening the competitive positioning of the organization among rivals (Teece, 2018, 2010).

2.2.1.1. Dimensions of business model innovation.

Johnson, Scholes, and Whittington (2008) explained the business model innovation as a

constituent of three basic elements that are (i) customer value proposition, (ii) key organizational

resources and process and lastly, (iii) profit formula of the organization. Koen, Bertels, and Elsums

(2011) explained the concept of business model innovation as of three types that are (i) technology,


18

(ii) financial hurdle, and (iii) value network. However, other researches are of the opinion that the

concept of business model innovation delivers uncertain outcomes as the innovation to the

organizational products, services and process requires more investment and time (Amit & Zott,

2012). Santos and Eisenhardt (2009) explained the business model innovation as the realignment

of activities in the present business model of the organization that is something novel to the market

of product or service in which the organization struggles. Gambardella and McGahan (2010)

defined the concept of business model innovation as the novel approach of the organization to

commercialize its existing assets. On the other hand, Casadesus and his colleagues (2012) defined

the concept of business model innovation as the search of an organization to acquire new logistics,

new ways of creating value and new ways of capturing value for all the stakeholders of the

organization. In line with the Casadesus and Richart (2012) explanation, another investigator has

also differentiated the business model innovation in terms of value creation, value proposition and

value capture for all the stakeholders of the organization (Richter, 2013). Comes and Berniker

(2008) claimed that the business model innovation carries the answers of the two important

questions that are (i) what value does the organization deliver to its customers? And how does this

delivered value benefit (i.e. financial, value chain, organizational structure, etc.) the organization

back? Yunus, Moingeon, and Lehmann-Ortega (2010) explained that the business model

innovation comprises of three elements of value proposition, profit equation, and value

constellation. The value proposition refers to the description of the customer and the value

delivered to those customers. The profit equation answers the questions that how the value is

captured from the revenue generation mechanism through a value proposition. The third element

value constellation refers to the mechanism that how the organization may deliver the promised

value to its customers. On the other hand, another researcher claimed that the business model

innovation comprises of three capabilities of strategic sensitivity, resource fluidity, and leadership

unit.

The literature review also reveals that the concept of business model innovation is most

limitedly debated than any other concept in the field of strategy. The middle layer managers play

an essential role in regulating business model innovation (Hossain, 2017). Managerial and

entrepreneurial skills affect the extent of innovation in business models (Hossain, 2017). Basically,

the business model innovation process is accelerated and flourished by the strategic activities of


19

experimenting, abstracting and reframing the existing business models (Doz & Kosonen, 2010).

However, some organizations put behind low-cost methods for the overall improvement in

profitability. This fact is also argued by Hinterhuber and Liozu (2014) who argued that the majority

of the organizations stress the innovation in new products or services. However, the innovation in

pricing strategies of product or service may also be a powerful tool in the hands of an organization

for the attainment of competitive advantage. In a competitive environment, the suppressed and

week (in terms of the competition) organization uses the pricing innovation as a defensive strategy

to bring innovation in the business model for its stability (Velu, 2016). It is essential for the

organization to bring innovation in its business model through a generative cognition mechanism

as a proactive approach (Geissdoerfer et al., 2018).

However, the existing management theories need more detailed precision relating to the

manner the business models of the organization get innovated (Fuller & Haefliger, 2013). The

managers are essential to understanding the in-depth complexities of the ongoing innovation and

factors of business model innovation (Fuller & Haefliger, 2013). Basically, the business model

innovation effectuates the firm on a broader level. It is because the phenomenon of business model

innovation itself requires the organizational restructuring that is not similar in the cases of the other

forms of innovations. In this regard, the participation of top management is fundamental for the

attainment of business model innovation. The relational dynamics by managers are key for the

business model innovation at informal levels within the organization (Zott et al., 2012). This fact

is also supported by Doz and Kosonen who argued that the role of leadership in bringing innovation

at the business model is necessarily critical for fostering leadership unity. The facilitative activities

(such as dialogue, alignment, and collaboration among all levels of the organization) need to be

encouraged by the organization to attain leadership unity. In parallel to this, the cross-functional

teams and individual behaviors of acceptance or resistance may also possess an influential role on

the extent of business model innovation. The organizations need to be flexible in this regard as the

mechanism of business model innovation involves the transfer of existing business models from

one market to another (Amit and Zott, 2009). The organization needs to be flexible with respect to

their internal customers (that are employees) and patience for business failure due to innovation in

the business model. This business failure may be caused by some cost structures, unit margins or

some false assumptions of innovation or the velocity of the external environment dynamics


20

(Schirmer, Hartmann, Bertel, & Echtler, 2015). Business model innovation is no more a static

process and overall the organization’s intention to improve its business models always possess a

positive impact on its ability to perform. However, it was argued in the existing literature that new

organizations with the low level of business model innovation may be studied to be successful in

the longer run in comparison to those new organizations who possess the moderate level of

business model innovation (Velu, 2016). It means that the new organizations experience a decrease

in the survival challenge as the extent of business model innovation increases.

Despite a wide disagreement among the different researches on the conceptualization and

clarity of concept between the researchers, they generally agree on a point that business model

innovation articulates the value creation. It involves the different values promised to deliver to the

customer and their interrelation among each other (McGrath, 2010) while on the other hand, value

proposition refers to how value is delivered to the customer (Teece, 2010). Although it is believed

that the integration of product and service delivery business models may be essential for the

creation of value for the customers. As the delivery of service may be viewed as the strategic

complement to the product with an intention to please the customer. But it is essential to mention

that providing the service along with the product may not be sufficient enough to create and capture

the value for the customer. Innovation in business model may another footstep for the value

creation and capture. Johnson et al., (2008) pointed out that business model innovation may

possess the luminous value proposition, as the offered complementary services may not address

the same need of value.

Innovation in business model may be of two folds for the organizations (i) with the

integration of new technological advancement or (ii) adoption, experimenting of new ideas.

Innovation in business model may acquire through the integration of updated technological

advancement for the creation of value. But, technological innovation may not prove popular

enough in comparison to innovative ideas (Chesbrough, 2010). It may happen that the simple novel

idea with a great business model may create more value to the customer than the business model

with superior technology offerings. Capturing the value basically requires the demonstration of

value creation, generation of business model options or choices, further identification of the risks

for each option proposed during generation of business model, prioritize the risk elements,


21

reducing the extent of risk through experimentation and doing homework for incubation (Euchner

& Ganguly, 2014). This process approach towards the capture of value may yield an effective

innovation in business model (Euchner & Ganguly, 2014). Option choices are critical for

innovation in the business model. Poor option choices may yield week business model innovation

while the strong option choices (i.e complementary product offerings etc.) may consequent to

strong business model innovation (Fuller & Haefliger, 2013). Although, the business model

innovation involves the phenomenon that how an organization may capture value for the customers

from their product or service offerings. Still this phenomenon carries the complex decision

processes with heavy investments, costs for the acquisition of new required resources,

orchestrating of existing business processes and the efforts to overcome the internal resistance

from employees (Desyllas & Sako, 2013).

Furthermore, the role of the manager in identifying the external opportunity, searching for

new business models, experimenting the new ideas and implementing at the appropriate time are

some fundamental aspects of business model innovation. An organization may observe some

differences among the implementation of the new business model either completely replacing the

existing business model or implemented parallel with the in-practice business model. In secondary

case, the organization attempts to overcome the failure risks by pilot testing the new business

model in single business-unit or small targeted market for a restricted time period (Bucherer, Eisert

& Gassmann, 2012). The organization may have the option to revert back to the previous old

business model (parallel in practice) in case the new business model met with failures. However,

running a new business model parallel with the existing old business model would require some

additional separate business units either partially centralized with other functioning of an

organization or completely independent (Bucherer, Eisert & Gassmann, 2012).

2.2.1.2. Research Gap - 1: Operationalization of BMI needs further empirical validation.

(Foss & Saebi, 2018, 2017; Bashir & Verma, 2019; Geissdoerfer et al., 2018; Hossain, 2018;

Scheider & Spieth, 2014)

Extensive previous researches are available on the literature of business model (Lambert

& Davidson, 2013; Wirtz, Pistoia, Ullrich & Gottel, 2016) however, the extensive review of an

existing body of knowledge reveal that the only limited articles (by Schneider & Spieth, 2014;


22

Saebi et al., 2017; Teece, 2018, Geissdoerfer et al., 2018; Bashir & Verma, 2019) specifically

reviews the literature streams of business model innovation. These researches discussed in detailed

the present literature stream of business model innovation identified the research gaps and set forth

the potential research questions for the promotion of new researches on the clarity of conception

and development of theoretical frameworks. Foss and Saebi (2018, 2017) argued that there exists

a little agreement by researchers on the dimensionality of business model innovation. The

researcher also claimed that up till now no systematic and empirical analysis of dimensionalization

of business model innovation has been carried out that pinpoints the research gap in present

knowledge body. Scheinder and Speith (2014) also indicated that there is a need to further examine

the factors of business model innovation in different cultural settings in order to establish a better

understanding of business model innovation. Scheider and Speith (2014) posed some research

questions for future researches that includes “what constitutes the factors of business model

innovation among different cultural settings?” and “which general forms of business model

innovation can be notorious among different cultural settings?”. Similarly, Geissdoerfer and

colleagues (2018) debated that future researches necessarily needs to validate the dimensions of

business model innovation through empirical analysis in different cultural contexts. Saebi, Lien,

and Foss (2016) also argued that more cross-cultural empirical researches are needed to validate

the adaption of business model innovation in different cultural contexts. Saeibi et al., (2017) and

Hossain (2018) stated that there is a lack of clarity in existing literature pertaining to the

dimensions and operationalization of business model innovation as this field is emerging one. The

existing new researches are not coordinated and branching off the conception of business model

innovation in various different directions that consequently may not be fruitful for the compact

and general agreement over the new emerging concept. Thus, there is a need for future researches

to bring coherence and legalize the components that constitute the business model innovation

through empirical analysis (Hossain, 2018; Foss & Saebi, 2018, 2017). In this regard, it is essential

to state that Clauss (2017) has developed a research instrument for the measurement of business

model innovation conception after a rigorous scientific research mechanism. However, the

researcher argued that the developed research instrument was validated only in manufacturing

firms and the generalizability of the instrument cannot be promised. The researcher further claimed

that the differences exist in business model innovation among the different industries such as

service business models (Clauss, 2017; Claub et al., 2014). Therefore, future researches are


23

recommended by Clauss (2017) to testify the provided instrument of business model innovation

for the different national cultures and organizations. Thus, this indicates a research gap in present

literature of business model innovation. Below mentioned table 2.1 explains all the major

researches conducted on the conceptualization of business model innovation that further supports

this identified gap discussed in detail.

Table 2.1.

Survey evidence pertaining to the conceptualization of business model innovation

Researches on

BMI

Proposed dimensions

of BMI

Methodology

adopted

Limitation and Future

Research Direction

Spieth &

Meissner

(2018)

• Dynamic BMI

• Relational BMI

• Architectural BMI

A qualitative

approach with

case study

approach

Future studies may broaden the results of

a study by testifying the parameters in

different organizations. Longitudinal

studies are also recommended.

Trapp, Voigt

& Brem (2018)

• New value proposition

• Innovative value

constellation

• New BM to firm

• Integrated into daily

operations

• BM created internally

A qualitative

approach with

interview

method

Future research can evaluate the business

model innovation parameters from the

survey method. Future research is also

called to investigate international

business models in detail.

Teece (2018)

Discussed the conception of

business model innovation in

connection with dynamic

capabilities.

Conceptual

paper

Forthcoming researches are suggested to

testify the influence of innovation

capabilities in bringing innovation among

business

Foss & Saeibi

(2018)

Discussed in detailed the future

avenues of research in three

streams of BMI (dimensions, the

effect of BMI and antecedent of

BMI). Supports the dimensions of

BMI as a constituent of three

constructs in line with Teece

(2010) illustration of BMI

construct.

Literature

Review

Future researches are recommended to

explore the role of BMI as independent,

moderating or mediating and dependent

variable. Few challenging research

questions are posed by the researcher for

future researches.

Geissdoerfer,

Vladimirova,

Van Fossen &

Evans (2018)



connection with service

innovation.

Conceptual

Paper


explore the dimensions of BMI.

Furthermore, it is also suggested that

future researches may take into account

the differentiation among business model

innovation, service innovation, and

product innovation.

Hossain (2018)

Discussed the past, present

research streams on business

model innovation and paved the

way for future researches

Thematic

Analysis This research has suggested that its

elements must be empirically


24

investigated and it is something different

from product and process innovation.

Adrodegari,

Pashou &

Saccani (2017)

Explained the components of

product-service BMI.

• Idea generation,

• Selection of idea

• Requirement analysis

• Implementation and

• Evaluation

Conceptual

Paper

This research has suggested that its

parameters among different sectors and

contexts must be empirically researched

for the advancement of knowledge.

Foss & Saebi

(2017)

Discussed the fifteen years of a

literature review on BMI

Literature

Review

Future researches need to explore and

establish general agreement on constructs

of BMI.

Clauss (2017)

In line with Teece (2010)

illustration of BMI construct

• Value capture

• Value creation and

• Value proposition

Quantitative

approach with

survey method

Future researches are needed to testify the

provided instrument of business model

innovation for the different national

cultures and organizations as the existing

instrument is only tested among

manufacturing firms.

Schneider &

Spieth (2014)

Discussed in detailed the existing

researches and new research

directions on the field of business

model innovation.

Literature

Review

Future researches are needed to explore

the constructs and elements of this newly

evolved concept.

Another essential point to discuss here is that the existing researches on the

conceptual clarity of business model innovation are conceptual in nature or adopted the

qualitative research approach. Furthermore, Foss and Saeibi (2018, 2017); Hossain (2018),

Bashir & Verma (2019), Geissdoerfer et al., (2018); Saeibi, Lien and Foss (2016); and

Scheider and Spieth (2014) also envisions the need to empirically testify the components

and dimensions of business model innovation. This research gap is addressed by empirically

validating the scale comprising of the dimensionality of business model innovation. Detailed

reliability and validity analysis (i.e. through construct validity, composite reliability,

convergent validity and discriminate validity) of the sub-constructs of business model

innovation will be carried in consequent chapters in order to close this research gap.

2.2.2. Service Innovation Capabilities (Independent Variable).

Various researchers have explained the innovation capabilities in various perspectives.

Teece and Pisano (1994) have defined the firm’s innovative capability as those capabilities,


25

abilities and resources of the organization that enables the firms to generate the innovation as an

outcome. They further explained that there are four dimensions that enable the firm innovative

capacity that is culture, resources, competence and networks. Culture is embedded within the firms

and is reflected by what and how things are done by the firm. It basically comprises of the

knowledge, skills embedded within the processes and activities of the firm’s systems. Resources

comprise of the sets of assets, skills and internal abilities of the firms that shapes the competitive

position in external environment. Competence represents the ability of firm to convert the

resources into the outcome of productivity and innovation. It involves the effective grabbing of

marketing opportunities through external environment assessment. On the other hand, networks

form the basis to acquire competitiveness. Organizations through informal and formal networking

acquire the relevant knowledge. This acquired knowledge is then translated into the new business

opportunities by the resources and competence of the firm. Thus, the outcome is the innovative

services.

Swink and Hegarty (1998) defined the innovative capabilities as the ability of the firm to

identify the existing crucial technologies and processes of firms for their further development and

improvement in addition to the integration of new technologies from the outside external

environment. In their research study, Swink and Hegarty (1998) have operationalized the

conception of innovative capabilities as the second-order construct. Its first order constructs are (i)

search for new technologies, (2) processes and equipment developments and (iii) cross-functional

product development. Lawson and Samson (2001) explained the concept of innovation capabilities

as the combination of different capabilities of an organization’s practices, resources and

procedures aimed to bring and adopt the innovation within the organization. It refers to the ability

of the organization to effectively execute and capabilities of the organization to ensure innovation.

In addition, the organization’s human resources, funding and investment channels, operational

champions as the element of time and money all are crucial for the success of any innovative

project in the realm of project management (Lawson & Samson, 2001).

Neely, Filippini, Forza, Vinelli and Hii (2001) has defined the concept of innovation

capabilities as the ability of the organization to produce innovative outputs and continuously

transform the acquired new knowledge or ideas into new products or service offerings to the


26

customer. Neely et al., (2001) presented a theoretical framework illustrating the association

linkage between innovation capability and business performance. The authors explained that the

innovation capabilities cause the organization to perform innovative in terms of product

innovation, process innovation, management system, and organizational innovation. This

innovative performance of the organization impacts the overall business performance in terms of

return on investments, market share, competitive position and value to the customer. Smith, Busi,

Ball, and Meer (2008) argued that the innovation capabilities are comprised of nine factors that

help the organization to build innovation. The author argued that these nine factors of innovation

capabilities are also linked with each other. They are technology, innovation process, corporate

strategy, organizational structure, organizational culture, employees, resources, knowledge

management, and management style & leadership. Nilsson, Regnell, Larsson, and Ritzen (2010)

have defined the innovation capabilities as the multifaceted phenomenon that revolves around

workforce skills, team works, cross-sectional collaboration and many other organizational

characteristics that are related with the innovation. The author has taken the team as the basic unit

of analysis for the study of the conception of innovative capabilities. Innovative teams are treated

as those organizational units that are aimed to produce new products or services to meet the

competitive market needs. Nilsson et al. (2010) presented a three-level conceptual framework

referred to as measuring innovations in teams, illustrating in-depth the concept of innovation

capabilities. It depicts the innovation capability at the team level and the unit of analysis are the

managers and team members. It comprises of three levels that are measurement areas,

measurement factors and finally the measurement inspiration in depth discussed in consequent

paras. The four major measurement areas are the innovation elicitation, project selection, ways of

working and impact. Innovation elicitation represents the measurement area of innovation

capabilities that are more related to innovative ideas identification activities of the project (Nilsson

et al., 2010). Project selection is made on the basis of the most feasible proposal innovation team

got on the terms of finances, resources and time (Nilsson et al., 2010). Project selection is made

on different eligibility criteria including timing, size of project, risk element, internal stakeholders

of the project, external stakeholders and return on investment. Innovation team operates in lieu of

project selection. It may also comprises of the organizational as well as the team capabilities to

run the project, the innovation process and the extent of flexible climate of innovation and

creativity among the team members aimed at ensuring the continuous improvement in processes.


27

The innovation team overall falls accountable for the output of the project and responsible to

communicate the benefits of the project or any other further development if required by the project.

The overall generic objective of any project is to provide beneficial impact on the organization.

The measurement factor that revolves in this measurement area of impact are product features,

interaction, trust, intellectual property rights and standards and practices.

Preez, Louw and Essmann (2006) conducted a synthesis on evolutionary literature on

innovation processes and integrates the latest developments / researches and proposed a conceptual

framework illustrating the conception of innovation capabilities and innovation process. Preez et

al. (2006) argued that there are three factors that are complementary and essential for innovation

capabilities to prove sufficient enough to be innovative for the organization. These three factors of

innovation capabilities include innovation process, knowledge exploitation and organizational

efficacy. Christensen (1995) has proposed a framework that has studied all assets of the firm

inclusive of all innovation capabilities and illustrated the inter-linkages and nature of association

among them. The framework by Christensen proposes that the capabilities of organization can be

classified into three broad categories of tradeable resources, capabilities, technical or functional

capabilities and managerial competencies. These group of capabilities helps the organization to

develop new product and services in addition to the major improvements in existing products or

services. Organization needs a specific combination of these innovation capabilities in order to

achieve higher productivity and sustain its survival in competitive dynamics. Martinez – Roman,

Gamero, Tamayo (2011) argued that the innovation capability is deeply affected by three factors

that are (i) knowledge, (ii) organization and, (iii) human factors. The creation, maintenance,

sharing and preservation of knowledge from the external and internal sources of the firm depicts

the extent of knowledge. Incorporation of new organizational member includes the phenomenon

of acquiring new knowledge from the external environment with an objective to enhance the

innovation capability of the firm. The phenomenon of creation of knowledge within the

organization through providing developmental opportunities to employees. Training and

developmental opportunities may eventually lead to increased learning by the employees and thus,

increase the knowledge acquisition phenomenon inside the organization with the increased

employee’s capacity.


28

2.2.2.1. Review of recent theoretical frameworks of service innovation capabilities.

Aziati, Tasmin, Jia and Abdullah (2014) have explored the concept of innovative

capabilities among the thirty (30) Malaysian food SMEs and have classified the innovation

capabilities into two broad spectra of technological innovation capabilities and business innovation

capabilities. Technological innovation capabilities as explained by Aziati et al. (2014) refers to the

ability of the firm to continuously convert the acquired new knowledge, information and ideas into

the new product offerings, services, structures, processes and systems with the help of the

technology in – a place with an objective to benefit the organization and other internal

stakeholders.

Story, Raddats, Burton, Zolkiewski and Baines (2017) in-depth studied the innovative

capabilities needed to provide the advanced services from the perspectives of three main

organizational actors that are a manufacturer, intermediaries and, customers. The authors discussed

that there are seven key innovative capabilities that are essential for effective service delivery by

these three organizational actors. For manufacturers, there are three innovative capabilities that

could help those foster better services and these three innovative capabilities are (i) need to create

balance among product and service innovation, (ii) Using life service methodologies develop a

customer focused, and (iii) develop synergistic product and service cultures. For intermediaries,

there are two innovative capabilities that could help them provide better-advanced service and

these two innovative capabilities are (i) coordination with a third party and (ii) integration of third-

party product and services. Customers play a crucial role in defining the faith of service

effectiveness as the interaction with customers opens the new ways of thinking for the

manufactures. For the customer, the author defines there are two major innovative capabilities that

are (i) co-creating innovation, and (ii) service outsourcing. Thus, the authors are of the opinion

that this complex interconnectivity of all the network actors together facilitates the effective

service deliveries with the help of these seven innovative capabilities.

Iddris (2016) conducted a research study to study in – depth the conception of innovative

capabilities specifically in the context of supply chain and explored the dimensions of innovative

capabilities. Iddris (2016) explained that the innovation capabilities are comprised of four crucial

dimensions that are idea management, idea implementation, collaboration and finally the learning.

The author argued that together all these four constructs of innovative capabilities helps the


29

organization to foster innovative performance. Idea management as explained by Iddris (2016)

refers to the ability of the firm to convert new acquired knowledge and ideas into the new product

or services offering or improvement in existing product or services. The author further explains

that the idea management enables the firm to strengthen the interactions with other market players

and stakeholders (for example suppliers, manufacturers, customers, business partners, employees,

etc.) for the gathering of new knowledge and ideas. Idea implementation as explained by Iddris

(2016) refers to the transformation of newly acquired knowledge or idea at idea management phase

into the establishment of new processes, practices, technologies and routines within the boundaries

of the organization with the objective to achieve innovative performance.

Collaboration is a crucial construct of innovative capabilities that refers to the positive

interaction and smooth flow of information, acquired knowledge, ideas across all the

organizational members with the intention of facilitating the knowledge sharing with the openness.

Iddris (2016) further explained that the learning forms another essential construct of innovative

capabilities that involves the process of sharing of knowledge along with the preservation of

knowledge for future reference within the organization.

Chamsuk, Fongsuwan and Takala (2017) explained the concept of innovative capabilities

as those abilities required by the group of companies, enterprises and organizations belonging to

same existing / to be an industry for the execution and effective implementation of the new idea.

The authors further explained that the innovative capabilities involve the phases of creation,

development and promotions of all the new established products, services, processes, technologies,

techniques and systems in place. The concept of innovative capabilities is further operationalized

into five dimensions that are (i) product innovative capabilities, (ii) process innovative capabilities,

(iii) service innovative capabilities, (iv) organization innovative capabilities, and (v) marketing

innovative capabilities. Product innovative capabilities as explained by Chamsuk et al. (2017)

refers to the ability of the firm to bring in the new or existing markets both the new developed new

products or services and improved existing products or services with value creation of the firm

before the competitors introduce. Process innovative capabilities as explained by Chamsuk et al.

(2017) refers to the ability of the firm execution of the newly created or improved version of the

production (product or service) and the delivery channels methods. Service innovative capabilities


30

as explained by the author Chamsuk et al. (2017) refers to the ability of the firm to align the

innovative activities of the firm with the organizational goals, core objectives and address the

customer’s / market’s needs with the practical institutionalization of organizational goals in

operational practices at the individual level. Organization innovative capabilities as explained by

Chamsuk et al. (2017) refers to the ability of the firm to regulate such management style within

the organization that can facilitate the innovation-based investment and creates the innovation-

based procedures and practices. Finally, the marketing innovative capabilities as explained by the

Chamsuk et al. (2017) refer to the ability of the firm to introduce effectively and successfully the

new products or services to the new and existing markets.

Chamsuk et al. (2017) further explained that the organization’s needs to focus on its

technological and research development skills that can help the organization in strengthening

innovative capabilities. They further argued that the recent researches have viewed the conception

of innovative capabilities only in the perspective of new product development however, they are

many other critical perspectives and aspects of innovative capabilities that are neglected and need

to be further studied (Chamsuk et al., 2017).

2.2.2.2. Dimensions of service innovation capabilities.

Generally, it is believed that the organization needs to identify its core internal capabilities

and then strive to strengthen them by critically reviewing these internal capabilities. Four

characteristics are necessary for the internal capabilities for the assurance of survival of the

organization in tough competitive dynamics that value, rare, inimitability and non- substitutability

(Barney, 1991). Value refers to the maximized benefits offered to customers in terms of valued

product or services (Barney, 1991). The internal capabilities are termed as valued if they result in

the output of valued product or services to customers. Internal capabilities must only be owned by

the organization itself or few other organizations and thus, non-reachable to the other market

players. If the characteristics of the rarity of internal capabilities are lost by the organization and

more organization tends to access that particular internal capability then this eventually paves the

way towards the competitive parity (Barney, 1991). Similarly, the internal capabilities possessing

the earlier both characteristics of value and rarity if and only if owned by the single / one

organization may eventually open the ways towards the competitive advantage for the parent


31

organization (Barney, 1991). But here lies the condition that the temporary service success could

only be sustainable by the parent company if and only if the competitors are unable to replicate

and duplicate that internal capability. The particular internal capabilities are not replaceable by any

other competitor. If the internal capabilities are value creating, rare and even perfectly inimitable

but lack the in- substitutability element then its results into the zero financial benefit. As the other

market players and competitors are able to counter the parent firm’s value-creating a strategy with

the new substitute that may be offered at lower prices thus results in zero financial earning to

parent firm. Hence it can be said that the internal resources with the value-creating strategies,

rarity, perfectly imitable and non- substitutability would help the firm in building and sustaining

the competitive advantage over the other competitors (Barney, 1991). But the organization needs

to protect these internal capabilities that possess the characteristics of these four crucial elements

of value, rarity, inimitability and non-substitutability (Barney, 1991). Because this is the only

successful way for the firm to achieve innovation success and sustain the overall business success.

However, the work of Barney (1991) carries some critical drawbacks and also received

some critiques (Priem & Butler, 2001). The theory applies to the static external environment of

the organization, however, the environment in which the organizations are operating are carrying

rapid changes with time to time with high velocity thus the theory is least applicable to a dynamic

equilibrium. Furthermore, the term resource and internal capabilities are also used interchangeably

with the lease in-depth illustration of the conception of firm capabilities (Priem & Butler, 2001).

It is also very crucial to state that the capabilities cannot be categorized as resources and possess

some differences from the resources (Amit & Schoemaker, 1993). Resources of the firms are not

something firm-specific but tradable entities while on the other hand, the capabilities are the firm-

specific that helps the firms to engage and maintain its internal resources (Amit & Schoemaker,

1993). Capabilities may also involve those implicit firm’s process that regulates and transfers the

knowledge within the organization. This fact is also widely acknowledged by other researchers as

well (Conner & Prahalad, 1996; Makadok, 2001; Barney, Wright & Ketchen, 2001; Hoopes,

Madsen & Walker, 2003).

The extent of new knowledge and capability to sense an organization possess to run its

operational activities is an essential element of innovation capabilities (Christensen, 1995). The

capabilities to sense aim to improve the understandings of the organizational events or procedures


32

in order to bring clarity into innovative assets and capabilities while on the other hand applying

the new knowledge aims to develop the technologies, processes and techniques to achieve value

and cutting the production costs. All the innovative capabilities associated with the organizational

and managerial innovation inclusive of the capabilities related to technological innovation

represents the process of innovative asset. It may include quality control measures, management

structure development, cultural development, etc. Aesthetic design assets is another form of

innovation capabilities that refers to the innovative capabilities of predicting, explaining and

adopting the on-going market trends (Christensen, 1995). It includes the marketing activities as

well as the interaction of marketing entities for integration of industrial designs for the expression

of artistic and on-going fashion trends in product or service. The high degree of these inter

innovative capabilities linkages results into the higher degree of innovation among the

organizations.

2.2.2.2.1. Sensing customer needs

Sensing the customer needs is a form of innovative capabilities that represents the capacity

of the organizational members to search for the new opportunities in terms of growing unfilled

customer needs and based on these needs, generate the new business idea. It would also enable the

organizational members to sustain the individual knowledge that can help them in bringing the

creativity and new mechanisms of performing assigned tasks in a productive manner (Momeni,

Nielsen and Kafash, 2015). Searching for the new opportunities especially for the organization

who are operating in dynamic market conditions serves as the biggest challenge for the human

resource of the firm (Lichenthaler, 2009). As the first step towards the innovation process, is the

exploration and search for the new external opportunities and the organization that are more good

in searching the opportunities and generating the new ideas are more stronger in their innovative

capabilities. Generation of new ideas is the execution phase of the earlier one whose output is the

new product or service offerings to the customers. A new idea can be transformed into a new

product, new service, any new technology or any new techniques of the management.

The firm acquires the new knowledge about the cost-cutting processes, new technologies and

better performance mechanisms are then acquired from the external environment. It further helps

the firm to decide to what extent the resources needs to allocate at this new idea and what are the

resources that are critical for the development of this new idea brought from the external

environment. Literature has also discussed this phenomenon as sensing new technological trends


33

(Den Hertog, Van der Aa, & De Jong, 2010) that basically refers to the phenomenon of exploring

the new technologies from surrounding and improving the existing technologies in light of the

acquired new information.

2.2.2.2.2. Sensing technological options

Sensing new technology and technological development is a crucial element that produces

the technology-based advantage to the firm by developing the internal technology of the

organization (Swink & Hegarty, 1998). The development of internal process and equipment can

also help the organization in customizing the existing technologies and processes as per the needs

with more efficiency and flexibility. Cross-functional product development is mostly accepted for

the creation of a new product or service. The participation of different functions of the organization

in the development of product, process and design helps the organization in bringing the

customer’s voice into the new product design and promotes the product customization thus

significantly contributes to the innovation capabilities of the firm. However, the cooperation and

collaborative attitude are the must factor for the cross-functional product development.

Capabilities to sense new technological trends contributes to the organizational goals of

achieving innovation and business success. Technological capabilities contribute to the outcome

of new product, service and technology offerings to the customer and are regarded as the most

necessary ingredient of the innovation capabilities of the firm. It paves the way to effectively utilize

the technology into the processes, procedures, techniques, mechanisms and the constituents of the

major organizational programs or events. The extent of the strengthening of the technological

capability of any firm is dependent upon the extent of financial investment and time has been

incurred by the organization for its maintenance and development. Another important aspect that

strengthens the technological capacity of the organization is the learning processes and ample use

of new knowledge for the generation of innovative activities or products.

Smith et al., (2008) also termed the sensing technology as the most crucial and essential

element of innovation capabilities as the progress of innovation process and innovation activities

are highly dependent upon the effective utilization of technology within and across the

organization. Smith et al., (2008) has further categorized the technology element into three sub-

constructs of (i) use of technology, (ii) technical skills and education, and (iii) technology strategy.


34

The construct use of technology represents that to what extent the organization adapts the

technology in daily routine processes to complex issues. The construct technical skills and

education represents the abilities of human resource skills of the organization in the field of

technology. The third construct technology strategy represents the organizational stance toward

technology in strategic planning.

2.2.2.2.3. Conceptualization

Conceptualization is another form of innovation capability that contributes to the ratio of

success of any organization (Lawson & Samson, 2001). It is the ability of the organization to learn,

understand, translate and predict the value-added information and knowledge from the surrounding

competitors and markets into a new idea. Organizations effectively identify the opportunities and

threats by effectively using this innovative capability and proactively adopts the practices in light

of the changes or events occurring in the external environment. The transformation of the new

ideas into the establishment and creation of something is an essential aspect. It is argued that the

creativity serves as the foundation for the innovation that enables the organization to proficiently

gather the new knowledge and ideas, evaluate the applicability and truthfulness and further the

enhance the new ideas into profitable terms.

The new ideas may possess three forms of sources that either the new idea is created actively

or the new idea may be gathered from the existing resources or either it may be sourced from the

internal or external stakeholders of the organization (Nilsson, Regnell, Larsson & Ritzen, 2010).

This newly elicited idea forms the basis of the new project proposal being processed by the

innovative team of the organization at this phase of conceptualization. Innovation

conceptualization as explained by Smith et al., (2008) involves the process of creation, execution

and application of innovation within and across the organization. The author has further classified

this process into three sub-constructs of (i) idea generation, (ii) implementation mechanism, (iii)

selection and evaluation techniques. The author also argued that innovation is also affected by

other factors of leadership styles, employee’s behavior and usage of technology. Thus, it is

pertinent to mention that knowledge in this manner forms the basis for the decision making as the

process of gathering information and assimilating the relevant knowledge is crucial for the decision

making of an appropriate idea for conceptualization. The acquisition of right and relevant


35

knowledge and application of this specific knowledge serves the organization with the innovative

capabilities initiatives in the right direction with the right intensity (Preez et al., 2006). The

organization possesses the appropriate technologies, strategies, culture, structures, policies,

procedures, leadership, management practices and sufficient resources to facilitate the innovative

capabilities initiatives by the organization. Thus, conceptualization plays the foundational role as

innovation requires effective and timely decision making in order to cope with the growing market

changes. Management literature further explained that the conceptualization involves the two key

phases that are thinking of ideas as a possible option and selection of the relevant idea (Sborn,

1992; Soltani, 2008). It is pertinent to mention that the searching the new opportunities and

generating the new ideas both are dependent upon the abilities and skill sets of the organizational

members. For the effective identification of external opportunities, organizations need to

strengthen the knowledge at an organizational level and upgradation of the knowledge with the

new one at the individual level is a crucial aspect for the innovation capabilities.

2.2.2.2.4. Coproducing and Orchestring

Coproducing and orchestring is another form of innovative capabilities that enable the

organization to transform the research and development findings into the new product or service

development with effective quality control and improvement in production processes with an

overall objective to fulfill the market and customer needs. Coproducing and orchestring

capabilities can be enhanced by ensuring the good vendor quality input to the production process,

strong quality control processes, effective pre-testing of new products or services, ensure an

acceptable degree of flexibility in new product, services, customer personalization (Aziati et al.,

2014). It may also enable the organization to assemble, expand and effectively utilize the essential

resources of human skills, technological and financial for the progress of innovation within the

organization. Besides technological innovation activities, any other form of organizational activity

cannot be performed without the financial aspects. Human capital is also another critical aspect of

this capability that carries, fosters and reserves the organizational activities as well as the

knowledge. It is pertinent to mention here that most of the enterprises face the major barrier of

financial strength (for example availability of funds). Thus, an organization possessing the sound

technological innovation capabilities can foster healthy coproducing and orchestring capability

within the organization.


36

Coproducing and orchestring help the organization to ensure the effective utilization of

resources and anticipates the shortages (if any). It helps in maintaining the smooth flow of

knowledge and outputs to achieve the targeted higher productivity. In simple words, co-producing

and orchestring help the sensing customer needs and growing technological trends capabilities to

integrate into conceptualization and consequently combines the physical resources of a firm with

the productive human capabilities (Zawislak et al., 2012).

2.2.2.2.5. Scaling and Stretching

Scaling and stretching capabilities refers to the ability of the firm to interpret the existing

state of the technology of firm and absorb the new technology or product or service and gradually

transform the new technologies into existing operational capacities of firm with an objective to

achieve high degree of technical economic efficiency in business processes (Zawislak et al., 2012).

This forms of innovative capability enable the firm to diffuse new forms of methods, process, and

technologies into the existing organizational process, routines or technology with the objective to

stabilize new product and service to the market. These capabilities are driven by tracing the path-

dependent routines of operational activities with the integration of new technology, product or

service. It may also involve the ability of the firm to cut – down its existing marketing, logistics,

delivery, outsourcing and bargaining costs. Limited researches have also termed this capability as

transaction capability (Zawislak et al., 2012).

Summarizing, each firm acquires some specific set of knowledge that is further translated

into new technology or improved existing technology having some value for the market and thus

could be termed as the ‘firm sells the technology’. This potential technology solution is further

integrated into existing daily operational routines to ensure the production of desired new products

or services at a commercial scale and thus can be termed as ‘creates the operations’. However, the

organization ensures the effective utilization of resources and technologies for production. Still,

the problem lies, that these capabilities do not guarantee the innovation success until unless the

organization possesses the ability to cut-down the different forms of costs to ensure the competitive

position among the market players. This coordination and diffusion function by the scaling and

stretching capabilities serves as a control effort for the other innovative capabilities and could be

termed as ‘guarantees the sale’. The two innovative capabilities conceptualization and co-


37

producing and orchestring play the most critical role in firm innovative performance. The earlier

capability is merely accountable for the creation of new products or services while the latter

capability enables the firm to produce these new products at a commercial scale. However, all the

firm needs another form of the important innovative capability to manage these two capabilities

workable in an organized manner. Thus, scaling capability is required to integrate these two

innovative capabilities and ensure effective coordination among them. But these innovative

capabilities together are not sufficient for the attainment of innovation success and business model

innovation. Organizations need to cut-down their different forms of costs in order to ensure its

leading position among the competitors and this further requires the set of knowledge and abilities.

2.2.2.3. Innovation capabilities sub-construct needs to be validated. (Chamsuk et al.,

2017; Narcizo et al., 2017)

Different researchers have conducted detailed researches on the concept of firm innovative

capabilities in different perspectives of human resource management, distinctive competencies,

human skills, absorptive capacity, organizational capabilities, dynamic capabilities, technological

capabilities, marketing capabilities, etc. There are also some researches who have addressed the

conceptualization of innovative capabilities (Zawislak et al., 2012; Yam et al., 2011; Nisula &

Kianto, 2013; Momeini et al., 2015; Story et al., 2017; Iddris, 2016; Chamsuk et al., 2017).

However, the previous researches have emphasized one or a few specific dimensions of innovative

capabilities such as research and development, new product development, etc (Nisula & Kianto,

2013; Chamsuk et al., 2017). This serves as a gap that there is a need to examine the different

forms of capabilities. In addition, the recent researches have viewed the conception of innovative

capabilities only in the perspective of new product development however, they are many other

critical perspectives and aspects of innovative capabilities that are neglected such as process

development, marketing capabilities, behavioral aspects etc. that needs to be further studied

(Chamsuk et al., 2017)

Narcizo et al., (2017) conducted a bibliometric literature study on the conception of

innovation capabilities and found that the existing literature pertains the nineteen (19) different

conceptual definitions and explanation of innovation capability concept. This concludes that the

researches on the conceptualization of innovation capability carry the variability in explaining the


38

phenomenon itself (Narcizo et al., 2017). Thus, there is a need to bring some coherence in

conceptualization through validation research studies.

Concluding, it is not incorrect to state that still there is a need to further explore the

conception of innovation capabilities as there is no such agreement in existing literature on what

are those factors that determine the innovative capabilities for the attainment and assurance of

service innovation (Zawislak et al., 2012; Nisula & Kianto, 2013; Narcizo et al., 2017). This arises

the need to validate the concept of innovation capabilities. Furthermore, the existing literature does

not also pertain the general consensus on the particular definition of the concept of firm’s

innovative capabilities and there is further need to clarify the concept of firm innovative

capabilities by developing some comprehensive framework (Zawislak et al., 2012; Breznik &

Hisrich, 2014). This points towards the research gap in present literature body.

Thus, this research work has attempted to address this research gap (indicated by Zawislak

et al., 2012; Breznik & Hisrich, 2014; Nisula & Kianto, 2013; Narcizo et al., 2017; Chamsuk et

al., 2017) by reviewing and validating the research construct of innovative capabilities. This

research work has adopted the research instrument of Den Hertog, Van der Aa, and De Jong

(2010). It is pertinent to mention that some of the researchers have already validated this research

instrument in different countries of the globe. However, negligible or no research study has been

conducted to validate this research instrument for the operationalization of innovation capabilities

in the Pakistani’s cultural settings. Consequently, this study contributes to body of knowledge by

extending existing research chain on validation to bring coherence in the definition of innovation

capabilities. Thus, attempting to contribute to closing this identified research gap. The detailed

operationalization and definitions of measures of innovation capabilities are discussed in the

consequent chapter.

2.2.3. Service Innovation Success (Mediating Variable).

The concept of service innovation success became evident and opaque with the passage of

time that it involves the phenomenon in which the renewal is achieved in provided services

(Toivonen & Tuominen, 2006). However, different stakeholders of the organization are involved

in the process of service concept design, service delivery channels and service launch, thus the


39

concept of service innovation is a combination of different elements and stages of new service

offering with a final objective of achieving the customer satisfaction and fulfilling the customer

need in more valuable and profitable manner (Preissel, 2000).

The idea of service innovation has merely evolved by Miles (1993) who has coined the

term service innovation first time in literature. In his research article published in journal namely

“Futures” the author has very deeply illustrated the numerous characteristics of services and in a

step forward, deeply explained the linkage of these characteristics or features of services with the

different forms of innovations. The objective was to illustrate the barriers and arising problems

associated with the service characteristics and make the phenomenon understandable and opaque

for the resolution of the contemporary service innovation-related issues. Miles (1993) has

classified these features of services in four broader terms that are (a) features of services in terms

of service production, (b) features of services in terms of service product, (c) features of services

in terms of services consumption and (d) features of services in terms of services markets. Features

of services associated with the service production basically refer to the five interconnected and

interdependent characteristics of services that pave the way for the enhanced service innovation

success within the organization or enterprise. The second service feature of labor involves the

professionalized skills highly equipped with the interpersonal skills and specialist knowledge are

required but the services have reduced the greater dependence on the expensive labor skills due to

the usage of expert systems and telecommunication. Features of services that are associated with

the service product basically refer to the nature of the product and features of the product. The

nature of the product involves the services processes or services product that are hard to distinguish

and difficult to store or transportation. It involves the material components such as the

membership’s cards, however, telecommunication or electronic channels are used for the purpose

of the order placement, reservations or delivery information. On the other hand, the features of the

product involve those characteristics of services that are customized and personalized as per the

laid down requirements of the end-user. Internets or other electronic protocols are used for the

input of the customer requirement and the other expert systems or software are used by the

organization or enterprise for the storage of customer’s records (i.e. likings, requirements, etc.).

Features of services that are associated with the consumption of the service basically refer to the

delivery of the product, the role of consumer and organization of consumption. Delivery of product

involves the particulars of distribution and consumption with the aspects of time and space. The


40

role of the consumer is crucial for the success of services as the consumer needs or demands

information serves as the input for the design and production of services. The organization of

consumption is somewhat difficult to separate from the production in services. Self-service is

another formal official economies that are found common at some places however technology and

user-friendly software are also services consumption modes fashionable. Features of services that

are associated with the services markets basically refer to the organizations of markets, regulations,

and marketing. Organizations of markets involve the provision of services delivered to end-users

either in governmental bureaucratic sectors or retails sectors. However, now the quasi-markets are

also delivering the services through the privatization or outsourcing of services. Electronic point

of sales and new reservation systems are all growing technological trends of markets organizations.

Regulations are quite common in services either regulated by national bodies or foreign

conventions. Performance indicators and monitoring of laid down basic requirements are made by

the regulating bodies and institutions. Marketing in services involves the guarantees and the

demonstration packages involved for the promotion and placement of services in the market among

the rivals.

A critical review of existing literature reveals that the conception of innovation success is

viewed in three different perspectives in the present literature. The first perspective of this concept

endures the ‘innovation success in services products’ that is new, improved and novel services

may be offered to the customers (Hertog, 2000; Johne and Storey, 1998; Nijssen et al., 2006; Smith

et al., 2007; Menor & Roth, 2007; Storey & Hull, 2010). This perspective of service innovation

success upholds the majority of service development strands of innovation in existing literature

(Johne and Storey, 1998; Nijssen et al., 2006). This perspective of service innovation success is

also contrasted with the concept of technological innovation in literature as the latter one defines

the success of innovation in products. Thus, the literature explains that the innovation in the

product is quite different and distinguishable from innovation in services and therefore the service

innovation needs to be studied as a separate concept (Miles, 1993). Present literature on innovation

pertains to the second perspective of conception on ‘innovation in service processes’ that states

the service innovation as the new, improved and novel way of designing, making, producing and

delivering the service processes. This perspective of service innovation upholds the numerous

researches on the strands of new service delivery mechanisms in the literature (Araujo & Spring,

2006; Chen, Tsou & Huang, 2009; Lenfle & Midler, 2009). The third perspective views the service


41

innovation concept as ‘innovation in service firms, organizations, industries’ in existing theories.

But, the review of the literature has revealed that most of the previous researches on innovation

generally addresses the concept of technological innovation in manufacturing firms and the

concept of service innovation is relatively newer one that is less explored (Toivonen & Tuominen;

2009). However, it is very crucial to state that the concept of service innovation success is serving

as a central driver to economic growth in many developing nations (Toivonen & Tuominen, 2009;

Gallouj & Windrum, 2009). Recent digitization and incorporation of ever-changing technological

advancement in business processes of service industries have revealed that the service innovation

requires more research in the present area (Ostrom, Bitner, Brown, Burkhard, Goul, Smith-

Daniels, Rabinovich, 2010).

Furseth and Cuthberton (2013) explained the service innovation success as the service

innovation triangle that consists of a value, business model, customer experiences, service system,

technology, key internal resources, and strategic capacity. Den Hertog, Van der Aa, and De Jong

(2010) explained that service innovation success consists of, (i) service concept innovation, (ii)

new customer interaction, (iii) set of business partners and new value system, (iv) new revenue

model, (v) new delivery system, (vi) new service delivery system (that is technological). Flikkema,

Jansen, and Sluis (2007) have also defined the concept of service innovation as the

multidisciplinary process of designing, testing, launching and marketing the new services with the

ultimate effort to establish the valuable customer experience.

Edvardsson (1997) has defined the service innovation success as the combination of two

mandatory aspects that are an in-depth understanding of what customers have needed and what

could be the different ways in which the design of the new services may wholly fulfill the needs

of the customer with higher satisfaction. However, there are other factors that may not be

neglected. It may include the customer’s needs of preference (i.e. some demanding needs of the

customer are primary and others are secondary and there is a need to prioritize these need levels

accordingly etc.), and any other associated support services. Consequently, this in-depth

understanding of the service concept may eventually describe the actual value of the services

offered in terms of the success of service innovation.

However, service innovation does not occur as a single activity rather it’s a combination

of a series of activities taking place either in a mutual or sequential manner (Edvardsson, 1997).


42

The services either new or unique are not solely created or developed by the organization but they

are partly co-created by the suppliers that do not fall under the direct control of the organization

itself. However, an organization can set basic parameters and requirements for the suppliers to be

eligible for the success of innovative services co-creation. That is how an organization can

effectively control service innovation success. Three basic aspects of the organization’s service

innovation success are (i) define quality requirements, (ii) understand internal customer’s

expectations, and (iii) understand end customer’s expectations.

Toivonen, Tuaminen and Brax’s (2007) envision the service innovation success as the

value proposition of service innovation. The authors explained that most of the service firms in

today’s world have used the rapid application model of the service innovation process. It can be

used because of the rapid application model of service innovation outcomes the urgent delivery of

service offerings. As the present competitive dynamics of markets call for the urgent need of

service launch so it also provides the opportunity to further develop the service offering in support

of customers or clients along with the existing ongoing operations of the organization to ensure

service innovation success. Furthermore, the development of the new service offering goes parallel

with the service testing or launch by answering the raised queries or issues of the real markets. In

addition, rapid application innovation processes require small investments for the testing and

execution and thus, the risk for economic loss may be minimal with greater chances of service

success.

Furseth and Cuthbertson (2013) explained the service innovation success as the summation

of all the interactions between the service organization and the customer for the offer and delivery

of the services took place. Although the service firms pursuit to deliver all its customers with the

same and equal level of satisfaction and pleasure from an organizational point of view, however,

it varies at customers' end in light of their desires and differentiating personalities. Thus, it is not

incorrect to state that the major part of the concept of service innovation success revolves around

the notion of commercializing the service offerings in a manner that may establish the value not

only for the customers only but the owner of the service firms and the suppliers. Furseth and

Cuthbertson (2013) have defined the value as the custodian of the societal, environmental,

economic and emotional aspects of the services however this description cannot be termed as

universal as the definition of value differs among the different service organizations. Some service


43

organizations may describe it in terms of financial profit or market share while the other may

regard it as the outcome of firm-specific targets. Thus, numerous researches have illustrated the

concept of innovation success specifically in the realm of small and medium enterprises. The

existing literature on service innovation success is dominated by the research studies that are

illustrating the dimensions for service innovation success. This research work has adopted the Riel,

Lemmink, and Ouwersloot (2004) operationalization of service innovation success and measured

the construct with three dimensions. Details on operational definitions and measures of the

constructed service innovation success are discussed in the next chapter.

2.2.4. Employee Resistance to Change (Moderating Variable - 1)

Resistance by employees is considered as one of the basic underlying reason for the

deterioration in the implementation of new initiatives within the organization. Organizational

changes met with failure at first instance due to the resistance of organizational members (Egan &

Fjermestad, 2005). Resistance is a sort of organizational disease that keeps on spreading

(increases) with the passage of time and serves as a barrier for the innovation which an innovative

organization needs to find ways to imitate. Zander (1950) defined the resistance as the behaviors

of organizational members that are directed to protect and preserve themselves from the planned

change. Folger and Skarlicki (1999) explained the resistance as the behavior of seeking challenges,

disruption, invert prevailing planned change assumptions and power relations by the

organizational member. Ashforth and Mael (1998) explained the resistance as the intentional acts

of disobedience and non-cooperation by the organizational members. Brower and Abalofia (1995)

explained the resistance as the intention and act of opposition against the change or responding

passively to change activities.

In fact, the existing literature on the concept, operationalization, and dimensions of

employee resistance to change are well established. The literature also clarifies that there exists a

distinction in causes and the symptoms of employee resistance and managers need to address the

reasons for resistance, not the symptoms (Lewin, 1951; Zander, 1950). A number of researches

have explained and listed the factors that cause the employee resistance to change. Zander (1950)

explained that there are six main reasons due to which resistance to change emerges by the

organizational members, (i) ambiguity in the minds of organizational members who perceives that


44

the change initiatives will coarsely affect them, (ii) carrying and interpreting the change initiative

in diverse and negative manner, (iii) the presence of other strong forces that convinces the

organizational member to oppose the change initiatives, (iv) lack of employee involvement or

participation and the autocratic imposition of change activities by the top management, (v)

resistance due to personal interests of the organizational members, and (vi) lastly, inbuilt ignorance

of organizational members relating the pre-established institution or structures.

Some researchers have also indicated that the ignorance of the skills, abilities of the

organizational members also serves as the cause for them to resist (Hoffman, Festinger &

Lawrence, 1954). The resistance to change emerges and further heightens because the managers

who execute the novel activities misunderstood their employees and the situation of the

organization (Flower, 1962). In the opinion of these managers, implementing the novel changes

and innovation is simple as moving from one position to another. They fail to identify how the

other organizational members will conceive when the novel changes would be implemented.

Lackness in communicating the clarity of the necessity of change is a baseline cause for the

resistance that is self-trouble by the managers who strive for the implementation of novel changes

(Flower, 1962). Resultantly, the members of the organization perceive these implementations as a

threat that can harm their social status at the workplace. The rewards systems and other systems to

acknowledge or recognize the employees are also critical as they determine the behavior of the

employees thus consequents to the innovative or non-innovative aptitude among the human skills

of the organization.

There could be other factors like the personal interests of the individual that fosters them to

deviate the implementation of novel changes. Generally, the managers strive to bring change in

the existing status quo of organization with the foundational goal of profit maximization and

safeguarding organizational survival. The organizational change may be either for the cost

minimization, service quality standards, innovation adoption, increased productivity or process

product developments. It all requires the organization to merely become self-centered. However,

the members of the organization also pursue some personal interests. The organizational pursuit

for the change approach may be in clash with the personal interests or goals of the organizational

members. This prospective conflict between the interests of the organizational members and the


45

interests of the organization is widely considered as the heart of management sciences (Barnard,

1938). Different established theories also advocate these diverging interests between the

organizational owners and the employees (Mitnick, 1982). The literature theorizes that the

organization pursues the interests of maximizing the profits by cutting the organizational expenses

either through paying less while on the other hand employees are more interested in less work with

more pay or wages. This heightens the conflict among the owner and employee. The employee’s

stance of opposition to the organizational viewpoint is termed as resistance (Keen, 1981). Strebel

(1996) also advocated that the owners and members of the organization both pursue the give-and-

take obligations and commitment with each other and this give-and-take obligation between the

two, further shapes their behaviors and relationship. Implementation of any novel idea that detritus

the personal compacts of the organizational members would necessarily be resisted by the

members (Strebel, 1996).

Literature also identifies the psychological aspects of the individuals as a reason for the

resistance to implied novel changes (Dent & Goldberg, 1999; Kegan & Lahey, 2001; Oreg, 2003;

Coch & French, 1948). Some researches explained that resistance is a product of context in which

the novel changes are going to take place and the behavior of individuals or groups (Dent &

Goldberg, 1999; Lewin, 1951). Thus, imposing novel changes may not be fruitful until and unless

the factors of organizational context may be molded as per the desired requirements (Dent &

Goldberg, 1999; Lewin, 1951). Expectations of employees versus the expectations of the

employers basically refer to these factors of organizational context (Rousseau, 1995). The

employees expect facilitative and valued pays, rewards, developmental opportunities, career

growth paths, etc. from their organizations. While on the other hand, the employers expect that the

employees may behave more proprietor towards the organizational goals, work efforts,

commitment and responsibility, etc. The stability prevails within the organization until the time

the expectation from both sides stays compatible. But, when such novel changes are introduced

that may imbalance the factor of the employee’s expectation to lower scale (in contrast to

employer’s expectation), it paves way for the resistance (Rousseau, 1995).

Besides the factors of organizational context and participative role of employees as

tempering towards the resistance level, the psychological disposition of the organizational


46

members is influentially accepted as the contributing element of resistance to change (Oreg, 2003,

2006, 2008, 2011; Burnes, 2014). In recent researches in this field, the individual is termed as the

main source of resistance in comparison to the organizational factors (Oreg, 2003, 2006, 2008;

Oreg & Sverdlik, 2011; Burnes, 2014). An organization possesses the individuals with varying

degrees of psychological disposition of acceptance or rejection towards the novel changes (Oreg,

2003). The members who possess a higher level of psychological disposition mainly holds the

negative or opposing approach towards the novel changes. While on the other hand, the members

who possess the lower level of psychological disposition are of those who accept the change or

engages themselves in novel changes with the passage of time (Oreg, 2003). This level of

psychological disposition is measured by the four personality attributes of routine seeking

behavior, cognitive rigidity, the emotional reaction towards the implanted changes and the short

term focus of the individual (Oreg, 2003). The researchers also agreed that the individuals who are

close-minded, rigid in nature prove to be less willing to introduced new ideas, situations, things or

events (Fox, 1999; Lau & Woodman, 1995; Oreg, 2003). This close-mindedness and rigid behavior

shape the cognitive rigidity of individuals (Oreg, 2003).

A past extensive literature has been reviewed on the concept and established

operationalization of employee resistance to change. This research work has adopted the Oreg

(2003) operationalization of employee resistance because of its consistency in development and

widely validation by different researchers in different contexts have made it as one of influential

research measure of existing literature. The construct employee resistance to change has been

operationalized into five sub-constructs of routine seeking, emotional reaction, short term thinking

and cognitive rigidity (Oreg, 2003). Details on operational definitions and measures of the

construct employee resistance to change are discussed in the next chapter.

2.2.5. Management Entrepreneurial Orientation (Moderating Variable - 2).

The concept of ‘Entrepreneurial orientation’ belongs to the field of strategic

entrepreneurship and being considered as a form of strategic orientation in the existing body of

knowledge that involves the entrepreneurial aspects of an organization’s strategic planning

(Wiklund & Shepherd, 2005). Entrepreneurship is a distinctive characteristic that distinguishes the

traditional manager and employees from the entrepreneurs. Entrepreneurs are those members of


47

the organization that are always in continuous search for innovative and proactive activities (Choo

& Lee, 2018). However, the traditional managers, employees and other members of the

organization slightly or larger possess the tendency to avoid risk-taking entrepreneurial actions

(Choo & Lee, 2018). Thus, the literature evidence that the continuous search for new business

opportunities and creating those opportunities into new values for growth as well as for the

customer are the real facet of entrepreneurial members of the organization (Brockhaus, 1980;

McClelland, 1961).

The review of existing literature on entrepreneurial orientation reveals that recently this

concept has become one of the promising area of research in entrepreneurship and strategic

management literature (Wales, 2016; Campos, 2018). The recent researches illuminate the concept

of an entrepreneurial orientation as a necessary condition for the organizations that desire to sustain

in competitive market environments (Choo & Lee, 2018; Campos, 2018). The concept was

recognized in early researches by Mintzberg (1973) as an entrepreneurial aspect of strategy

creating an approach of the organization. However, the concept gained more attention from the

work of Miller and Friesen (1982) who termed the phenomenon as an “entrepreneurial model”.

Originally, the concept of entrepreneurial orientation implies the organizations that continuously

strive to innovate aggressively by taking risks in their product and marketing strategies (Miller &

Friesen, 1982). Later on, the concept was properly operationalized into three essential dimensions

of innovation, risk-taking, and proactiveness (Miller, 1983). Miller’s conceptualization of

entrepreneurial orientation by any organization requires the emphasis on these three sets of

dimensions. However, Miller’s (1983) dimensional based conceptualization of entrepreneurial

orientation pertains to some lacking. The three dimensions of entrepreneurial orientation may need

to covary in order to be the foundational parameter of entrepreneurial orientation. The absence of

covariance among the three sub-constructs may not claim the constituent of an entrepreneurial

orientation as conceptualized by Miller’s work (Covin & Wales, 2012).

Lumpkin and Dess (1996) further addition the two dimensions of autonomy and

competitive aggressiveness in the previous three-dimensional conceptualization of entrepreneurial

orientation. However, the Lumpkin and Dess (1996) illustration of entrepreneurial orientation was

based on the clarification of Miller’s work lacking. It states that the entrepreneurial orientation


48

does not require the complete set of these five dimensions as a whole. Rather it was suggested that

the dimensions do not strongly require to covary strongly or positively with each other in order to

claim the presence of entrepreneurial orientation. This illustration of entrepreneurial orientation

by Lumpkin and Dess (1996) was somewhat of a typical latent construct type that explains the

concept of being entrepreneurial. However, the specific context of these five-dimensional views

as explaining the construct itself was not covered by this research.

However, it has been long believed in the existing literature that taking the risks in gripping

the new business opportunities and proving to be innovative are the essential parameters of the

organization to sustain its survival in competitive market dynamics. It has also been believed that

the individuals who carry the challenging goals and seeks for the challenging tasks (within an

organization) may pursue the characteristics of an entrepreneur (McCllelland, 1961). This is

evident from these earlier conceptualizations of entrepreneurial orientation by different

researchers. Zahra and Neubaum (1998) defined the concept of entrepreneurial orientation as the

collective output of an organization’s radical innovation, risk-taking activities and proactive

approach in strategic activities of the organization that is carried in the sustenance of existing

riskier projects. Covin and Slevin (1989) explained that those organizations can be regarded to

possess the entrepreneurial orientation whose middle and top managers carry the entrepreneurial

traits and entrepreneurial style in decision-making processes. Voss, Voss, and Moorman (2005)

defined the entrepreneurial orientation as an organizational level proposition to engage its

employees in risk-taking, proactive, innovative, competitive aggressiveness and autonomy related

behaviors that trigger the change within the organization as per the external environment. Avlonitis

and Salavou (2007) defined entrepreneurial orientation as an integral phenomenon through which

an organization embarks the proactive and innovative activities to achieve a better competitive

position among its rivals. Cools and Boreck (2008) explained the entrepreneurial orientation as the

strategy of the top management of the organization relating to the innovativeness, proactiveness

and risk-taking initiatives. Pearce, Fritz, and Davis (2010) defined entrepreneurial orientation as

the set of distinctive interrelated behaviors that constitutes the initiatives of proactiveness, risk-

taking, autonomy, competitive aggressiveness and innovativeness. Rauch (2009) defined

entrepreneurial orientation as the strategy creation process that enables the organization in

achieving competitive advantage and sustaining its vision in the longer run through an


49

entrepreneurial manner. In essence, the entrepreneurial orientation elucidates the practices of

entrepreneurship in the strategic stance of the organization in carrying its existing businesses. The

conceptualization of entrepreneurial orientation laid down by Covin and Miles (1999) was found

to be the predominant one. However, Covin and Wales (2012) argued that future researchers can

opt unidimensional or multidimensional construct of entrepreneurial orientation in light of the best

reflection of measures as per their study dynamics. Covin and Wales (2012) conducted a detailed

systematic study on the conceptualization of entrepreneurial orientation in a challenging

perspective. They concluded that the measurement of entrepreneurial orientation should be

grounded from the theoretical perspective of the research. Similarly, Anderson et al., (2015)

studied the construct of an entrepreneurial orientation as the combination of two entrepreneurial

behaviors of management (that are proactiveness and innovativeness) with the manager’s stance

of favoring the risk-taking behavior in strategic decision-making phenomenon. This

conceptualization of entrepreneurial orientation was also in line with the conceptualization by

Covin and Miles (1999) illustration.

Ready to innovate is entitled to be the prime component of entrepreneurial orientation by

the existing literature. It is believed that the absence of ready to innovate consequents to the

negligible extent of entrepreneurial orientation in organizations even rest of all determinants

functions to their peaks (Morris et al., 2011). Lumpkin and Dess (1996) explained the concept of

ready to innovate as the willingness of the organization to carry new ideas and exploit these new

ideas through experimentation in a more creative manner. Ready to innovate is the most researched

and studied determined of entrepreneurial orientation (Parkman et al., 2012). It flourishes at all

levels of the organization including individual, team or group, organizational and inter-

organizational levels (Ireland et al., 2006).

It is argued that ready to innovate is a force between the two foundational functions of

corporate entrepreneurship that are business venturing and the most important strategic renewal

(Yildiz, 2014). Proctor (2014) has defined the ready to innovate as the practical implementation

of the new ideas, concepts, and discoveries into profitable product or services. The phenomenon

of ready to innovate originates with the stage of proposal drafting or formation, further moving to

the development of the basic generated idea and ends with commercially exploiting the developed


50

idea in form of some marketable product or service (Tonnessen, 2005). Freeman and Soete (1997)

defined the ready to innovate as the accomplishment of an organization in successfully conducting

the first transaction of their newly produced product, service offer or any process from the newly

generated idea. Thus, the number of explanations on the conception of ready to innovate are

researched in the literature of entrepreneurial orientation. It was revealed that all these conceptions

carry the same explanation that the ready to innovate is a phenomenon that possesses some

processes from the origination of an idea to outcome in the shape of product or service or systems.

It also revealed that the output of this sub construct ready to innovate involves the launch of end-

product in the market to add value to the organization as well as the customer.

Competitive aggressiveness refers to the organization’s tendency to challenge its rivals

intensively being the new entrant to market or with the improvement in its competitive position

(Lumpkin & Dess, 1996). However, the rigorous act of challenging the rivals necessarily requires

the organization to pursue some unconventional strategies instead of traditional conventional

tactics. This may also require the organization to behave proactive and reactive towards the moves

of their competitors (Stambaugh et al., 2011). Chen et al., (2006) explained that the competitive

aggressive is an ability of an organization to perform more effective and healthier, with more

strong offensive position holder and being the aggressive market entrant dominant by others in

contrast to its rivals. Chen et al., (2006) further explained that the extent of competitive

aggressiveness of an organization may be reflected by the degree of its responsiveness in a manner

that how the organization immediately defends itself if the rivals lower its product or service prices.

However, some of the researches have also argued that the merger and joint business ventures also

prove to be effective in increasing the competitive aggressiveness of organization (Harrison et al.,

1991; King et al., 2004). It may happen due to the synergy effect of the business venture with

higher profit returns.

Besides the competitive aggressiveness, the ability to work independently by taking actions

and decisions with more empowerment and delegation are also essential for the organization to

regulate entrepreneurial orientation. Autonomy refers to the extent of freedom and openness

provided to employees to experiment with the new ideas and creative techniques to promote

entrepreneurship orientation within the organization (Lumpkin & Dess, 1999). It is also generally


51

believed that when the top and middle management authorizes the functional and line managers

with some autonomy, the resultantly the extent of innovation increases within the organization

(Janssen et al., 2015; Ireland et al., 2006). The organizations providing their employees with

sufficient autonomy consequently flourishes the innovative culture within an organization where

the individuals are free to share and experience new ideas and opportunities. The individual and

team efforts to pursue the new market opportunities may lead the organization to be the new

entrant. The new ideas and opportunities based concepts generated or developed by the individuals

or team members are communicated to middle managers for the decision making (Hart, 1992).

Thus, autonomy promotes creativity and innovation within the organization that is also dependent

upon the personal attributes of the individuals (Eder, 2007).

Risk-taking results from the autonomy and self-employment decisions is also an essential

element of entrepreneurial orientation. Organizational risks are the outcome of experimenting the

creative ideas and innovation. Risk-taking refers to the organization performing an act that is

considered suspicious and uncertain to the profitable outcomes with the tentative probability of

failure and loss (Wiklund & Shepherd, 2008). These uncertain actions by the organization may

include the decision to venture into uncertain or new markets, huge lending from markets or

investing in those business ventures whose outcomes are doubtful (Baker & Sinkula, 2009). It can

be argued that risk-taking involves those strategic acts by organizations that require heavy

investment either in terms of human or financial capital but carries a higher propensity of failure

(Eggers & Kaplan 2013). The outcome of risk-taking may be either success (positive) or failure

(negative in nature). Although risk-taking flourishes and enhances the innovation within the

organization, however, it is not necessarily that the outcome of risk-taking always is positive in

nature. It is something that is influenced by the past experiences of the organization in parallel

with the ability to frame the propensity of risk propositions (Lumpkin & Dess, 1996). Calculating

the risk is essential for the organization rather than playing gamble with uncertain outcomes.

Because the organizations that avoid uncertainties with less inclination towards the new

opportunities always stay far behind from the innovation and consequently the strong competitive

positing in markets (Nishimura, 2015).


52

Past extensive literature has been reviewed on the conception and established theories of

management entrepreneurial orientation. This research work has adopted the Wang (2008)

conceptualization of entrepreneurial orientation by operationalizing the construct into essential

sub-constructs of ready to innovate, competitive aggressiveness, risk-taking and proactiveness.

Details on operational definitions and measures of the construct management entrepreneurial

orientation are discussed in consequents section.

2.3. Proposed Association of Study Variables

2.3.1. Association of Innovation Capabilities and Business Model Innovation (Gap-2).

Majority of organizations who are striving in a complex market dynamics are thought to

continuously oblige to address growing industry demands (Teece, 2012). However, the

organization ability to identify, learn, integrate and reconfigure its internal competencies,

capabilities and resource base is essential to cope with this changing nature of external market

dynamics. The resources of an organization that are difficult to reproduce and imitate by the

competitors firm, if used in value generation for the customers ultimately bring the innovation in

the organization (Weking, Lupberger, Hermes, Hein, Böhm, & Krcmar, 2020). This dynamic

capabilities perspective stresses on renewing the existing capabilities of the organization along

with the generation of new organizational capabilities in order to achieve competitive advantage

(Weking et al., 2020).

This determines that the capabilities of an organization are the prerequisite for the efficient

and speedy realignment of existing resources of the organization to meet the needs of the customer

and the market. These innovative capabilities such as sensing and seizing are required to design

and implement the new business models with an objective to meet the growing needs of new

markets (Hock-Doepgen, Clauss, Kraus, & Cheng, 2020). Continuously sensing and seizing the

external opportunities and periodically integrating them into the internal facets of the organization,

may ultimately enable the organization to proactively guard against the new threats as they arise

(Hock et al., 2020). Furthermore, seizing the external opportunities from the growing market also

requires the capabilities of the organization for the generation of sustainable advantage over the

rivals (Teece, 2012). However, the organization can only achieve this objective, if it proves to be


53

keen toward the capabilities that allows them in the realignment of resources towards the service

innovation success (Siebold, 2020). The speed and extent of effectively utilizing the resources in

pursuance of customer needs and wants would yield the extent of success of these capabilities. It

is crucial to discuss here that the innovation capabilities of the organization are multi-facet. It is

essential to discuss that all the organization may not essentially strengthen enough in every factor

of innovation capabilities. Those who are stronger in sensing and coproducing, may not be strong

enough in scaling and stretching capabilities. This may vary among different organizations in

different contexts. There may also be a chance that the organization who are stronger in forming

the new business model, may proves to be flimsy in implementation skills. Consequently, it could

be said that firms carry the stronger innovative capabilities in contrast to its competitors, if it is

more stronger in all elements. These are the organizations that may bring novelty in their existing

business model (Hock et al., 2020). Teece (2018) discussed that business models and dynamic

capabilities are two interdependent concepts of management. Theoretically, the role of capabilities

as the driver of business model innovation can be understood and explained. However, there is a

need to further testify this association through empirical analysis in order to getter better

understandings of the phenomenon. Scheinder and Speith (2014) also argued that there is a need

to explore how an organization identifies its relevant external opportunities in terms of

capabilities? And does these capabilities emphases the business model innovation within the

organization? Some of the recent researches also posed a challenging research question for future

researches that states, what is the role of innovation capabilities of the organization as an internal

driver of business model innovation? That needs to be empirically investigated (Saebi et al., 2017;

Teece, 2008; Speith & Messner, 2019). Thus, the influence of innovation capabilities in

determining business model innovation needs to be explored in light of these researches (Teece,

2018; Scheinder & Speith, 2014; Foss & Saebi, 2018, Speith & Messner, 2019; Saebi et al., 2017).

Based on the discussions above paras and the gap identified from the review of the literature, the

following research hypotheses are developed as,

H1: Innovation capabilities may possess positive influence on business model innovation.


54

Scheinder and Speith (2014), Foss and Saeibi (2018, 2017) and Teece (2018) comprehend

the need to testify the proposed relationship of innovation capabilities and business model

innovation. The empirical testing of this hypothesis contributes to the existing literature body by

closing this research gap.

2.3.2. Relationship of Innovation Capabilities and Service Innovation Success.

The strength of innovation capabilities of the organization basically determines the speed

and extent of synchronizing the organization resources to deliver value to the customers by

fulfilling their unmet needs and wants (Helfat & Martin, 2015). Achieving the success of

innovation is a challenging task for the organizations especially for the service organizations. It is

also self-evident in existing literature body of entrepreneurship and strategic management

disciplines that the outcome of the innovation (innovation success) is a foundational means for the

organization to enhance and sustain its customer base (Kiel et al., 2017). The existing literature

generally believes that the organization who are capable enough to assess and actively responds

the growing market or customer needs, such organizations are more likely to be the first entrant

with the generation of new service or new changes in existing product or services (Arnold et al.,

2016). This indicates that the organization requires some of the capabilities to identify the customer

needs, assessing technological trends, available technological options and conceptualizing the new

product or services in combination with these capabilities and customer or market growing needs.

It represents the magnificent skill of science and analysis by the organization to script the success

story of new innovative service (Teece, 2014; Helfat & Martin, 2015). It basically requires the

innovative capabilities of the organization to fully explore the external opportunities of potential

innovative service and its consequential outcome to the external environment of the organization.

Literature has also evidences that the role of innovation capabilities in predicting the extent

of innovation success is also dependent upon the extent of the new opportunities explored either

through the use of experimentation or research etc. Service success is dependent upon the

information about the recent trends and growing market needs. It may be obvious as previous

mainstream literature agrees with the fact that the organization necessarily requires the

development and re-work on the innovation capabilities to generate more economic as well as

societal value (Zack, McKeen & Singh, 2009; Kogut & Zander, 1992).


55

The organization pursuing the success of new innovative services needs to develop and

sustain its capabilities to cater for its short term survival and long term growth of services (Lee et

al., 2018; He & Wong, 2004). The organizations that manage the information relating external

environment and market needs may be competent enough to develop the new innovative ideas into

the new innovative services through effectively utilizing its resource base and capabilities.

Similarly, the organization fails to manage and promote these aspects of the external environment

may render in week new service outcome. The literature also supports the fact that the success of

the organization operating in dynamic or stable environment involves the identification of

technological available options and growing trends while on the other hand survival in such

environments requires the continuous development of new competencies through effective

utilization of innovation capabilities (Gonzalez et al., 2018). However, the alignment and

coherence of these innovation capabilities are mutually desirable in order to understand the extent

of innovation success consequentially achieve. The existing literature also states that the

innovation capabilities may possess some influence on the performance indicator of innovation

may need to be studied (Teece, 2018; Gonzalez et al., 2018). As it is essential to understand that

to what extent the innovative success enhances by improving the same differentiation of novel and

efficiency centered innovation capabilities. Based on the above discussion, the research hypothesis

2 has been established as;

H2: Innovation capabilities may possess a positive influence on service innovation success.

2.3.3. Relationship of Service Innovation Success and Business Model Innovation.

Existing concept of blue ocean strategy advocates that the high competition shifts the

organization's foci and energies towards the competitor’s moves rather than customer demands.

The competition in the overcrowded market does not guarantee organizations with higher

productivity (Kim Mauborgne, 2004). Exploring the quests with new ways of doing things opens

up the saturated market with the new ocean to quest (Kim Mauborgne, 2004). Thus, innovation

creates a new market space and creating value in business for the customers.

The existing body of literature has defined innovation success as dimensional variable that

refers both the process and consequential aspects (Menor, Tatikonda & Sampson, 2002). The


56

majority portion of service innovation literature has emphasized on the performance of innovation

from competitive lens. However, there also exists limited research studies who have focused the

financial performance as central theme in relation to this newly evolved construct (Gima, 2003;

Froehle, Roth, Chase & Voss, 2000). It highlights that more researches are required to testify the

innovation success from performance parameters. In order to achieve this goal, this work has taken

this construct as determinant of success i.e short term, long term and indirect nature. It is pertinent

to state that the success of new service settles on its path when the new service offerings are aligned

with the customer needs in such a way that company earns an ongoing stream of revenues from it.

However, pioneering a new service is not always a path for continuous financial benefit. Being the

first in service offering resultantly educates the customer about the new value propositions. This

paves the way for the rivals to enter with more substitute features or characteristics of service, with

the potential threat to pioneer organization. In this way, the competitive position, commercial

success, service reputation and level of customer satisfaction towards the pioneer service are

critical for the long term success of the pioneer service offerings.

It has also been found in existing literature that successful service innovation requires the

effective and timely decision making in order to cope the growing market changes of the

competitive world (Mennens, Gils, Schroder & Letterie, 2018). The success of new services loses

its essentiality if the valued knowledge gained through the success of this new service offerings is

not completely retained by the organization for future references (Preez et al., 2006). The

transformation right and relevant information and experience of service innovation success may

serve the organization with the developmental changes in the existing business model of the

organization. This may predict that experience of service innovation success is an essential factor

that may affect the extent of developmental changes in existing business process and business

model.

However, the organization are necessarily require to develop new competences in

pursuance of growing market need in order to ensure its continuous survival. They are needed to

continuously update themselves with new technological advancements in their existing the service

portfolios. This would consequentially reap the organizations with the benefits of more improved

internal processes that would be required for more innovative value creation and proposition.

Similarly, the lasting good reputation of pioneer service and healthy customer satisfaction may


57

further enable the organization to seek new customer segments or markets with more improved

delivery channels. Strengthening customer based on the retention of the existing customers and

building the new ones would resultantly strengthening the innovative revenue models with

additional sales. Based on the above discussion, the research hypothesis three is formed as,

H3: Service innovation success may possess positive influence on business model

innovation.

2.3.4. Service Innovation Success as Mediator (Research gap – 3).

Each and every organization in the real world possess some parameters of innovation

capabilities but it does not imply the fact that all the organizations are continuously innovating. It

implies that innovation capability is a necessary condition for the organization to innovate but not

sufficient enough for innovation. It is essential to state that the development and launch of novel

services require the significant funds along with the danger of overall disappointment. It is

apparent that the failure reflects that all efforts, capabilities and capitals are compensated as

wastage. Therefore, the forthcoming researches are taking the construct innovation success as

central emphases. Brentani and Ragot (1996) have distinguished the service innovation success

factor in terms of internal and external aspects based on the conception of strength, weakness,

opportunities and threats analysis. How well a service has taken into consideration the external

opportunities and threats, overall shapes the customer perception of new service benefits. It

determines why the customer should opt for that specific new service offerings. While the service

value proposition such as the new ways of channel deliveries would be considered as the internal

success factor of the new service. The organization necessarily requires strengthening themselves

in recognizing the unmet market and customer desires. They further necessarily require to adopt

some efficient technologies and then orchest, scale and stretch these new acquired capabilities with

the prevailing organizational processes. Such organizations may evidence to be efficacious in

delivering the customer value. It is vital to proclaim that the extent of the innovation capabilities

align with the existing process of organization may further surface the extent of the success of

innovation of organization in terms of financial parameters, parameters of competitive positioning


58

and the parameter which may sustain the overall success of innovation (Hossain, 2018). An

organization deliberately achieving the success in competitive positioning and sustainability

parameters, may further enhances the ability of an organization to posited new ways of doing

business to deliver and capture value (Helfat & Martin, 2015). Bashir and Verma (2019) explained

that the organization is capable of delivering the customer with the value proposition with the

increased profits to the organization. Such new service offering may be met with the success

overall to the organization, customer and other business partners.

Thus, it would not be wrong to state the service innovation capabilities of sensing,

conceptualizing, orchestrating and stretching may influence the success of the new service offering

with more competitive positioning and sustainability. It may further yields the value creation, value

proposition and value capture to customers as well as the organization with the success of the new

service offering. These arguments are also supported by some of researchers that indicated the

more empirical researches are needed to investigate this phenomenon (Bashir & Verma, 2019;

Hossain, 2018; Teece, 2018). Teece (2018) has suggested that the forthcoming researches should

empirically testify the influence of innovation capabilities on their innovative business models.

The focus is to understand that whether the strong capabilities produces the operative, novel and

efficient business model. Teece (2018) also proposed that the forthcoming researches may also

requires to illustrate the potential influence of some critical significant connections among the

association of innovation capabilities and business model(s) innovation. He also explained that it

is very crucial to examine their intricate connection for the further advancement of knowledge in

the field of this newly evolved construct business model innovation. The researcher has also

suggested that forthcoming researchers may examine the influence of these innovative capabilities

in relation to any performance indicators that could be the innovation success. In light of these

arguments, this work efforts to fill this research gap by developing the research hypotheses four

as,

H4: Service innovation success mediates the relationship between innovation

capabilities and business model innovation.


59

Teece (2018), Scheinder and Speith (2014), and Foss and Saeibi (2018) comprehend

the need to explore the possible association with performance indicators (such as innovation

success in this work). The empirical testing of this hypothesis 4 contributes to the existing

literature body by closing this research gap.

2.3.5. Moderation Effect of Employee Resistance to Change (Research gap-4).

There is a number of organizations that spend heavily on their innovative capabilities but

still unable to achieve innovation success while on the same perspectives there exist some

organizations in the real world that do not invest much but still successful in achieving the

innovation success (Zawislak et al., 2012). This raises the concern to ponder and the answers lie

into the innovation capabilities. The innovation capabilities are the handheld parameters that

enables the organizations to absorb, implement, adapt and transform the new technologies and

practices into laid down operational, transaction and management routines of the organization with

an objective to be profitable in terms of innovation. It might also be possible that the two

organizations who possess the same level of educated, skilled and competent workforce /

organizational members may behave different towards their innovation and organizational goals

(Nisula & Kianto, 2013). The reason for different output is the differences these two organizations

possess in regulating the environment of collaboration and contextual elements that shape the

stance of the employees towards novel things (Miller, 2019). Hence, this discussion concludes to

the point that it is not only the innovation capabilities of the firm that drives the innovation success

but behind there lies the behavior of employees for managing the novel changes (Miller, 2019;

Nisula & Kianto, 2013).

Employee resistance was treated as an essential barrier to the innovation mechanism in

existing literature therefore, it is critical for the organization (to take in consideration) who intends

to carry innovation either in product or service offerings, business process and existing business

models (Rodriguez, Molina-Castillo, & Svensson, 2019). The resistance by employees against any

newness or developmental change in form of innovation may disclose the conflict of interests of

employees and employers (Hauschildt, 1999; Rodriguez et al., 2019). Although, the literature

argues that the employee resistance to change may have a substantial effect on the business success


60

of the organization in the longer run. It may be higher among the organizations in which the pay-

back compensation on the ongoing innovation was not guaranteed by the organization. This

employee resistance to change may have divesting effect not only on the innovation capabilities

of the organization but also on the ongoing innovation mechanism that consequently may lead to

the abolishment of innovation within the organization (Guldmann, & Huulgaard, 2020). The

genesis of innovative service success and the ultimate innovation in existing or new business

models by innovation capabilities of the organization may be interdependent on the extent of

employee resistance to change within the organization (Guldmann, & Huulgaard, 2020). Hao and

Yu (2011) conducted detailed research on the nature of association among the different forms of

innovation capabilities of organization and outcome of innovation that is innovation success. The

researchers found that all the forms of innovation capabilities possess the positive effect on the

innovation success among the Chinese organizations and further call for future research to explore

the role of some moderating elements that effect the association of innovation capabilities and

service success.

Generally, it can be argued that the phenomenon of business model innovation carries both

forms of employees i.e. winners and losers. The organizational members who losses during the

ongoing mechanism of bringing newness or change in business model may be expected to

disproportionately behave more negatively towards the ongoing business model innovation. In

comparison to those, who gain during this ongoing phenomenon may expect to behave more

positive towards business model innovation. Summarizing, the researcher was of the opinion that

business model innovation may regulate some extent of employee resistance to change (Muller,

2019). This debate is further supported by Foss and Saebi (2018) and that needs to be explored by

future researches. This posed research question by Foss and Saebi (2018) states that there is a need

to explore the role of entrepreneurial orientation (or vision) on the business model innovation. In

light of these theoretical discussion and an efforts to address these research gaps articulated by

researchers Hao and Yu (2011) Muller (2019) Foss and Saebi (2018, 2017), the hypothesis 5 and

6 are developed as,


61

H5: Employee resistance to change moderates the direct relationship of innovation

capabilities and business model innovation, in such a way that the relationship is

stronger with lower employee resistance.

H6: Employee resistance to change negatively moderates the relationship between

innovation capabilities and service innovation success in such a way that the

relationship is stronger with lower employee resistance.

Thus, the empirical testing of these hypotheses 5 and 6 contributes to the existing

literature body by closing these research gaps comprehend by Muller (2019) Hao and Yu

(2011) Foss and Saebi (2018, 2017).

2.3.6. Moderation Effect of Management Entrepreneurial Orientation (Gap – 5).

Generally, it is argued that the heart of entrepreneurship can be termed as innovation but it

is not necessary that all the innovation is the not the outcome of higher entrepreneurial orientation

only (Groskovs & Ulhoi, 2019). Organizations continuously experience some routine forms of

innovation in response to its rivals or customer growing needs that guarantee its survival in

competitive market dynamics. However, the innovation within the organization that is inspired by

the entrepreneurial orientation may be more distinguishable than this routine innovation of

adaptation and responses to market new trends (Baker & Sinkula, 2009). Actually, this mechanism

of identifying external opportunities is the precursor one that brings innovation success with the

ultimate objective of bringing new service offerings to market or customer. This phenomenon

requires the entrepreneurial orientation by the management of the organization at the heart of

which this new innovation would rest (Al‐Jinini, Dahiyat, & Bontis, 2019).

Thus, the organization that possesses a strong entrepreneurial orientation by the

management may likely to develop successful innovative service offerings as per the customer or

market needs. Similarly, such organization learns from the service’s success and may efficiently

brings newness in the existing business model either by replacing the older business model with

the newer one or may bring some new developmental changes in existing business model

(Groskovs & Ulhoi, 2019). The genesis of these forms of innovation depends on the

entrepreneurial insight and orientation by the management, not through traditional customer


62

research. Vaznyte and Andries (2019) argued that the entrepreneurial orientation serves as a

instrument for the organization to decide whether the new business model can be pursue or not.

Some of the other researchers also supported the argument that the entrepreneurial orientation may

affect the organization that whether the new business model or corporate start-up fits with the

dynamic external environment irrespective of the enhanced capabilities to innovate (Lafuente,

Vaillant, and Leiva, 2018; Vaznyte & Andries, 2019) . Thus, there is a need to empirically

investigate the understanding of the phenomenon that how the entrepreneurial orientation predicts

the success of innovation success as well as the degree to which an organization capture, deliver

or propose value (Vaznyte & Andries, 2019). Foss and Saebi (2018, 2017) conducted a detailed

systematic literature survey on the business model innovation and argued that there is a need to

explore the moderation effect of certain factors (such as the management entrepreneurial

orientation) on the association of antecedents and business model innovation itself. Foss and Saebi

(2018) further elaborated this research direction and posed a challenging research question that

states that the role of entrepreneurial orientation (or vision) needs to be explored on the business

model innovation. Hao and Yu (2011) also argued that the different forms of innovation

capabilities possess a direct effect on the service innovation success. However, the future

researches are recommended to explore this association of innovation capabilities and service

innovation success with some potential moderating factors with an objective to bring more clear

insight of this association (Hao and Yu, 2011). In light of these theoretical discussion and an effort

to address these research gaps articulated by researchers Vaznyte and Andries (2019) Hao and Yu

(2011) Foss and Saebi (2018, 2017), the hypothesis 7 and 8 are developed as,

H7: Management entrepreneurial orientation moderates the direct relationship of

innovation capabilities and business model innovation, in such a way that the

relationship is stronger with increased entrepreneurial orientation.

H8: Management entrepreneurial orientation positively moderates the relationship

between innovation capabilities and service innovation success in such a way that

the relationship is stronger with increased entrepreneurial orientation.


63

Thus, the empirical testing of this hypotheses 7 and 8 contributes to the existing literature

body by closing this research gap articulated by researchers Vaznyte and Andries (2019) Hao and

Yu (2011) Foss and Saebi (2018, 2017).

2.4. Antecedent of BMI Needs to be Explored (Research Gap-6)

The evolution of this new construct ‘business model innovation’ is only decade earlier. It

is not wrong to state that the increased globalization, growing technological advancements and

tough competitive market dynamics have led today’s businesses to fall in prey of continuous

innovation. This consequently has led to the emergence of the concept of ‘business model

innovation’. However, it is also pertinent to mention that the business models of the organizations

tend to be stable and static in natural characteristic especially when an organization is enjoying a

success with efficient and effective practiced activities and strategies that further serves as a path

to imitate for rivals (Teece, 2018, 2010; Doz & Kosonen, 2010).

The review of existing literature body reveals that the detailed researches have been

conducted on the barrier of business model innovation by some of the researches (Amit & Zott,

2001; Chesbrough & Rosenbloom, 2002; Christensen & Raynor, 2003). However, the consequent

researches have summarized and organized these barriers of business model innovation in two

broad classifications of obstruction and confusion (Chesbrough, 2010). Furthermore, the literature

also recommended the strategies of experimentation, leadership style and change leadership to

overcome the effects of these barriers on the business model innovation (Chesbrough, 2010). The

literature also indicated that managerial cognition also plays an essential role in the transformation

of business model innovation (Aspara et al., 2012). However, it was a single case study and

directed for future researches to testify the effect of management cognitive orientation in

determining the business model innovation at a larger scale. Some of the other researches were

also found to explore the role of individuals (employees) in the creation of new ideas and the

development of business model innovation (Bjork, 2012; Eppler et al., 2011). However, the

majority of these previous research studies provided more concrete concepts but followed the

qualitative research methodology. Below mentioned table 2.2 explains this progress of researches

on the antecedents of business model innovation. It also explains the way forward for future

researches in quest of search for antecedents of business model innovation phenomenon.


64

Table 2.2.

Survey evidence pertaining to the antecedents of business model innovation

Authors Focus and Contribution Methodology

Adopted

Findings and Future

Research Directions

Trapp, Voigt

& Brem

(2018)

Develop and test the business

model innovation identification

instrument for the new

researches and practitioners

A qualitative

approach with

interview

method

The characteristics of BMI were

investigated an an attempt to address the

research gap. The future research can

evaluate these business model innovation

parameters from survey method. Future

research is also called to investigate the

international business models and their

configurational changes in details.

Loon & Chik

(2018)

Investigates the role of

technology and innovation in

bring novelty in business

models of SMEs.

A qualitative

study with

case study

approach

Technology, innovation and customer

relations plays an influential role on

business model innovation. Future research

may adopt a quantitative approach for

investigating business model innovation

phenomenon.

Speith &

Meissner

(2018)

Investigates the business model

innovation of a company in

terms of developmental

alliances and innovation success

A qualitative

approach

with case

study

approach

Future study may broaden the results of a

study by testifying the parameters in

different organizations. Longitudinal

studies are also recommended.

Valter,

Lindgren &

Prasad (2018)

Explains the role of seven forces

on the business model

innovation process in

engineering lab set-up

Case study

approach

Empirical studies are recommended that

may investigate the individual, group and

emotion forces on the business model

innovation.

Foss & Saebi

(2018)

Discussed in detailed the future

avenues of research in three

streams of BMI i.e. dimensions,

the effect of BMI and

antecedent of BMI.

Literature

Review


explore the role of BMI as independent,

moderating or mediating and dependent

variable. Few challenging research

questions are posed by the researcher for

future researches.

Adrodegari,

Pashou &

Saccani

(2017)

Discusses the methodology for

the selection and design of a

new business model for revenue

generation

Case Study of

ULMA

company

--

Teece (2018)



connection with dynamic

capabilities.

Conceptual

paper

Future research is recommended to testify

the association of capabilities and business

model innovation.

Geissdoerfer,

Vladimirova,

Van Fossen &

Evans (2018)



connection with service

innovation.

Conceptual

Paper

Future researches are recommended to take

into account the differentiation among

business model innovation, service

innovation and product innovation. The


65

validation of constructs of BMI are also

recommended

Hacklin,

Bjorkdahl &

Wallin (2018)

Explains the role of value

migration on business model

innovation

A qualitative

study based

on interviews

Empirical testing and collection of field

data are recommended.

Foss and

Saeibi (2017)

Discussed the fifteen years of a

literature review on BMI

Literature

Review

Future researches need to explore the

antecedent, element and effects of BMI.

Some challenging research questions are

also recommended for future researches.

Cortimiglia,

Ghezzi &

Frank (2015)

Discussed that the organization

engages in strategic making

process while achieving

business model innovation. It

also aimed to check the

relationship of SMP on

business model innovation

Mix method

approach

Future researches need to investigate the

different value propositions shaping the

business model innovation in an empirical

setting.

Maglio and

Spohrer

(2014)

Investigated the service science

perspective on one type of

business model innovation

Conceptual

Paper

Four principles of service sciences are

proposed that stress on the basic

relationship of service on the business value

propositions.

Scheinder

and Speith

(2014)

Discussed in detailed the

existing researches and new

research directions on the field

of business model innovation.

Literature

Review

Future researches are needed to explore the

elements and antecedents of business model

innovation.

It is crucial to state that these researches are conducted in-depth in investigating the

business model innovation as an outcome. However, these researches have not taken in parallel

the phenomenon of business model innovation (operationalization) itself (Foss & Saeibi, 2018).

Rather, the mere focus of the majority of these previous researches was on explaining a particular

type of change of business model (Foss & Saeibi, 2018). In addition, the majority of these

researches have used the qualitative research methodology and the empirical testing of the

dimensions and phenomenon was also found to be limited. The explanation of the factors that led

to the change in business model was also found to be limited in previous researches (Foss & Saebi,

2018). This research work also attempted to address these challenges of literature as well.


66

The new researches on business model innovation pose certain significant queries for

forthcoming studies. Teece (2018) indicated that the aspects of capabilities (i.e. identifying market

opportunities and adoption in current practice) may revitalize the aspects of business model

innovation. Therefore, these associations and their influential role for performance (i.e. may be a

success) need to further explored in future researches (Teece, 2018). Thus, the recent researches

on business model innovation indicate some key questions (theoretical as well as empirically

analyzed) that need to be explored in order to contribute in the existing body of knowledge (Foss

& Saeibi, 2018, 2017; Scheinder & Speith, 2014).

• What is the role of capabilities as a driver of business model innovation? (Teece, 2018; Foss

& Saebi, 2018, 2017; Scheinder & Speith, 2014) (Gap-2 of this work)

• What are the elements and dimensions of business model innovation? (Hossain, 2018;

Bashir & Verma, 2019; Geissdoerfer et al., 2018; Scheinder & Speith, 2014; Foss & Seibi,

2018, 2017). (Gap-1 of this work)

• And what are the drivers, and factors that shape the business model innovation? (Scheinder

& Speith, 2014; Saebi et al., 2017; Foss & Saeibi, 2018, 2017; Hossain, 2018; Bashir &

Verma, 2019; Geissdoerfer et al., 2018; Speith & Meissner, 2018). Foss and Saeibi (2018)

further clarified the path by posing the challenging research questions that there is need to

explore the role of employee resistance and management orientation or cognition on

business model innovation (Gap – 3, Gap – 4, Gap – 5 and Gap – 6 of this work).

These are certain crucial queries that are not yet answered in present literature body (Foss

& Saebi, 2018, 2017). Foss & Saebi (2018, 2017) also highlighted that up till now no researches

have been found that deals with the antecedents of the business model innovation and thus it also

serves as a gap in literature body. These are some of the identified research gaps that are attempted

to address in this research work. Based on the above discussion on possible antecedent of business

model innovation and the research gaps identified by the researchers Schneider and Spieth (2014),

Foss and Saeibi (2018, 2017); Saebi et al., (2017), Hossain (2018), Bashir and Verma (2019),

Geissdoerfer et al., (2018), Speith and Meissner (2018), and Teece (2018), following research

hypotheses H9 and H10 are developed to address these research gaps,


67

H9: Employee resistance and management entrepreneurial orientation moderates

the direct relationship of innovation capabilities and business model innovation

when the putative mediator service innovation success held constant.

H10: Service innovation capabilities possess the positive indirect effect on the

business model innovation (through positive mediation effect of service innovation

success), that is further negatively moderated by employee resistance to change and

positively moderated by the management entrepreneurial orientation.


This chapter has discussed in detail the existing theories, conceptual models and different

standpoints of existing literature relating the research constructs of this research work. On the

basis of this extensive review of the literature, six crucial research gaps were identified. In order

to address these research gaps, ten testable research hypotheses have been developed. Chapter

three discusses in detail the theoretical stance of these posited relationship and proposed

theoretical framework.


68

CHAPTER 3

RESEARCH METHODOLOGY

This chapter explains in detail the philosophical underpinnings including ontological,

epistemological and axiological stance of this research study. Based on these theoretical

underpinnings, the study variables, the theoretical model of this research and the nature of the

relationship among the variables are discussed in detail. Then, it discusses the methodology

followed in the completion of this research work. It includes the brief illustration of the research

design, population and sample frames, sampling strategy adopted, the process of drawing the

sample size, development of research instrument and brief information about the analytical

techniques

3.1. Research Paradigm and Philosophy

The research paradigm comprises of six essential layers of research onion that are

philosophy, approach, strategy, choices, time horizons and data collection techniques (Saunder et

al., 2009). The research philosophy basically identifies the deep-rooted beliefs and assumptions of

the research study (Saunder et al., 2009). The research philosophy including the ontological

assumption and epistemological assumptions of this study are elaborated as,

3.1.1. Ontological Stance of Study

Ontology basically refers to the “reality of being”. It refers to the study of reality and how

things exists (Saunder et al., 2009). The ontological assumption of this study is based on strategic

entrepreneurship perspective that pays attention towards the entrepreneurial stance of the

organization in exploring new innovative opportunities and simultaneously considers the

challenges in forms of employee resistance towards the innovative ideas, practices, and activities

(Holcomb et al., 2009; Ireland & Webb, 2007). Therefore, it is very essential and important to

researches on the concept of business model innovation in which the organization pursues of the

developmental changes of existing business model or adoption of new distinguished business

models for the delivery of value to customer and markets (Amit & Zott, 2010; Foss & Saebi, 2018).

Porter (2001) illustration of business model conception as “invitation for faulty thinking and self-

delusion” evolved this concept in different theoretical frameworks in relations with different fields

of management. However, there still lacks a well-articulated theoretical contribution in the realm


69

of business model innovation (Teece, 2018; Foss & Saebi, 2018, 2017; Bashir & Verma, 2019;

Hossain, 2018; Scheinder & Speith, 2014).

3.1.2. Epistemological Stance of Study

Epistemology basically concerns with the scope of knowledge (Saunder et al., 2009). It basically

refers to nature of reality that how to know what is known. The epistemological stance of this study

basically attempts to overview the realm of business model innovation falling in strategic

entrepreneurship perspective through the lens of force field of change theory (Lewin, 1951). The

concept of business model innovation itself originates from the amalgam of resource-based

perspective and strategic entrepreneurship perspective (Ireland et al., 2003). The resource-based

theory emphases on the rare, imitable, unique and non-substitutable attributes of an organization’s

resources (Barney, 1991; Teece, 1984). The potential of business models of the organization to

assemble, organize and coordinate the organizational resources (Morris, Schindehutte & Allen,

2005) further indicates the need to consider the capabilities in combination with resources to

deliver rare, imitable and non-substitutable value to customers and markets (Teece, 2010; 2018).

The dynamic capabilities perspective prolongs the resource-based theory by indicating the need

for the organizations to be innovatively capable of adopting and implementing the new value

creating, capturing and proposition strategies (Grant, 1996; Pisanno, 1994; Schreyogg & Eberl,

2007). Enhanced and developed capabilities of the organization are considered to sense the

customer or market needs, available technological options and provide the potential opportunities

to the organization (Teece, 2010; 2018) that are further conceptualized into new innovative ideas

to orchest and stretch in existing business processes of the organization. This determines the

service innovation capabilities of an organization (Janssen et al., 2015; Teece, 2018). Enhancing

these capabilities are necessary to achieve overall innovation success and innovation in the overall

business model of the organization (Hao & Yu, 2011; Teece, 2018). Force Field Theory of Change

by Lewin (1951) explains that there are two forms of forces that affect the process of bringing some

change in the organization (either the organization is striving for some form of innovation or

attempts to revolutionize the organizational culture). These influencing forces (or factors) need to

be managed in order to ensure the successful outcome (Lewin, 1951). The forces that are driving

the change needs to be stronger in relation to the forces that attempt to restrain the change process.

This would establish positive results towards the desired outcome. However, if there exists the


70

equilibrium between the driving forces and restraining forces then no change will happen in

desired outcomes (Lewin, 1951). This force field theory of change by Lewin (1951) provides the

best prototype for the moderation effects of two study variables management entrepreneurial

orientation and employee resistance to change on the complete accomplishment of business model

innovation. The managers of the organization strive to bring the positive change or innovation in

the overall business model of the organization through promoting and practicing the behaviour or

activities alike risk-taking, readiness to innovate, aggressively competitiveness and market

proactiveness. This is also supported by upper echelons theory (Hambrick & Mason, 1984) which

states that the senior executives and their teams are responsible for bringing and sustaining the

innovation, strategic formations and enactment. These individuals and group of individuals do so

by their experiences, personal attributes and values (Hambrick & Mason, 1984). In parallel to this

driving force of management entrepreneurial orientation, the mechanism of enhancing business

model innovation within the organization also experiences the restraining effects of employee

resistance to change. This employee resistance to change may constitute the single or

combinational behavior of routine seeking, short term thinking, cognitive rigidity and emotional

reaction from the employees. Thus, the moderation effect of management entrepreneurial

orientation (as the driving force of bringing innovation mechanism) and the employee resistance

to change (as the restraining force of bringing innovation mechanism) may exist on the service

innovation capabilities, service innovation success and business model innovation. This represents

the epistemological stance of this study that also lays the foundations of the theoretical framework

of this research work that is established on the prototypes of these philosophical underpinnings of

strategic entrepreneurship theory and force field theory of change.

3.1.3. Axiological Stance of Study

Axiology basically refers that how the investigator would investigates the beliefs. It basically

involves the standards, procedures and practices put to be in action in search of the raised beliefs

(Saunder et al., 2009). The above stated epistemological stance further paves the way for the

formulation of theoretical framework of this study. As stated above, the two foundational theories

namely strategic entrepreneurship theory and force field theory of change provide a more useful

and suitable prototype for the formation of theoretical framework of this study. It is also essential

to state that, the extensive critical review of the literature has revealed the six major research gaps


71

that are explained and articulated in this research work. Based on the ontological and

epistemological stance of study and an attempt to address these identified six research gaps

(detailed in chapter two), this research work limits the scope of tentative theoretical framework of

this research work to two broad theoretical perspectives that are theory of strategic

entrepreneurship (Hitt, et al., 2001; Ireland, et al., 2003; Hitt, et al., 2011) and force field theory

of change (Lewin, 1951).

3.1.4. Hypothesized Theoretical Framework

Based on these ontological, epistemological and axiological assumptions, this research

work carries the positivist research philosophy under which generalizable body of knowledge may

be generated with emphasis on quantifiable results. In this connection, the research survey strategy

has been used with a deductive approach. The deductive approach starts with the formation of

research question or hypothesis and tries to find the answer to posed research question through

collection and analysis of data (Saunder et al., 2009).

An effort to fill these keen research gaps and formation of proposed hypotheses further

surfaced the avenues towards the establishment of proposed theoretical model of this study. The

hypothesized theoretical framework clearly illustrates how the research constructs are affecting

and interacting with each other. The research construct “service innovation capabilities” plays its

role as an independent variable that possesses the two types of effects on the dependent variable

“business model innovation”. The first type of causal effect of service innovation capabilities on

business model innovation is hypothesized to be a direct effect that is also reflected in hypothesis

1. The other type of causal effect (indirect) of service innovation capabilities on business model

innovation is hypothesized to be an indirect effect that is covered with the series of hypotheses

from 2 to 9. This indirect effect of independent on the dependent variable is influenced by one

form of the mediator (service innovation success) and two proposed moderators (i.e employee

resistance, and management entrepreneurial orientation).

It is essential to clarify here that this indirect effect may exist due to some an

epiphenomenon association between the mediator or moderator in simple mediation or moderation

between the independent and dependent variables (Hayes, 2017). These mediator or moderators

may have the transmitting effect on the relationship of the independent and dependent variables

thus, converting their direct effect into indirect effect (Hayes, 2017).


72

The hypothesized conceptual framework of the study illustrates that the indirect effect of

innovation capabilities (independent variable) on business model innovation (dependent variable

is comprised of three forms of paths and influencing factors. Stage one: at first level, this indirect

effect is mediated by service innovation success and it is hypothesized that this mediation effect

may be of positive nature (i.e. increase in the extent of service innovation success would result

into more strengthen the effect of innovation capabilities on business model innovation (i.e.

hypothesis 4). In addition to this hypothesis 4, the three foundational support hypotheses namely

1, 2 and 3 are also developed. Stage two: in addition to this mediating influence, the influence of

the moderation effect of employee resistance (moderator 1) may exist that is further classified into

two paths. The first path of moderation effect of employee resistance (moderator 1) may exist on

the indirect relationship of innovation capabilities and service innovation success that will be

checked through hypothesis 5. The other second path of moderation effect of employee resistance

(moderator 1) may exist on the direct effect of innovation capabilities and business model

innovation that will be testified through hypothesis 6. It is also hypothesized that this moderation

effect may be negative in nature that means the higher employee resistance may yield the

weakening effect on these two paths i.e. direct and indirect relationships. Stage three: in sum of

these two previous effect of mediation (service innovation success) and moderation (employee

resistance), it is hypothesized that another moderating variable “management entrepreneurial

orientation” (moderator - 2) may also exist parallel that also influences the direct effect of service

innovation capabilities and business model innovation and the effect of service innovation

capabilities and service innovation success. It is also hypothesized that this moderation effect may

be positive in nature that means the higher management entrepreneurial orientation may yield the

strengthening effect on these two paths i.e. direct and indirect relationships. This will be further

testified by the development of hypothesis 7 and 8 as also depicted in the figure 3.1.

Concluding, this discussion reveals that the influencing magnitude and direction of one

mediator and two modertors would termed this hypothesized model as conditional in nature.

Hypothesis 9 will check the conditionality of the two moderators on the direct effect of service


73

innovation capabilities on the business model innovation with the putative mediation effect of

service innovation success considered to be held constant. Hypothesis ten is also formed in order

to empirically testify the validity of this proposed research framework.

Figure 3.1. Hypothesized Conceptual Framework of Research Study

Thus, the recent researches of Foss and Saebi (2018, 2017), Bashir and Verma (2019),

Hossain (2018), Geissdoerfer and colleagues (2018), Speith and Meissner (2018), Teece (2018),

and Schneider and Spieth (2014) envisions the need to investigate the concept of business model

innovation as the dependent variable and further explore the factors precursor to business model

Employee Resistance to Change

• Routine seeking

• Emotional reaction

• Short term thinking

• Cognitive rigidity

Service Innovation Success

• Short term success

• Long term success

• Indirect success

Innovation Capabilities

• Sensing user needs

• Sensing technological options

• Conceptualization

• Coproducing and orchestrating

• Scaling and stretching

H5

H3

Business model innovation

• Value creation innovation

• Value proposition innovation

• Value capture innovation

H6

H2

H1

H7 H8

Management entrepreneurial orientation


74

innovation. The empirical testing of all the research hypotheses of this work contributes to the

existing literature body by closing the mentioned research gaps. The summarization of research

gaps and mechanism adopted to address these research gaps are already illustrated in table 1.1 in

chapter one of this research work. The formation of mentioned ten hypotheses with an objective

to address these identified six research gaps consequently led to the development of this proposed

research model. The tentative hypothesized research model of this work will be tested through

empirical analysis of hypothesis 10.

3.2. Research Design

The research design refers to the research plan of how the posed research questions may

be answered (Saunder et al., 2009). The research strategy of this research work is research survey

as it is considered to be one of an efficient tool for data collection by researchers with more

accurate results with minimal biases (Saunder et al., 2009). As the population framework is

geographically spread nationwide, the self – administer research survey are provided to HR

departments for the complete response by the picked participant. The research work has opted for

mono-method choice (single data collection technique i.e. survey) with quantitative methods as

this work falls in positivist research philosophy. The collection of data may be attempted on a

single point of time. The population constitutes the four cellular companies of Pakistan. The unit

of analysis are chiefs, departmental heads and middle managers discussed in detail in section 3.4.

3.3. Operationalization of Research Instrument and Measurement

This research work has used the existing research instrument of previous past researches

in order to measure the research constructs. Most of the items/scales from previous researches are

adopted with no changes and amendments.

3.3.1. Service innovation capabilities.

The first research construct service innovation capabilities are operationalized with the five

second-order sub-constructs that are sensing user needs, sensing technological options,

conceptualizing, co-producing and orchestrating, and finally the scaling and stretching (Den

Hertog, Van der Aa, & De Jong, 2010. These five dimensions of service innovation capabilities


75

were measured with the adopted 15-items scale developed by Den Hertog et al., (2010). The

original items of this previous study were measured on a 7-point Likert scale with (1) strongly

disagree to (7) strongly agree. This research work has adopted these original items for the

measurement of service innovation capabilities as it is, with no change or amendment. The

operational definitions of these five indicators are stated as follows,

i. Sensing user needs: Sensing user need refers to the capability of the

organization to sense or understand the existing and potential needs of the

customers in advance through interactions with different segments of customers

and markets (Den Hertog et al., 2010).

ii. Sensing technological options: Sensing technological options refers to the

capability of the organization to sense or adapt the new technologies and

potential new services through interactions with competitors, technology

providers and clients, etc. (Den Hertog et al., 2010). This indicator is more linked

with the business development aspect of the organization (Den Hertog et al.,

2010).

iii. Conceptualizing: Conceptualization refers to the capability of the organization

to smartly rework on the new idea or new sensed technological options by

combining the new and existing service elements into something new service

offering to market (Den Hertog et al., 2010).

iv. Coproducing and Orchestrating: Coproducing and orchestrating refer to the

capability of the organization to co-design and co-produce the new service

offerings with the suppliers, customers and other accompanying alliances (Den

Hertog et al., 2010).

v. Scaling and stretching: Scaling basically refers to the capability of the

organization to diffuse the elements or concept of new service offering across


76

the different functioning of the organization (Den Hertog et al., 2010). On the

other hand, stretching refers to the capability of the organization to promote this

new service offering with effective branding strategies in a way that seems

valuable for potential customers (Den Hertog et al., 2010).

3.3.2. Service innovation success.

The second research construct service innovation success is operationalized with the three

second-order sub-constructs that are short term success, long term success, and indirect success

(Riel et al., 2004). Eighteen item scale has been adopted from the work of Riel, Lemmink, and

Ouwersloot (2004) for the measurement of these three sub-construct research variable. The

original items were measured on 7-point Likert scale with (1) strongly disagree to (7) strongly

agree. Similarly, this work has adopted these eighteen items as they were developed, with no

change or amendment. The operational definitions of these three indicators are stated as follows,

i. Short term success: The short term success refers to those elements of new

service that represent the salient aspects of innovation success such as

contribution to financial success, add substantial value to other services or

product and overall success. (Riel et al., 2004).

ii. Long term success: The long term success refers to those elements of new

service that are linked with the sustained competitive advantage of the

organization such as commercial success, competitive position, brand equity and

reputation, expansion in new markets and customer satisfaction. (Riel et al.,

2004).

iii. Indirect success: The indirect success refers to those elements of new service

that serves as a precondition for the future success of the organization such as

in-house technological knowledge of the organization, employee satisfaction, the

creation of new innovation opportunities (Riel et al., 2004).


77

3.3.3. Business model innovation.

The construct business model innovation is constituent of three second-order sub-

constructs namely value creation innovation, value proposition innovation, and value capture

innovation. The value creation innovation was operationalized further into four third-order

subcontracts namely new capabilities, new technology or equipment, new partnerships and new

processes (Clauss, 2017). The second dimension of business model innovation “value proposition”

was further operationalized into four sub-constructs of namely new offerings, new customers and

markets, new channels and new customer relationships (Clauss, 2017). These four sub-constructs

are measured with twelve items. The third dimension of business model innovation “value capture”

was further operationalized into two sub-constructs of new revenue models and new cost

structures. These two sub-constructs are measured with eight adopted items. In sum, the concept

of business model innovation has been measured with the total thirty-three items scale adopted

from the previous work of Clauss (2017) with no change or amendment. The original scale is

measured on a five-point Likert scale mainly (1) strongly disagree to (5) strongly agree. The

operational definitions of these sub-constructs are stated as,

i Value creation innovation: Value creation innovation refers to the acquisition

of new capabilities, new technology or equipment, new business partnerships

and improvement of existing routines through the acquisition of new processes

with an objective to bring positive substantial changes in business model (Clauss,

2017).

ii Value proposition innovation: Value proposition innovation refers to the new

offerings introduce by the organization to meet growing needs of existing and

new customers or new market segments with the new delivery channels

purposely to build strong customer relations so that the substantial positive

change can be brought in business model (Clauss, 2017).

iii Value capture innovation: Value capture innovation refers to the development

of new revenue models and new cost structures to utilize the potential


78

opportunities with an objective to bring positive substantial changes in business

model (Clauss, 2017).

3.3.4. Management entrepreneurial orientation.

The research constructs “management entrepreneurial orientation” is operationalize into

four sub-constructs of ready to innovate, aggressively competitiveness, market proactiveness and

risk-taking (Wang, 2008). These four sub-constructs are measured with the adopted eleven items

scale adopted from the previous research work of Wang (2008). The original items are adopted as

they were developed with no change or modifications. The original items were measured on a

seven-point Likert scale mainly (1) strongly disagree to (7) strongly agree. The operational

definitions of these sub-constructs are stated as,

i. Ready to innovate: Ready to innovate refers to the extent to which the management of the

organization encourages new ways of performing things, seek unusual and novel

opportunities or solutions and facilitates its employees to behave and think in a novel

manner (Wang, 2008).

ii. Aggressively Competitiveness: Aggressively competitiveness refers to the extent to which

the organization initiates leading foremost action in comparison to rivals with an objective

to adopt competitive positioning to overtake rivals (Wang, 2008).

iii. Market Proactiveness: Market proactiveness refers to the extent to which the organization

facilitates the research and development, technological leadership and continuously

markets new lines of product with more improvements (Wang, 2008).

iv. Risk-taking: Risk-taking refers to the extent to which the organization embraces the

uncertain projects with higher profit returns with the belief that some uncertain acts are

necessary to attain the organizational objectives (Wang, 2008).

3.3.5. Employee resistance to change.


79

The fifth research construct employee resistance to change is operationalized with the four

dimensions that are routine seeking, emotional reaction, short term thinking, and cognitive rigidity.

Fifteen item scale has been adopted from the work of Oreg (2003) for the measurement of these

four sub-construct research variable. The original items were measured on 6-point Likert scale

with (1) strongly disagree to (6) strongly agree. Similarly, this work has adopted these fifteen items

as they were developed, with no change or amendment. Employee resistance to change is

operationally defined as dispositional resistance that means all the individuals are disposed to resist

the change but the extent of resistance varies among all (Oreg, 2003). Some individuals are much

more disposed to resist the newness or change in comparison to others (Oreg, 2003). The

operational definitions of the four sub-constructs that are routine seeking, emotional reaction, short

term thinking and cognitive rigidity are stated as,

i. Routine seeking: Routine seeking refer to the desire of individuals to stabilize

the existing daily routines of work or life with the obvious reluctance towards

the adoption of novel acts (Oreg, 2003).

ii. Emotional Reaction: Emotional reaction refers to the feelings of psychological

resilience and hesitancy to lose control experienced by the individual when any

novelty or change is brought (Oreg, 2003).

iii. Short term thinking: Short term thinking refers to the intolerance for the

adjustments and weak stimulation for experiencing something different or new

when any novel act or changes are brought within the organization (Oreg, 2003).

iv. Cognitive Rigidity: Cognitive rigidity refers to the attribute of close-mindedness

of individuals that are less willing to adjust themselves in new contexts and

situations (Oreg, 2003).

3.3.6. Finalization of research instrument.


80

The consolidated version of the instrument of this research work consists of six parts (with

a total of 92 items). The first section (A) of the questionnaire consists of the fifteen items measuring

the conception of service innovation capabilities ranging from items 01 – 15. The second section

(B) consists of the thirteen items measuring the conception of service innovation success ranging

from the items 16 – 28. The third section of the survey questionnaire (C) constitutes the eleven

items of construct of management entrepreneurial orientation ranging from 29 – 39. The fourth

section of the questionnaires (D) contains the fifteen items measuring the concept of employee

resistance to change ranging from 40 – 54. The fifth section of the survey (E) comprises of thirty-

three items measuring the concept of business model innovation ranging from 55 – 87. The last

part of the survey questionnaire (F) contains the three items measuring the demographic attributes

of the respondents namely gender, age and education.

It is pertinent to mention that the research instrument of this research study comprises of

different measurement scales of 5-point, 6-point, and 7-point Likert scale. Hair, Black, Babin, and

Anderson (2009) explained that measurement error can be caused by imposing the one type of

Likert scale (i.e. 7-point) by the researcher for measurement of the construct. However, the

respondent can accurately respond to the other type of Likert scale (i.e. 3-scale) for that particular

construct (Hair et al., 2009). It is also advisable by some researchers that the previously existing

scales may be adopted (with no change) or adapted with minor changes i.e. grammar (Saunder,

2009; Sekaran, 2010; Hair et al., 2009). So that the credibility of scale validity may not be

compromised (Saunder, 2009).

Dawes (2008) conducted detailed experimental research to check the impact of different

Likert scales (i.e. 5-point, 6-point, 7-point, and 10-point etc.) on the data characteristics. He

concluded that all of these different Likert scales are desirable for obtaining the data for regression

analysis. He also explained that the values of kurtosis and skewness for these different Likert scales

are approximately similar and these different Likert scales were found to all comparable in

different statistical techniques of regression analysis, confirmatory factor analysis and structural

equation modeling (Dawes, 2008).

3.4. Population and Sample of study

The population of this research work consists of cellular companies in Pakistan. It is

pertinent to mention that cellular companies of Pakistan presently carry different forms of


81

additional business model (i.e. payment mechanism in collaboration with financial institutes such

as branchless banking etc.) in parallel with the parental business model of providing sim based

cellular services to citizens. Currently, these four cellular companies are engaged in branchless

banking business models that includes (i) Easypaisa (operated by Telenor and Tameer

microfinance bank), (ii) Mobicash (operated by Mobilink and Waseela microfinance bank), (iii)

Timepey (operated by Zong and Askari bank) and (v) Upayment (operated by Ufone, Habib bank

limited, Summit bank limited, Soneri bank and Bank Al Habib limited).

The justification for choosing the cellular companies of Pakistan is evident with the fact

that it is the fastest growing and economic contributing sector that boosts the 0.28 percent of

Pakistan GDP with only 1 percent increase in its mobile phone subscription (PTA, 2018). Presently

the cellular companies of Pakistan are not only providing cellular services (through GSM sims) to

general public, but also playing its crucial role in some Government-to-Public G2P payment

projects such as Benazir Income Support Program Project, Guzara Allowance in Sindh, e-

Agriculture project (i.e. providing weather forecast, farm advisory and market prices alert etc.)

(PTA, 2018). In addition to these, cellular companies are also regulating the branchless banking

operations in collaboration with certain financial institutes of Pakistan (PTA, 2018). These are

some additional business models carried by cellular companies for the generation of revenues in

parallel with the parental business model of mobile services subscription (PTA, 2018). Thus, the

concept of business model innovation and innovation capabilities that are briefly investigated in

this research work are best reflected in the existing operations of cellular companies of Pakistan.

In this connection, this research work has selected the four cellular companies of Pakistan as the

population of this research work.

3.4.1. Unit of Analysis

The unit of analysis of this research work are the upper management and middle managers

(i.e. including chief executives, deputy chiefs, head of departments, senior managers, divisional

managers, team leaders, project managers, zonal managers etc.) of cellular companies of Pakistan.

Upper and middle managements are selected because of the following reasons,

• Den Hertog et al. (2010) argued that the concept of innovation capabilities can be measured

from those members who carries the information and valid knowledge relating major


82

business process of the organization (Miller et al., 1998; Janssen, Castaldi & Alexiev,

2015). It may include chief executives, senior executives and senior managers (Den Hertog

et al., 2010; Janssen et al., 2015).

• The concept of service innovation success involves the salient features of innovation

success that are also associated with competitive positioning among the other industry

players. Riel et al. (2016) argued that the service innovation success can be better reflected

among the responsible position holders of the organization such as chief executives,

departmental heads, product managers, technical managers, service managers, marketing

manager, other senior managers etc.

• Mitchell and Coles (2003) were the first ones who coined the idea that the chief executives

of the organization can objectively bring innovation in their organization’s business model.

The concept of business model innovation involves the changes in the creation of values

(in terms of new capabilities, processes, equipment etc.) offering value to customer or

market and capturing the value in terms of new cost or revenue structures. Clauss (2017)

stated that these forms of changes could better be measured from the responsible position

holder of the organization that are upper management (such as chief executive and business

leaders) and a middle layer of management (including divisional managers, group leaders,

project manager, product manager etc.) Trapp et al. (2018) also argued that the tool to

measure the existing definitions and illustration of business model innovation in the

organization needs the senior corporate managers and executives to articulate.

Therefore, keeping in view these existing researches supported aspect and the philosophy

of the research framework, this research work have chosen the upper management and middle

managers of the four cellular companies as the unit of analysis for this research work.

3.4.2. Determination of Sample Size

The population frame of this research work consists of approximate 1274 participants

(including chief executive, deputy chiefs, head of departments, senior managers, divisional

managers, regional or zonal managers, and project managers) from the four cellular firms


83

nationwide, as per the statistics gathered by their respective HR departments. Saunder (2009)

indicated that the minimum 370 sample size (roughly) may be required from the population frame

of 5001 to 10,000 at a 95 percent confidence interval for a five percent margin of error. Some of

the other researchers pointed out that the minimum sample size of 200 is sufficient for the

attainment of generalizable results (Kelloway, 1988; Roscoe, 1975). On the other hand, Krejice

and Morgan (1970) came up with a mathematical formula for the calculation of minimum sample

size for the finite population as,

S = X2 NP (1-P)

d2 (N-1) + X2 P (1-P)

However, the term ‘N’ in this mathematical expression, represents the total population size

(1274); the term “P” refers to the population proportion (0.5) that is usually assumed to 50 percent

(maximum possible sample size); the term “d” indicates the degree of accuracy (0.05) usually

assumed to be 5 percent margin of errors and lastly the term “X” refers to the constant value of

1.96 at 95 percent confidence level. By putting these values, it can be calculated as,

S = (1.96)2 (1274) (0.5)(1 - 0.5) .

(0.05)2 (1274-1) + (1.96)2 (0.5) (1 - 0.5)

S = 295

It reveals that the minimum sample size of ‘295’ would be required by this research work

in order to obtain acceptable and generalizable results at of 95 percent level of confidence, by

using the finite population formula of Krejcie and Morgan (1980).

3.4.3. Selection of Sample and Sampling Technique

In order to select the minimum size of 295 participants, this research work has adopted a

simple random sampling strategy. A random sampling strategy is a form of probability sampling


84

technique in which the each and every member of the whole population frame carries the equal

chance to get picked for a sample of the study (Sekaran, 2001). Random sampling provides a better

representation of the population in the selected sample with enhanced generalizability of results

(Sekaran, 2001). Saunder et al., (2009) explained that the researches who does not require face to

face contacts and no relevant strata exist in the sampling frame with no periodic patterns, such

researches should choose simple random sampling strategy. It is pertinent to mention that the

responses from the senior chiefs, departmental heads and middle managers of cellular companies

do not require face-to-face contact for the filling of the research questionnaire. In addition, the

population frame does not constitute any prominent cluster or strata. Therefore, this research work

has opted for the simple random sampling strategy for the selection of sample size from the

population frame in light of illustration of selecting the probability sampling strategy by Saunder

et al. (2009). Thus, five hundred and fifty (550) participants were selected under the simple random

sampling technique. The methodology followed in the selection of sample under simple random

sampling strategy is as follows,

• At the initial step, the list of participants of four cellular companies (comprising of total

1274 approximate population) is obtained from the respective HR departments of each

organization. It is crucial to inform here that the HR departments have only shared the

employee code keeping in view the secrecy and privacy of credentials.

• Each employee code in the provided list is allocated with a unique serial number, starting

from zero (0).

• The respondents are randomly picked through the MS Excel program. The ‘RAND’

function is used in MS Excel program that automatically picked the five hundred and

fifty participants with the coded unique serial number. The questionnaire (mentioned

with the selected employee code) were floated to the respective HR department for the

acquisition of responses from the picked sample of 550 participants.

3.4.4. Data Collection

The research questionnaires (with the marked employee codes) were handed to the

respective HR departments of four cellular companies namely Telenor, Mobilink – Warid, Ufone,


85

and Zong. The concerned authorities of HR Department were requested to hand over the provided

printed questionnaires (each with the marked employee codes) to the respective personnel only.

These selected personnel’s of cellular firms were numerous time reminded via the concerned HR

authorities for the return of filled questionnaires. Numerous telephonic, email reminders and

personal visits to HR departments were the efforts of this survey process. Total of five hundred

and fifty (550) research questionnaires were floated. In response four hundred and twenty-seven

(427) completely filled questionnaires were received with the overall response rate of 77.63

percent.

3.5. Reliability and Validity of Research Instrument

Pre-testing constitutes the face validity and content validity analysis of finalized research

instrument. The establishment of satisfactory level of face validity and content validy, further

paves the way for the rigorous validity and reliability testing of research instrument. The validity

and reliability of the research instrument were tested by using Kouftero’s (1999) approach.

Kouftero (1999) explained that the validity of the research instrument can be tested in four steps.

First of all, the traditional method (i.e. measuring construct validity only) may be employed for

testing the measurement model through the exploratory factor analysis and reliability estimation

after item extraction of EFA. However, this earlier traditional approach carries some shortcomings

in terms of assessment of uni-dimensionality and other measurement model properties i.e. item

reliability and model fit indices (Kouftero, 1999; Gerbing & Anderson, 1988) that are covered by

Kouftero’s approach (1999). In the next steps, these shortcomings are covered through testing the

convergent validity (t-values and item reliability), model fit indices through confirmatory factor

analysis. After the iterative process of confirmatory factor analysis, the construct reliability of

residual eligible items of measurement models is calculated. In the last step, the discriminate

validity of the constructs is checked through the Pearson correlation. Average variance extracted

are also calculated at this step. The successful validation of the items measuring the construct and

sub-constructs further entails the testing of structural relationship of constructs.

3.5.1. Face Validity.

The face validity involves the process of reviewing the research questionnaire by the expert

of the questionnaire’s subject area (Saunder et al., 2009). The face validity of the research

instrument is said to be establish when this expert concludes that the questionnaire carries all the


86

traits or characteristics to which it intends to measure (Saunder et al., 2009). In this regard, the

final version of the research instrument is shared with the three reputable Ph.D. faculty members

of national universities (of subject area) with an intention to obtain the valuable constructive expert

opinion from an academic research perspective. In addition to the three local opinions, an expert

opinion is also obtained by an international researcher (Ph.D. faculty member) of technologically

/ academically advance country (as categorized by HEC, Pakistan). The finalized research

instrument, operationalization of constructs, measures of constructs, sources of measures, the

elaboration of theoretical framework and research objectives of study were shared with these

subject experts to get conformity. Just being checked on the face of finalized research with this

provided information of study, all experts verbally agree that the finalized research instrument is

a valid measure for the constructs which are being measured. Thus, the face validity of the research

instrument is established.

3.5.2. Content Validity.

The content validity involves that the research measures represents all the facets or

contents of the research constructs that needs to be measured (Saunder et al., 2009). In order to

assess the content validity of the research instrument, the three reputable practitioners of middle

management were asked to review all of the items for readability, clarity and comprehensiveness.

The practitioners were asked to provide their feedback about items in two judgments (favorable or

not favorable) keeping in view the readability, clarity and comprehensive of items. All the

practitioners passed the favorable judgment for all the items of finalized research instrument with

the recommendation of negligible changes.

3.5.3. Construct validity (Exploratory factor analysis).

The construct validity checks how well the results justifies and rationalizes the theory for

which that particular research instrument was developed (Sekaran, 2003). The exploratory factor

analysis is considered as the most common statistical tool for checking the construct validity of

the research instruments (Hair et al., 2010; Sekaran, 2003; Koufteros, 1999). Therefore, this

research study has also tested the construct validity via the exploratory factor analysis. Table 3.1

reveals the results of the exploratory factor analysis for the construct of innovation capabilities.


87

Table 3.1. Exploratory Factor Analysis for the Scale of Innovation Capabilities

Items

Factors

1

*IC4

2

*IC2

3

*IC5

4

*IC1

5

*IC3

1. We systematically observe and evaluate the need of our customers .178 .297 .177 .742 .100

2. We analyze the actual use of our services. .340 .234 .227 .689 .097

3. Our organization is strong in distinguishing different groups of users and

market segments .313 .201 .233 .675 .011

4. Staying up to date with promising new services and technologies is

important for our organization .336 .768 .003 .061 .049

5. In order to identify the possibilities for new services, we use different

information sources .153 .781 .135 .224 .084

6. We follow which technologies our competitors use .197 .861 .163 .091 .005

7. We are innovative in coming up with ideas for new service concepts .048 .033 .049 .016 .894

8. Our organization experiments with new service concepts .156 .106 .147 .184 .061

9. We align new service offerings with our current business and processes .069 .057 .091 .025 .878

10. Collaborations with other organizations helps us in improving or

introducing new services .755 .207 .072 .094 .041

11. Our organization is strong in coordinating service innovation activities

involving several parties .827 .179 .121 .124 .015

12. Our organization is efficient in initiatives and maintaining the partnerships .749 .242 .191 .106 .063

13. In the development of new services, we take into account our branding

strategy .182 .125 .742 .101 .059

14. Our organization is actively engaged in promoting its new services -.002 -.023 .841 -.013 -.026

15. We introduce new services by following our marketing plan .255 .275 .627 .221 .027

Total Rotation Sum of Squares

% of Variance (Rotated)

Cumulative % of Variance

2.365

15.766

15.766

2.364

15.762

31.529

1.920

12.803

44.332

1.873

12.487

56.819

1.613

10.755

67.574

KMO & Barlett’s Test: KMO = .842; Chi-Square =2193.450, df = 105, p-value = .000

Note. *IC1 = Sensing user needs; IC2 = Sensing technological options; IC3 = Conceptualization; IC4 = Coproducing

and orchestrating; IC5 = Scaling and Stretching.

It was found that the 67.54 percent of the cumulative variance of innovation capabilities

are explained by its five sub-constructs. The result also revealed that the sub-construct “co-

producing and orchestrating” accounts for the highest variance (15.766 percent) among the other

sub-constructs with the highest rotated sum of squares value of 2.365. On the other hand, the sub-


88

construct “conceptualization” was found to possess the lowest variance (10.75 percent) with the

lowest rotated sum of squares of 1.613. The results also revealed that all the items of the research

instrument (except item number 8) were appropriately loaded with the factor loading values

ranging from .627 to .894 (that is greater than 0.4). However, the item number 8 (measuring the

sub-construct conceptualization) showed poor factor loading that needs to be excluded from the

final research instrument. The results of KMO and Barlett’s Test for the sample adequacy for the

construct of innovation capabilities was also found to be significant with the value of .842 (that is

greater than .6) with the p-value of .000 (that is less than .05).

Figure 3.2. Scree Plot for Innovation Capabilities Scale

Figure 3.2 portrays the scree plot for the extracted factors of the construct innovation

capabilities. The results of the exploratory factor analysis sketch the scree plot with the number of

factors (drawn at x-axis) and the loaded initial eigenvalues (drawn at y-axis). Figure 3.2 also

reveals that component 1 - 5 possess the initial eigenvalue greater than one. From component six

(lying near the cut-off value one), the scree plot starts flattens onwards with the lower eigenvalues

of the residual components. Thus, the scree plot supports the above results that the five components

(lying above the cut-off value one) factors stand eligible for the retention.

Table 3.2. Exploratory Factor Analysis for the Scale of Service Innovation Success


89

Items

Factors

1

*IS1

2

*IS3

3

*IS2

16. The new service is an overall success .784 .223 .153

17. Success exceeds expectations. .802 .164 .224

18. The new service contributed to financial success .795 .153 .178

19. The new service was a good idea to invest in .778 .232 .207

20. The new service adds substantial value to other products and services .631 .476 .124

21. The new service contributed to commercial success. .273 .332 .583

22. The new service improved our competitive position. .161 .102 .702

23. The new service improved brand equity and reputation. -.002 -.069 .829

24. The new service enabled expansion into new markets .313 .250 .562

25. The new service increased customer satisfaction and loyalty .280 .319 .640

26. The new service increased in-house technological knowledge .217 .814 .060

27. The new service increased employee satisfaction. .246 .740 .210

28. The new service created innovation opportunities .213 .831 .212




3.325

25.576

25.576

2.571

19.775

45.351

2.503

19.253

64.604


Note. *IS1 = Short term success; IS2 = Long term success; IS3 = Indirect Success.

Table 3.2 reflects the results of the exploratory factor analysis for the construct of

innovation success. The results show that 64.604 percent of cumulative variance on innovation

success is explained by its three sub-constructs. The result also reflect that the sub-construct “short

term success” accounts for the highest variance (25.576 percent) among the other sub-constructs

with the highest rotated sum of squares value of 3.325. On the other hand, the sub-construct “long

term success” is found to possess the lowest variance (19.25 percent) with the lowest rotated sum

of squares of 2.503. The results also reveal that all the items of the research instrument (except

item number 20) are appropriately loaded with the factor loading values ranging from .562 to .831.

However, the item number 20 (measuring the sub-construct short term success) was found to be


90

cross-loaded with the values of .631 and .476 among the component 1(short term success) and

component 2 (indirect success). This cross-loading qualifies the item number 20 to be excluded

from the final research instrument. The results of KMO and Barlett’s Test for the construct of

innovation success was also found to be significant with the value of .906 (that is greater than .6)

with the p-value of .000 (that is less than .05). Figure 3.3 portrays the scree plot for the extracted

factors of the construct innovation success. The scree plot also reflects that the three components

(lying above the cut-off value one) stand eligible for the retention.

Figure 3.3. Scree Plot for Innovation Success Scale

Table 3.3 shows the results of exploratory factor analysis for the construct of management

entrepreneurial orientation. The results show that 74.288 percent of cumulative variance on

entrepreneurial orientation is explained by its four sub-constructs that are ready to innovate,

aggressively competitiveness, market proactiveness, and risk-taking. The result also reflects that

the sub-construct “ready to innovate” accounts for the highest variance (20.55 percent) among the

other sub-constructs with the highest rotated sum of squares value of 2.26. On the other hand, the

sub-construct “aggressive competitiveness” is found to possess the lowest variance (14.56 percent)

with the lowest rotated sum of squares value of 1.602.


91

Table 3.3. Exploratory Factor Analysis for Management Entrepreneurial Orientation Scale

Items

Factors

1

*EO1

2

*EO3

3

*EO4

4

*EO2

29. In general, the top managers of our organization favor a strong

emphasis on research and development, technological leadership and

innovations.

.807 .198 .246 .091

30. In the past five years, our organization has marketed a large variety

of new lines of products or services. .800 .163 .241 -.003

31. In the past five years, changes in our product or service lines have

been mostly of a minor nature (reverse coded) .836 .252 .126 -.019

32. In dealing with competitors, our organization often leads the

competition, initiating actions to which our competitors have to

respond.

.011 .030 .041 .892

33. In dealing with competitors, our organization typically adopts a

very competitive posture aiming at overtaking the competitors. .034 -.049 -.053 .885

34. In general, the top managers of my organization have a strong

propensity for high risk projects (with chances of high return) .141 .761 .324 .048

35. The top managers believe owing to the nature of environment,

bold, wide-ranging acts are necessary to achieve our organization

objectives

.257 .783 .167 -.073

36. When there is uncertainty, our organization typically adopts a

“wait and see” posture in order to minimize the probability of making

costly decisions (reverse coded)

.224 .853 .182 .002

37. Management actively responds to the adoption of “new ways of

doing things” by main competitors .120 .223 .773 .049

38. We are willing to try new ways of doing things and seek usual,

novel solutions. .247 .167 .812 -.015

39. We encourage people to think and behave in original and novel

ways. .238 .230 .751 -.060




2.262

20.559

20.559

2.182

19.840

40.399

2.126

19.327

59.726

1.602

14.562

74.288


Note. *EO1 = Ready to innovate; EO2 = Aggressively competitiveness; EO3 = Market Proactiveness; EO4 = Risk

Taking.

The results also reveal that all the items of the research instrument are appropriately

loaded with the factor loading values ranging from .751 to .892. The results of KMO and Barlett’s

Test for the construct of entrepreneurial orientation is also found to be significant with the value

of .833 (that is greater than .6) with the p-value of .000 (that is less than .05). Figure 3.4 portrays

the scree plot for the extracted factors of the construct management entrepreneurial orientation.


92

The scree plot also reflects that the four components (lying above the cut-off value one) stand

eligible for the retention.

Figure 3.4. Scree

Plot for Management

Entrepreneurial

Orientation Scale

Table 3.4

shows the results of exploratory factor analysis for the construct of employee resistance. The

results show that 60.203 percent of cumulative variance on employee resistance is explained by its

four sub-constructs (that are routine seeking, emotional reaction, short term focus, and cognitive

rigidity). The result also reflects that the sub-construct “routine seeking” accounts for the highest

variance (17.26 percent) among the other sub-constructs with the highest rotated sum of squares

value of 2.58. On the other hand, the sub-construct “cognitive rigidity” is found to possess the

lowest variance (13.74 percent) with the lowest rotated sum of squares value of 2.06.

Table 3.4. Exploratory Factor Analysis for Employee Resistance Scale


93

Items

Factors

1

*ER1

2

*ER2

3

*ER3

4

*ER4

40. I would rather be bored than surprise. .783 .122 .195 .082

41. Generally change is not good .735 .263 .032 .263

42. Whenever my life forms a stable routine, I look for ways to change it. .658 .130 .217 .211

43. I prefer having a stable routine of experiencing a change in my life .756 .146 .215 .063

44. If I were to be informed that there’s going to be a significant change regarding the

way things are done at work, I would probably feel stressed. .271 .563 .269 .120

45. If I were to be informed that there’s going to be a change in one of my assignment at

work, prior to knowing what the change actually is, it would probably stress me out. .127 .690 .089 .179

46. When I am informed of a change of plans, I tense up a bit. -.027 .821 .000 .055

47. If my boss changed the criteria of evaluating employees, it would probably make me

feel uncomfortable even if I thought I’d do just as well without having to do any extra

work.

.240 .372 .272 .223

48. If in the middle of the work year, I were to be informed that there’s going to be a

change in the schedule of deadlines, prior to knowing what the change actually is, I

would probably presume that the change is worse

.291 .524 .101 .065

49. Changing plans seems like a real hassle to me .159 .063 .748 .291

50. When someone pressures me to change something, I tend to resist it even if I think

the change may ultimately benefit me. .246 .209 .709 .080

51. Once I have made plans, I am not likely to change them. .175 .147 .834 .201

52. I don’t change my mind easily .070 .096 .245 .716

53. I don’t often change my mind .193 .168 .106 .802

54. My views are very consistent over time. .202 .173 .170 .740




2.589

17.262

17.262

2.223

14.819

32.082

2.156

14.376

46.458

2.062

13.746

60.203


Note. *ER1 = Routine seeking; ER2 = Emotional Reaction; ER3 = Short term focus; ER4 = Cognitive Rigidity.


94

The results also reveal that all the items of the research instrument (except item number

47) are appropriately loaded with the factor loading values ranging from .524 to .834. However,

the item number 47 (measuring the sub-construct emotional reaction) is found to possess the poor

factor loading (that is below than 0.4). Thus, the item number 47 founds eligible to be eliminated

from the final version of the research instrument. The results of KMO and Barlett’s test is also

found to be significant with the value of .891 (that is greater than .6) with the p-value of .000 (that

is less than .05). Figure 3.5 portrays the scree plot for the extracted factors of the construct

employee resistance. The scree plot also reflects that the four components (lying above the cut-off

value one) stand eligible for the retention.

Figure 3.5. Scree Plot for Employee Resistance Scale

Table 3.5 shows the results of exploratory factor analysis for the construct of business

model innovation. The results show that the 60.203 percent of cumulative variance on employee

resistance is explained by its ten third-order sub-constructs (that are new capabilities, new

technology or equipment, new partnerships, new processes, new offerings, new customers and

markets, new channels, new customer relationship, new revenue models and lastly, new cost

structures). The result also reflects that the sub-construct “new cost structures” accounts for the

highest variance (10.67 percent) among the remaining nine sub-constructs with the highest rotated

sum of squares value of 3.52. On the other hand, the sub-construct “new customer relationship” is

found to possess the lowest variance (3.72 percent) with the lowest rotated sum of squares value

of 1.22.


95

Table 3.5. Exploratory Factor Analysis for Business Model Innovation Scale

Items

Factors

1

*B10

2

*B5

3

*B3

4

*B2

5

*B1

6

*B9

7

*B6

8

*B4

9

*B7

10

*B8

55. Our employees constantly receive

training in order to develop new

competences

.114 -.042 .025 .127 .813 .074 .037 .074 .013 .028

56. Relative to our direct competitors,

our employees have very up-to-date

knowledge and capabilities.

.098 .030 -.046 .072 .893 .089 .117 .108 .000 .005

57. We constantly reflect on which new

competencies need to be established in

order to adapt to changing market

requirements.

.061 -.031 .034 .077 .889 .148 .049 .132 -.038 -.059

58. We keep the technical resources of

our company up-to-date. .070 .091 .028 .807 .168 .134 .077 .134 -.018 .043

59. Relative to our competitors our

technical equipment is very innovative. .116 .044 .013 .910 .065 .109 .131 .190 .034 -.008

60. We regularly utilize new technical

opportunities in order to extend our

product and service portfolio.

.113 .054 .028 .932 .065 .069 .088 .172 .032 -.13

61. We are constantly searching for new

collaboration partners. .102 .103 .057 -.222 .253 -.401 .157 .181 .264 .310

62. We regularly utilize opportunities

that arise from integration of new

partners into our processes.

.042 -.060 .943 -.001 -.007 .002 .048 .000 .039 .015

63. We regularly evaluate the potential

benefits of outsourcing. .047 -.041 .951 .013 -.001 .001 -.002 .037 .018 .001

64. New collaboration partners regularly

help us to further develop our business

model.

.049 -.036 .955 -.003 -.033 .020 .018 .014 .007 .006

65. We were recently able to

significantly improve our internal

processes.

.201 .237 .073 .051 .184 .364 .178 .693 .040 .040

66. We utilize innovative procedures and

processes during the manufacturing of

our products as well as in all business

processes.

.236 .117 .008 .266 .093 .128 .101 .842 .026 -.012

67. Existing processes are regularly

assessed and significantly changed if

needed.

.121 .138 -.004 .314 .174 .123 .111 .836 .022 .004

68. We regularly address new, unmet

customer needs. .116 .940 -.049 .075 -.046 .142 .042 .125 .084 .079

69. Our products or services are very

innovative in relation to our competitors. .109 .901 .039 .063 .016 .158 .048 .146 .083 .050

70. Our products regularly solve

customer needs, which were not solved

by competitors.

.107 .934 .075 .077 -.046 .146 .060 .135 .086 .081

71. We regularly take opportunities that

arise in new or growing markets. .011 .052 .048 .192 -.039 .115 .760 .091 -.009 -.025


96

72. We regularly address new, unserved

market segments. .006 .045 -.002 .052 .173 .053 .851 .130 -.006 -.002

73. We are constantly seeking new

customer segments and markets for our

products and services.

-.025 .060 -.008 .070 .145 .244 .831 .027 .019 -.025

74. We regularly utilize new distribution

channels for our products and services. .004 .157 .015 -.007 -.017 .128 .008 .043 .907 .002

75. Constant changes of our channels

have led to improved efficiency of our

channel functions.

.003 .353 .008 -.245 .235 .263 .054 -.120 .103 -.376

76. We consistently change our portfolio

of distribution channels. -.034 .079 .029 .048 -.008 .093 .009 .015 .920 .056

77. We try to increase customer retention

by new service offerings. -.008 .000 .014 .016 -.005 .134 -.064 -.001 -.039 .734

78. We emphasize innovative/modern

actions to increase customer retention

(e.g. CRM).

.111 .367 -.044 .021 -.004 .068 .045 -.032 .177 .614

79. We recently took many actions in

order to strengthen customer

relationships.

.057 -.026 -.379 -.112 -.138 -.106 .356 .003 .067 .012

80. We recently developed new revenue

opportunities (e.g. additional sales, cross-

selling).

.232 .315 .030 .220 .070 .529 -.063 .339 .151 .019

81. We increasingly offer integrated

services (e.g. maintenance contracts) in

order to realize long-term financial

returns.

.212 .136 .036 .118 .194 .748 .262 .145 .157 .139

82. We recently complemented or

replaced one-time transaction revenues

with long-term recurring revenue models

(e.g. Leasing).

.209 .240 .062 .065 .118 .755 .212 .200 .108 .082

83. We do not rely on the durability of

our existing revenue sources. .178 .272 .009 .147 .251 .668 .222 .231 .100 .136

84. We regularly reflect on our price-

quantity strategy. .924 .118 .038 .070 .061 .102 .031 .120 -.016 .006

85. We actively seek opportunities to

save manufacturing costs. .866 .060 .036 .045 .086 .067 -.057 .096 .004 .040

86. Our production costs are constantly

examined and if necessary amended

according to market prices. .803 .056 -.003 .102 .091 .181 .041 .103 .001 .045

87. We regularly utilize opportunities

which arise through price differentiation. .926 .115 .047 .080 .061 .089 .021 .116 -.014 .006




3.521

10.670

10.670

3.273

9.917

20.58

2.891

8.760

29.34

2.844

8.619

37.965

2.697

8.173

46.139

2.578

7.812

53.95

2.439

7.392

61.34

2.417

7.325

68.66

1.887

5.719

74.38

1.229

3.724

78.11


Note. *B1 = New capabilities; B2 = New technology / equipment, B3 = New partnerships; B4 = New processes; B5

= New offerings; B6 = New customers and markets; B7 = New channels; B8 = New customer relationship; B9 = New

revenue models; B10 = New cost structures.


97

The results also revealed that all the items of the research instrument (except item number

61, 75, 79) are appropriately loaded with the factor loading values ranging from .529 to .955.

However, the three items 61, 75 and 79 (measuring the sub-constructs new partnerships, new

channels, and new customer relationships respectively) are found to possess the poor factor loading

(that is below than 0.4). Thus, these items (i.e. 61, 74 and 79) are found eligible to be eliminated

from the final version of the research instrument. The results of KMO and Barlett’s Test is also

found to be significant with the value of .808 (that is greater than .6) with the p-value of .000 (that

is less than .05). Figure 3.6 portrays the scree plot for business model innovation.

Figure 3.6. Scree Plot for Business Model Innovation Scale

The scree plot also reflects that the ten components (lying above the cut-off value one)

stand eligible for the retention. Table 3.6 summarizes the overall results of exploratory factor

analysis for all the constructs of this research study. It is pertinent to mention here, that one of the

objectives of conducting the exploratory factor analysis is to reduce the data with more defined

clusters (in form of factors). Similarly, it is found that the total six items (that are 8, 20, 47, 61, 75

and 79) qualify to be eliminated due to cross loading or poor factor loadings. Thus, it reduces the

earlier ninety (90) items research instrument to the eighty-four (84) items research instrument for

the measurement of the five constructs of this research study. Thus, all the basic conditions of

exploratory factor analysis are successfully met for the five constructs of this research work that


98

are innovation capabilities, innovation success, management entrepreneurial orientation, employee

resistance, and business model innovation).

Table 3.6. Summarizing the Overall Results of Exploratory Factor Analysis

Constructs Sub-Constructs Total

Items

Items

removed

Items

retained in

scale

Innovation

Capabilities

Sensing user needs 3 0 3

Sensing technological options 3 0 3 Conceptualization 3 1 2 Coproducing and Orchestrating 3 0 3 Scaling and Stretching 3 0 3

15 1 14

Innovation

Success

Short term success 5 1 4

Long term success 5 0 5

Indirect success 3 0 3

13 1 12

Management

Entrepreneurial

Orientation

Ready to innovate 3 0 3

Aggressively competitiveness 2 0 2

Market Proactiveness 3 0 3

Risk taking 3 0 3

11 0 11

Employee

Resistance

Routine seeking 4 0 4

Emotional Reaction 5 1 4

Short term focus 3 0 3

Cognitive Rigidity 3 0 3

15 1 14

Business

Model

Innovation

New capabilities 3 0 3

New technology 3 0 3

New partnerships 4 1 3

New processes 3 0 3

New offerings 3 0 3

New customer and markets 3 0 3

New channels 3 1 2

New customer relationships 3 1 2

New revenue models 4 0 4

New cost structures 4 0 4

33 3 30

Demographics 3 -- 3

Total Items 90 6 84

3.5.4. Construct reliability (Cronbach alpha).

The construct reliability reflects that all the items measuring a single construct are

consistent with each other (Sekaran, 2003). The Cronbach alpha value is generally checked in

order to test the construct reliability (Sekaran, 2003). It is believed that the values above and equals


99

to the 0.6 are minimally required for the items of the construct to be claimed as reliable (Sekaran,

2003). Table 3.7 shows the results of Cronbach alpha reliability estimates for all the research

constructs and sub-constructs of this research work.

Table 3.7. Reliability Analysis of Constructs and Sub-constructs after Extraction

Constructs Sub-Constructs

Total

Items after

extraction

Cronbach

alpha value

Innovation

Capabilities

Sensing user needs 3 .822

Sensing technological options 3 .815

Conceptualization 2 .739

Coproducing and Orchestrating 3 .779

Scaling and Stretching 3 .675

14 .841

Innovation

Success

Short term success 4 .864

Long term success 5 .770

Indirect success 3 .810

12 .876

Management

Entrepreneurial

Orientation

Ready to innovate 3 .833

Aggressively competitiveness 2 .739

Market Proactiveness 3 .815

Risk-taking 3 .779

11 .830

Employee

Resistance

Routine seeking 4 .799

Emotional Reaction 4 .759

Short term focus 3 .774

Cognitive Rigidity 3 .731

14 .860

Business

Model

Innovation

New capabilities 3 .886

New technology 3 .925

New partnerships 3 .958

New processes 3 .899

New offerings 3 .974

New customer and markets 3 .828

New channels 2 .862

New customer relationships 2 .950

New revenue models 4 .878

New cost structures 4 .926

30 .885

Total items 81 .891

The results show that all the five research constructs of this research study (that are

innovation capabilities, innovation success, entrepreneurial orientation, employee resistance and

business model innovation) possess the acceptable Cronbach alpha value of .841, .876, .830, .860

and .885 respectively. Furthermore, it is also found that all the sub-constructs of these five study

variables also possess the acceptable Cronbach alpha values ranging from .675 to .958.


100

Thus, the basic condition on construct reliability for the five study variables (innovation

capabilities, innovation success, management entrepreneurial orientation, employee resistance and

business model innovation) is also found to be consistent.

3.5.5. Convergent validity and item reliability (confirmatory factor analysis).

Convergent validity refers to the extent to which the measures of the construct or sub-

construct (that are theoretically correlated) are factually correlated with each other or not (Sekaran,

2003). Koufteros (1999) explain that the convergent validity can be checked by overlooking the

two essential aspects of item’s squared correlation values (that is also known as item reliability)

and the t-value (the ratio of factor loading and error terms). These two parameters can be calculated

through confirmatory factor analysis (Koufteros, 1999). It is also pertinent to mention that the

dimensionality assessment and model fit indices are also essential performance parameters for the

validity of research instrument. And these dimensionality assessment and model fit indices can

only be checked through confirmatory factor analysis. The results of confirmatory factor analysis

for all the constructs of this research study are detailed in table 3.8 in appendix-II.

The results revealed that all the remaining eighty one (81) items (six items qualified to

eliminate during construct validity) measuring the five research constructs of this study possess

the significant factor loading (that is above than 0.4) ranging from .503 to .999. Items t-values are

calculated by comparing (i.e. ratio of) the factor loadings with their standard errors (Bollen, 1989).

Higher factor loadings in comparison to their standard error refers that stronger these item

measures their constructs. The t-values above or equal to 2 are considered to be significant (Bollen,

1989). The results reveal that the t-value of all the items are significant with the values (greater

than 2) ranging from 5.405 to 997. It means that all these items are significantly related to their

respective constructs.

The second parameter of convergent validity is item reliability (R square value) that should

be above than 0.5 (Bollen, 1989; Koufteros, 1999). It is found that all the items (except item

number 14, 23, 42 and 48) possess the R square value greater than 0.59. It reflects that these items

possess the significant item reliability. The items (ie. 14, 23, 42 and 48) possessing the R square

value less than 0.5 can be regarded as less performers and qualifies to be dropped from the

respective scale (Koufteros, 1999). Thus, four items (14, 23, 42 and 48) qualifies to be eliminated

during this iterative process of confirmatory factor analysis.


101

The model fitness of the five constructs are also checked in confirmatory factor analysis.

Some researchers explain that the ratio of CMIN to degree of freedom below or equals to three (3)

represents the goodness fit of the measurement model (Marsh and Hocevar, 1985; Joreskog and

Sorbom, 1993). The results show that all the five constructs namely innovation capabilities,

innovation success, management entrepreneurial orientation, employee resistance and business

model innovation possess the good parsimonious fit with CMIN / df values of 2.01, 2.62, 1.69,

2.29 and 2.37 with the p-values of .000, .000, .000, .000 and .000 respectively.

The other model fitness measures such as absolute fitness measures and incremental fitness

measures of these five constructs are also checked. It is believed that the score of one (1) for

incremental fitness measures such as comparative fit index (CFI), adjusted goodness of fit (AGFI),

tucker lewis index (TLI) and normed fit index (NFI) reflects the perfect model (Bentler, 1972).

Tanaka and Huba (1985) report that the value of adjusted goodness of fit (AGFI) and goodness of

fit (GFI) should not be less than 0.9 for model to be claimed as good. Similarly, some researchers

also report that the value of tucker lewis index (TLI) and normed fit index (NFI) should not be less

than 0.9 (Bentler and Bonett, 1980; Bollen, 1989). Table 3.8 shows that the values of incremental

fit measures of NFI, GFI, AGFI and TLI for five constructs of study are found to be above than

0.9 that reflects the good fitness of measurement models. The absolute fit measures such as root

mean square error of approximation (RMSEA), standardized root mean square residual (SRMR)

and p of close fit (PCLOSE) are also checked. These measures represents the bad fitness of model.

Browne and Cudeck (1993) report that the values of bad fitness measures SRMR and RMSEA

should be less than or equal to .08. The values higher to .08 reflects the bad fitness of model and

the value closer to zero (but less than .08) reflects the good fitness of model. Table 3.8 shows that

value of RMSEA for five constructs namely innovation capabilities, innovation success,

management entrepreneurial orientation, employee resistance and business model innovation are

.049, .062, .041, .055 and .047 respectively. Kenny (2014) report the value of PCLOSE should be

greater than 0.05 for the good fit model in comparison to close fitting. The results of fit indices at

table 3.8 also show that the five constructs possess the PCLOSE values of .758, .603, .828, .906

and .628 that are greater than 0.05. Similarly, the value of SRMR for the five constructs are also

found to be less than .08 such as .014, .069, .012, .018 and .029. This also supports the good fitness

of measurement models.


102

Summarizing, the confirmatory factor analysis carries the iteration of four more items (14,

23, 42 and 48). It yields the 80 items final version of research instrument that measures the five

constructs of this study namely innovation capabilities, innovation success, management

entrepreneurial orientation, employee resistance and business model innovation. It is also found

that this final version of research instrument possesses the adequate convergent validity (item t-

values and item reliability) and holds the adequate performance (i.e model fit indices) for

measurement of five constructs.

3.5.6. Discriminate validity (Fornell-Lacker criterion).

Discriminate validity checks the extent of correlation of all the measures who are supposed

to be uncorrelated with each other (Sekaran, 2003). Basically, it attempts to testify that all the

research measures who theoretically should be uncorrelated, also empirically carries no or either

low correlation. Pearson correlation is generally believed as the statistical tool for testing the

discriminate validity. Tian and Wilding (2008) report that the correlation values of .1 to .3 shows

the small or weak correlation, .3 to .5 shows the moderate correlation and .5 to .9 shows the large

or strong correlation and 1 shows the perfect correlation. Furr and Bacharach (2014) explain that

there should be no correlation among the research measures in order to fulfill the elementary pre-

requisites of this validity. However, the small or weak significant correlation would be acceptable

and may be interpreted as the meaningless or negligible if the sample size is larger (Furr &

Bacharach, 2014). Fornell and Larcker (1981) explain that the discriminate validity can be checked

by comparing the value of square correlation of measures with the value of average variance

extracted. The value of average variance extracted (AVE) should be larger than the square

correlation value (Fornell & Larcker, 1981).

The results of discriminate validity for the construct of innovation capabilities are shown

in table 3.9. It is found that the sub construct sensing user needs (IC1) possess the no correlation

with the sub-constructs sensing technological options (IC2), conceptualization (IC3) and

coproducing (IC4) with the non-significant p-value of .197, .175 and .235 respectively (that are

greater than .05). The results also reveal the sensing technological options (IC2) also possess no

correlation with the sub-constructs conceptualization (IC3), coproducing (IC4) and scaling

stretching (IC5) with the non-significant p-values of .280, .328 and .279 (greater than .05)

respectively.


103

Table 3.9. Discriminate analysis of innovation capabilities scale

Dimensions IC1 IC2 IC3 IC4 IC5 AVE

Values

IC1

Correlation

Sig(2tailed)

R Square

1 .610

IC2

Correlation

Sig(2tailed)

R Square

.063

.197

.003

1 .573

IC3

Correlation

Sig(2tailed)

R Square

.066

.175

.004

.052

.280

.002

1 .631

IC4

Correlation

Sig(2tailed)

R Square

.058

.235

.003

.047

.328

.002

.021

.660

.001

1 .559

IC5

Correlation

Sig(2tailed)

R Square

.144

.003

.021

.053

.279

.003

.014

.771

.001

.133

.006

.017

1 .433

Note. *IC1 = Sensing user needs; IC2 = Sensing technological options; IC3 = Conceptualization; IC4 = Coproducing

and orchestrating; IC5 = Scaling and Stretching.

Similarly, it is also found that the sub construct conceptualization (IC3) possesses no

correlation with the sub-constructs coproducing (IC4) and scaling stretching (IC5) with the non-

significant p-values of .660 and .771 that are greater than .05. However, the sub-construct scaling

and stretching (IC5) is found to possess a significant weak correlation with the sub-construct

sensing user needs (IC1) and coproducing (IC4) with the correlation value of .144 and .133 with

the p-values of .003 and .006 that is also negligible.

It is also found that the average variance extracted value (.573) of sub construct sensing

technological options (IC2) is greater than the correlation squared value of .003. Similarly, the

average variance extracted value .631 of sub construct conceptualization (IC3) is also found to be

greater than the correlation squared values of .004 and .002. Table 3.9 also show that the average

variance extracted values .559 and .433 of sub-constructs coproducing (IC4) and scaling stretching

(IC5) are found to be greater than the correlation squared values of .003, .002, .001, .021, .003,

.001 and .017 respectively. Thus, these results of discriminate validity for the construct of

innovation capabilities are found to be satisfactory. Table 3.10 represents the results of

discriminate validity for the sub-constructs of innovation success.


104

Table 3.10. Discriminate analysis of innovation success scale

Dimensions IS1 IS2 IS3 AVE

Values

IS1

Correlation

Sig(2tailed)

R Square

1

.615

IS2

Correlation

Sig(2tailed)

R Square

.143

.003

.021

1

.440

IS3

Correlation

Sig(2tailed)

R Square

.017

.723

.001

.038

.432

.001

1

.601

Note. *IS1 = Short term success; IS2 = Long term success; IS3 = Indirect Success.

It is found that the sub-construct long term success (IS2) possesses a weak correlation with

the sub-construct short term success (IS1) with the correlation value of .143 and p-value of .003 <

.05 that is negligible. The result also reveals that the average variance extracted value .440 of long

term success (IS2) is greater than the correlation squared value of .021. Table 3.10 also reflects

that the sub-construct indirect success (IS3) possesses no correlation with the sub-constructs short

term success (IS1) and long term success (IS2) with the non-significant p-values of .723 and .432

respectively. Furthermore, the results also show that the average variance extracted value .601 of

sub construct indirect success (IS3) is greater than the correlation squared values of .001 and .001.

Thus, these results fulfills the foremost assumption of this form of validity for the construct of

innovation success.

Table 3.11 represents the results of discriminate validity for the sub-constructs of

management entrepreneurial orientation. The results show that;

• The sub-construct aggressive competitiveness (EO2) possesses no correlation with the sub-

construct ready to innovate (EO1) with the p-value of .550 which is greater than .05. The result

also reveals that the average variance extracted value .632 of aggressive competitiveness (EO2)

is greater than the correlation squared value of .001.

• The sub construct market proactiveness (EO3) possesses no correlation with the sub construct

aggressive competitiveness (EO2) with the non-significant p-value of .395 that is greater than


105

.05. However, it possesses a weak correlation with the sub constructs ready to innovate (EO1)

with the correlation value of .183 and significant p-values of .000 < .05 that is also negligible.

Furthermore, the results also show that the average variance extracted values .568 of sub

construct market proactiveness (EO3) is larger than the correlation squared values of .033 and

.001.

• The sub construct risk-taking (EO4) possesses no correlation with the sub constructs market

proactiveness (EO3) with the non-significant p value of .189 that is greater than .05. However,

it is also found that risk taking (EO4) possesses the weak correlation with the sub constructs

ready to innovate (EO1) and aggressive competitiveness (EO2) with the correlation value of

.166 and .117 with the significant p-values of .001 and .016 respectively that are negligible.

Furthermore, the results also show that the average variance extracted value .558 of sub

construct risk taking (EO4) is greater than correlation square values of .027, .013 and .004.

Thus, these results fulfill the elementary assumption of discriminate validity for the

construct of management entrepreneurial orientation.

Table 3.11. Discriminate analysis of entrepreneurial orientation scale

Dimensions EO1 EO2 EO3 EO4 AVE

Values

EO1

Correlation

Sig(2tailed)

R Square

1

.621

EO2

Correlation

Sig(2tailed)

R Square

.029

.550

.001

1

.632

EO3

Correlation

Sig(2tailed)

R Square

.183

.000

.033

.041

.395

.001

1

.568

EO4

Correlation

Sig(2tailed)

R Square

.166

.001

.027

.117

.016

.013

.064

.189

.004

1

.558

Note. *EO1 = Ready to innovate; EO2 = Aggressively competitiveness; EO3 = Market Proactiveness; EO4 =

Risk Taking.

Table 3.12 represents the results of discriminate validity for the sub constructs of employee

resistance. The results showed that;


106

• The sub construct emotional reaction (ER2) possesses no correlation with the sub construct

routine seeking (ER1) with the non-significant p-value of .738 that is greater than .05. The

result also reveals that the average variance extracted value .425 of emotional reaction (ER2)

is larger than the correlation squared value of .001.

• The sub construct short term focus (ER3) possesses no correlation with the sub construct

emotional reaction (ER2) and routine seeking (ER1) with the non-significant p-value of .280

and .372 that is greater than .05. Furthermore, the results also show that the average variance

extracted values .581 of sub construct short term focus (ER3) is larger than the correlation

squared values of .002 and .001.

• The sub construct cognitive rigidity (ER4) possess no correlation with the sub constructs short

term focus (ER3), emotional reaction (ER2) and routine seeking (ER1) with the non-significant

p values of .441, .246 and .385 that are greater than .05. It is also found that the average

variance extracted value .567 of sub construct cognitive rigidity (ER4) is larger than correlation

square values of .001, .003 and .001.

Thus, these results fulfill the elementary assumption of discriminate validity for the

construct of employee resistance.

Table 3.12. Discriminate analysis of employee resistance scale

Dimensions ER1 ER2 ER3 ER4 AVE

Values

ER1

Correlation

Sig(2tailed)

R Square

1

.629

ER2

Correlation

Sig(2tailed)

R Square

.016

.738

.001

1

.425

ER3

Correlation

Sig(2tailed)

R Square

.043

.372

.001

.052

.280

.002

1

.581

ER4

Correlation

Sig(2tailed)

R Square

.042

.385

.001

.056

.246

.003

.037

.441

.001

1

.567

Note. *ER1 = Routine seeking; ER2 = Emotional Reaction; ER3 = Short term focus; ER4 = Cognitive Rigidity.


107

Table 3.13 represents the results of discriminate validity for the sub constructs of business

model innovation. The results showed that;

• The sub construct new technology (B2) possess weak correlation with the sub construct new

capabilities (B1) with the correlation value of .213 and significant p-value of .000 < .05 that is

negligible. The result also reveal that the average variance extracted value .924 of new

technology (B2) is greater than the correlation squared value of .045.

• The sub construct new partnerships (B3) possess no correlation with the sub construct new

technology (B2) and new capabilities (B1) with the non-significant p-value of .804 and .095

that are greater than .05. Furthermore, the results also shows that the average variance extracted

values .949 of sub construct new partnerships (B3) is greater than the correlation squared

values of .006 and .001.

• The sub constructs new processes (B4) possess the no correlation with the sub-constructs new

partnerships (B3) with the non-significant p values of .098 that is greater than .05. However,

the new processes (B4) possess weak correlation with the sub-constructs new technology (B2)

and new capabilities (B1) with the correlation values of .140 and .197 with the significant p-

values of .000 and .004 that are also negligible. It is also found that the average variance

extracted value .869 of sub construct new processes (B4) is greater than correlation square

values of .019, .038 and .006.

• The sub constructs new offerings (B5) possess no correlation with the sub-constructs new

capabilities (B1), new partnerships (B3) and new processes (B4) with the non-significant p

values of .555, .091 and .231 that are greater than .05. However, the new offerings (B5) possess

the weak correlation with the new technology (B2) with a correlation value of .169 and

significant p-values of .000 that is also negligible. It is also found that the average variance

extracted value .978 of sub construct new offerings (B5) is greater than correlation square

values of .001, .028, .006 and .003.

• The sub constructs new customers and markets (B6) possess no correlation with the sub-

constructs new partnerships (B3) and new processes (B4) with the non-significant p values of

.725 and .197 that are greater than .05. However, the new customers and markets (B6) possess

the weak correlation with the new capabilities (B1), new technology (B2) and new processes


108

(B5) with correlation values of .218, .204, .149 and significant p-values of .000, .000, .002 that

are also negligible. It is also found that the average variance extracted value .943 of sub

construct new customers and markets (B6) is greater than correlation square values of .047,

.041, .001, .003 and .022.

Table 3.13. Discriminate analysis of business model innovation scale

Dimensions B1 B2 B3 B4 B5 B6 B7 B8 B9

B10

AVE

Values

B1

Correlation

Sig(2tailed)

R Square

1

.905

B2

Correlation

Sig(2tailed)

R Square

.213

.000

.045

1

.924

B3

Correlation

Sig(2tailed)

R Square

.012

.804

.001

.081

.095

.006

1

.949

B4

Correlation

Sig(2tailed)

R Square

.140

.004

.019

.197

.000

.038

.080

.098

.006

1

.869

B5

Correlation

Sig(2tailed)

R Square

.029

.555

.001

.169

.000

.028

.082

.091

.006

.058

.231

.003

1

.978

B6

Correlation

Sig(2tailed)

R Square

.218

.000

.047

.204

.000

.041

.017

.725

.001

.063

.197

.003

.149

.002

.022

1

.943

B7

Correlation

Sig(2tailed)

R Square

.008

.873

.001

.047

.330

.002

.028

.563

.001

.029

.555

.001

.234

.000

.054

.060

.216

.003

1

.880

B8

Correlation

Sig(2tailed)

R Square

.011

.827

.001

.020

.682

.001

.008

.867

.001

.062

.200

.003

.151

.002

.022

.001

.100

.000

.096

.048

.009

1

.555

B9

Correlation

Sig(2tailed)

R Square

.040

.404

.002

.009

.851

.001

.042

.381

.002

.012

.798

.001

.145

.003

.021

.061

.205

.003

.080

.098

.006

.042

.383

.002

1

.862

B10

Correlation

Sig(2tailed)

R Square

.003

.956

.000

.002

.965

.000

.049

.315

.002

.082

.091

.006

.012

.804

.001

.094

.053

.008

.039

.424

.001

.044

.364

.002

.137

.004

.018

1

.855

Note. *B1 = New capabilities; B2 = New technology / equipment, B3 = New partnerships; B4 = New processes;

B5 = New offerings; B6 = New customers and markets; B7 = New channels; B8 = New customer relationship; B9 =

New revenue models; B10 = New customer relationships.


109

• The sub construct new channels (B7) possess no correlation with the sub-constructs new

capabilities (B1), new technology (B2), new partnerships (B3), new processes (B4) and new

customers and markets (B6) with the non-significant p values of .873, .330, .563, .555 and

.216 that are greater than .05. However, the new channels (B7) possess the weak correlation

with the new processes (B5) with correlation values of .234 with a significant p-value of .000

that is also negligible. It is also found that the average variance extracted value .880 of sub

construct new channels (B7) is greater than correlation square values of .001, .002, .001, .001,

.054 and .003.

• The sub construct new customer relationships (B8) possess no correlation with the sub-

constructs new capabilities (B1), new technology (B2), new partnerships (B3), new processes

(B4) and new customers and markets (B6) with the non-significant p values of .827, .682, .867,

.200 and .100 that are greater than .05. However, the new customer relationships (B8) possess

the weak correlation with the new processes (B5) and new channels (B7) with correlation

values of .151, .096 with a significant p-value of .002, .048 that is also negligible. It is also

found that the average variance extracted value .555 of sub construct new customer

relationships (B8) is greater than correlation square values of .001, .001, .001, .003, .022, .000

and .009.

• The sub construct new revenue models (B9) possess no correlation with the sub-constructs

new capabilities (B1), new technology (B2), new partnerships (B3), new processes (B4), new

customers and markets (B6), new channels (B7) and new customer relationships (B8) with the

non-significant p values of .404, .851, .381, .798, .205, .098 and .383 that are greater than .05.

However, the new revenue models (B9) possess the weak correlation with the new processes

(B5) with correlation values of .145 with a significant p-value of .003 that is also negligible. It

is also found that the average variance extracted value .862 of sub construct new revenue

models (B9) is greater than correlation square values of .002, .001, .002, .001, .021, .003, .006

and .002.

• The sub construct new cost structures (B10) possess no correlation with the sub constructs new

capabilities (B1), new technology (B2), new partnerships (B3), new processes (B4), new

processes (B5), new customers and markets (B6), new channels (B7) and new customer

relationships (B8) with the non-significant p values of .956, .965, .312, .091, .804, .053, .424


110

and .364 that are greater than .05. However, the new cost structures (B10) possess the weak

correlation with new revenue models (B9) with correlation values of .137 with significant p-

value of .004 that is also negligible. It is also found that the average variance extracted value

.855 of sub construct new cost structures (B10) is greater than correlation square values of

.000, .000, .002, .006, .001, .008, .001, .002 and .018.

Table 3.14. Summarizing the Reliability and Validity Iteration Outcome

Constructs Sub-Constructs Initial

Items

Items

removed

in EFA

Items

removed

in CFA

Total

items

removed

Items

retained in

Final scale

Innovation

Capabilities

Sensing user needs 3 0 0 0 3

Sensing technological options 3 0 0 0 3 Conceptualization 3 1 0 1 2 Coproducing and Orchestrating 3 0 0 0 3 Scaling and Stretching 3 0 1 1 2

15 1 1 2 13

Innovation

Success

Short term success 5 1 0 1 4

Long term success 5 0 1 1 4

Indirect success 3 0 0 0 3

13 1 1 2 11

Management

Entrepreneurial

Orientation

Ready to innovate 3 0 0 0 3

Aggressively competitiveness 2 0 0 0 2

Market Proactiveness 3 0 0 0 3

Risk taking 3 0 0 0 3

11 0 0 0 11

Employee

Resistance

Routine seeking 4 0 1 1 3

Emotional Reaction 5 1 1 2 3

Short term focus 3 0 0 0 3

Cognitive Rigidity 3 0 0 0 3

15 1 2 3 12

Business

Model

Innovation

New capabilities 3 0 0 0 3

New technology 3 0 0 0 3

New partnerships 4 1 0 1 3

New processes 3 0 0 0 3

New offerings 3 0 0 0 3

New customer and markets 3 0 0 0 3

New channels 3 1 0 1 2

New customer relationships 3 1 0 1 2

New revenue models 4 0 0 0 4

New cost structures 4 0 0 0 4

33 3 0 3 30

Demographics 3 -- -- 0 3

Total Items 90 6 4 10 80


111

Thus, these results satisfy the basic assumption of discriminate validity for the construct of

business model innovation. Table 3.14 summarizes the overall results of these reliability and

validity iteration process for all the five constructs.

It is found that the total ten items (that are 8, 14, 20, 23, 42, 47, 48, 61, 75 and 79) qualify

to be eliminated due to cross loading in EFA, poor factor loadings in EFA and poor item reliability

in CFA. Thus, it reduces the earlier ninety (90) items research instrument to the eighty (80) items

research instrument for the measurement of the five constructs of this research study namely

innovation capabilities, innovation success, management entrepreneurial orientation, employee

resistance and business model innovation. It can also be claimed that this 80-item final version of

iterative purified scale carries the adequate construct validity, convergent validity, sufficient

construct reliability, adequate discriminate validity and holds the adequate performance (i.e model

fit indices) for measurement of five constructs. It is pertinent to mention here that some researchers

Chamsuk, Fongsuwan and Takala (2017), Narcizo, Canen and Tammela (2017) comprehend the

need to empirically validate the operationalization of innovation capabilities with a core objective

to bring uniformity in the operationalization of construct globally. Similarly, some other

researchers Foss and Saebi (2018); Foss and Saebi (2017); Clauss (2017); Scheider and Spieth

(2014) indicated that the majority of the previous researches on the concept of business model

innovation have opted for qualitative approach with no or less empirical analysis (Gap-1 of this

research work). This previously indicate the need to empirically test and validate the dimensions

of business model innovation (Foss & Saebi, 2018, 2017; Hossain, 2018; Bashir & Verma, 2019;

Clauss, 2017; Scheider & Spieth, 2014).

Thus, the detailed reliability and validity iterative process for testing the psychometric

properties of the above five constructs (namely innovation capabilities, innovation success,

entrepreneurial orientation, employee resistance and business model innovation) attempts to

successfully address the research objective one of this research work by further contributing to this

research gap.

3.6. Statistical Techniques

The collected data is analyzed by using the SPSS (version 20.0) and AMOS (version 22.0)

software. The demographic analysis of the respondents is checked to get deep insight into the


112

psychometric attributes of the sample. The descriptive statistics including means and standard

deviation are calculated for each construct of the study. In order to check the psychometric

characteristics of the research instrument, the validity analysis including construct validity,

discriminate validity and reliability analysis is checked through the statistical techniques of

exploratory factor analysis, Cronbach alpha value, confirmatory factor analysis, and Pearson

correlation. Before hypotheses testing, the basic assumptions of regressions are checked including

linearity, multicollinearity and data normality. Hayes (2017) regression-based process approach,

statistical technique are used for the testing of hypotheses and proposed theoretical model of this

research work. Finally, the overall model fitness measures are calculated through structural

equation modeling.


This chapter has discussed in detail the formation of the theoretical framework and theoretical

underpinnings along with the development of ten testable research hypotheses. The hypothesized

theoretical framework of this research study contains five constructs. The direct effect of

innovation capabilities (independent variable) on business model innovation (dependent variable)

has been hypothesized. The mediation role of service innovation success in between the direct

effect of the independent and dependent variable is also hypothesized. In addition to this, the

moderating effect of employee resistance (moderator 1) on the relationship of innovation

capabilities - service innovation success and the innovation capabilities – business model

innovation is also proposed. Furthermore, the moderating effect of management entrepreneurial

orientation (moderator 2) is also hypothesized on the direct and indirect effects of innovation

capabilities (independent variable) and business model innovation (dependent variable). Ten

testable research hypotheses are developed. The operational definitions of the research constructs

are also stated. Finally, the development of a research instrument for the collection of data from

target respondents and methodology of research survey are discussed. This chapter has discussed

in depth the methodology adopted to address the six posed research questions of this research

work. Quantitative research design with an empirical research approach has been used. The

research survey has been as a research strategy and the research questionnaire has been used as the

tool for the collection of data. The research instrument has been developed by adopted the items

from the previous existing researches. The research questionnaires of this research work constitute

the total ninety (90) items. The population constitutes the cellular companies of Pakistan. The

population frame consists of 1274 approximate senior chiefs, departmental heads and middle


113

managers from four cellular companies (namely Mobilink, Warid, Zong, and Telenor). Using

Krejice and Morgan (1980) illustration for a finite population, 295 number of respondents were

required to ensure the generalizability of the results. Five hundred and fifty (550) participants are

picked from the population frame under the simple random sampling strategy. However, four

hundred and twenty-seven (427) completely filled questionnaires are received back with the

overall response rate of 77.63 percent. The validity and reliability of research measures are also

checked in light of Kouftero’s approach (1999). The construct validity is analyzed using the

statistical technique of exploratory factor analysis. The results of exploratory factor analysis show

that all the basic conditions of exploratory factor analysis are successfully met for the five

constructs. However, the total six items (that are 8, 20, 47, 61, 75 and 79) qualify to be eliminated

due to cross loading or poor factor loadings. Resultantly, it reduces the earlier ninety (90) items to

the eighty-four (84) items in research instrument. The construct reliability is checked through

Cronbach alpha value and it is found that all the five constructs and sub-constructs possess the

acceptable values ranging from .675 to .958. The convergent validity and item reliability of the

constructs are also checked through confirmatory factor analysis. The results reveal that the t-

value of all the items are significant with the values (greater than 2) ranging from 5.405 to 997. It

means that all these items are significantly related to their respective constructs. However, the item

reliability of the four items (ie. 14, 23, 42 and 48) are not found to be significant and therefore,

qualifies to be eliminated during this iterative process of confirmatory factor analysis. It

consequents the final version of a research instrument to comprise of 80 items at this stage. The

discriminate validity of all the constructs is also checked through correlation values of sub-

constructs and the comparison of squared correlation value with the calculated average variance

extracted (AVE) values. The results show that the sub-constructs of all the five constructs possess

weak or no correlation. The comparison of the squared correlation of sub-constructs with the

calculated average variance extracted (AVE) values are also found to be in acceptable ranges.

These results satisfy the basic criteria of discriminate validity. Thus, this 80-item final version of

iterative purified scale carries the adequate construct validity, convergent validity, sufficient

construct reliability, adequate discriminate validity and holds the adequate performance (i.e. model

fit indices) for measurement of five constructs. This further shows the eligibility of the data for

hypothesis testing. The collected data may be analyzed by different statistical techniques using the

SPSS (version 20.0) and AMOS (version 22.0) software.


114

CHAPTER 4

DATA ANALYSIS AND RESULTS

This chapter explains in detail the results of the statistical techniques applied to the collected data.

This section attempts to empirically answer the research questions of this research work and further

provides the empirical evidence for the actuality of the hypothesized relationships of constructs.

In this regard, the demographic analysis, descriptive analysis, correlation of research measures and

Hayes (2017) based moderation mediation analysis have been conducted in detail.

4.1. Demographic Characteristics

The results of the demographic analysis of the participants of the research survey are

discussed in table 4.1. The results revealed that 71.19 percent of the respondent with the frequency

of 304 were males and the remaining 28.81 percent were female. The results also showed that 3.98

percent of respondents were aged less than thirty years, 83.61 percent of the (357) respondents

were aged between 31 years - 40 years and the residual 53 respondents (12.41 percent) were aged

above than forty years. Furthermore, it was also found that 16.9 percent of respondents (71) were

graduate, 71.90 percent of respondents (302) were post-graduate qualified and the remaining 11.20

percent with the frequency of 47 were MS or MPhil or Doctorate or equivalent qualified.

Table 4.1. Demographic Analysis of Research Survey Participants

S # Demographics Classifications Frequency Percentage

Males 304 71.19

1 Gender Females 123 28.81

Total 427 100

2 Age

Less than 30 years 17 3.98

31 yrs. – 40 yrs. 357 83.61

Above than 40 yrs. 53 12.41

Total 427 100

3 Education

Graduation 71 16.90

Post-Graduation 302 71.90

MS or MPhil or Ph.D. and Equivalent 47 11.20

Total 427 100

4.2. Descriptive Analysis

The results of the descriptive analysis are shown in table 4.2. The construct innovation

capabilities, service innovation success, entrepreneurial orientation are measured by 7-point Likert


115

scale. Whereas the employee resistance is measured by 6-point Likert scale and business model

innovation is measured by 5-point Likert scale. The results show that the average mean score of

innovation capabilities, service innovation success, and entrepreneurial orientation falls under the

category of “Agree” of seven-point Likert scale with the values of 5.0334, 5.0423 and 5.1370

respectively. It was also found that the mean score of employee resistance falls under the category

of “disagree” of six-point Likert scale with the value of 2.1734. Similarly, the mean score of

business model innovation falls in the category of “agree” of five-point Likert scale with the value

of 4.1647.

Table 4.2. Descriptive Analysis among Study Variables

Variables Mean S.D Minimum Maximum

Innovation capabilities 5.0334 .757 2.86 7.00

Service innovation success 5.0423 .615 3.29 6.79

Entrepreneurial orientation 5.1370 .796 2.85 7.0

Employee resistance 2.1734 .659 1.0 4.06

Business model innovation 4.1647 .510 2.0 4.50

4.3. Correlation Analysis among Study Variables

Formal correlation is checked among the study variables with an objective to check the

nature and magnitude of the relationship among variables once before testing the research

hypotheses. Table 4.3 explains the results of correlation analysis, mean and standard deviations of

study variables. The results show that the innovation capabilities are positive correlated with

service innovation success (r=.584, p =.000) and business model innovation (r = .598, p = .000).

Similarly, it is also found that the service innovation success is strongly positive correlated with

entrepreneurial orientation (r = .577; p = .000) and business model innovation (r = .568; p = .000).

However, the service innovation success is negatively strongly correlated with the employee

resistance (r = -.511; p = .000). Table 4.3 also shows that the innovation capabilities possess the

weak correlation with the entrepreneurial orientation (r = .119; p = .000) and negative weak

correlation with employee resistance (r = -.109; p = .000).


116

Table 4.3. Correlation Analysis among Study Variables

Variables IC IS EO ER BMI

IC Correlation

Sig(2tailed)

1

IS Correlation

Sig(2tailed)

.584

.000

1

EO Correlation

Sig(2tailed)

.119

.000

.577

.000

1

ER Correlation

Sig(2tailed)

-.109

.000

-.511

.000

-.157

.001

1

BMI Correlation

Sig(2tailed)

.598

.000

.568

.000

.694

.000

-.652

.002

1

4.4. Hypotheses Testing - Regression based Conditional Process Analysis

The hypothesized research model of this study consists of five research variables. It

portrays that the innovation capabilities (independent variable) not only possess the direct effect

on the business model innovation (dependent variable) but it also holds the indirect effect on

business model innovation through the mediation effect of innovation success. Furthermore, the

hypothesized research model of this study also illustrates that this indirect effect is further

moderated by the two variables of employee resistance and management entrepreneurial

orientation. This indicates that the effect of innovation capabilities (independent variable) on

business model innovation (dependent variable) is conditional in nature that is dependent upon the

magnitude and nature of the influence of these mediating and moderating variables.

It is pertinent to mention here that the structural equation modeling is considered as the

most widely used statistical technique for the testing of latent and observed structural relationships.

It is also believed by some researchers that the structural equation modeling is one of those

statistical techniques that constitutes the integrated characteristics of other statistical methods such

as MANOVA, regression, correlation and factor analysis etc. (Nachtigall, Kroehne, Funke &

Steyer, 2003; Eid, 2000). However, the recent researches claim that the structural equation

modeling does not examine the mediation effects that further leads to the erroneous conclusions


117

(Hair et al., 2012, 2013; Hair, Sarstedt, Hopkin & Kuppelwieser, 2014). Hair et al., (2014) argue that

there is a need for future statistical researches to come up with statistical solutions of moderated

mediation and mediated moderation analyses and this statistical research gap was later on filled by

Hayes (2017, 2018) regression based conditional process analysis. It is pertinent to mention here that

the hypothesized theoretical framework of this research work is dually moderated mediation research

model. Therefore, this research work has used the Hayes (2017) regression based conditional

process analysis for the testing of hypothesized relationships. The testing of all the proposed

hypotheses of this research work are embarked in following manner;

• Addressing Gap 2 - Testing the effect of X on Y. In this stage, the simple regression is

conducted to check the effect of service innovation capabilities (X) on business model

innovation (Y). This stage empirically tests the proposed hypotheses 1 of this study.

• Addressing Gap 3 - Testing the mediating effect of M on the relationship of X on Y. In

this stage, the simple mediation analysis (Hayes model 4 process template) is conducted to

check the mediation effect of service innovation success (M) on innovation capabilities (X)

and business model innovation (Y) relationship. This stage empirically tests the proposed

hypotheses 2, 3 and 4 of this study.

• Addressing Gap 4 – Testing the moderation effect of W. This stage is further categorized

into two sub-stages for further elaboration. At first instance, the moderation effect of

entrepreneurial orientation (W) is checked on the effect of innovation capabilities (X) and

service innovation success (M). This sub-stage empirically tests the proposed hypothesis 5 of

this study. At the second instance, the moderation effect of entrepreneurial orientation (W) is

checked on the direct effect of innovation capabilities (X) and business model innovation (Y)

that empirically tests the proposed hypothesis 6 of this research work.

• Addressing Gap 5 – Testing the moderation effect of Z. Similarly, this stage is also further

categorized into two sub-stages for further elaboration. At first instance, the moderation effect

of employee resistance (Z) is checked on the effect of innovation capabilities (X) and service

innovation success (M). This sub-stage empirically tests the proposed hypothesis 7 of this

study. At the second instance, the moderation effect of employee resistance (Z) is checked on

the direct effect of innovation capabilities (X) and business model innovation (Y) that

empirically tests the proposed hypothesis 8 of this research work.


118

• Addressing Gap 6 – Testing the moderation effect of W and Z on the relationship of X

on Y with putative mediator held constant. In this stage, the moderation effect of both

entrepreneurial orientation (W) and employee resistance (Z) simultaneously checked on the

direct relationship of innovation capabilities (X) and business model innovation (Y) with

considering the service innovation success (M) being held constant. This stage empirically

tests the proposed hypothesis 9 of this research work.

• Addressing Gap 6 – Testing the moderation effect of W and Z on relationship of X on Y

through mediation effect of M. In this final stage, all the above mediation and moderation

indirect effects (of stage one to stage four) are combined and simultaneously checked on the

relationship of innovation capabilities (X) and business model innovation (Y). This stage

empirically tests the hypothesized theoretical model of this research study in the form of

proposed hypothesis 10 of this research work.

Before proceeding for these step-wise hypotheses testing phenomenon, the assumptions of

regression analysis are also needed to be checked as under;

4.4.1. Assumptions of Regression analysis.

Regression Analysis is one of powerful parametric statistical test that requires some basic

assumptions to be met first. There are three basic assumptions of regression analysis that are a

normal distribution of data, linearity and multicollinearity.

4.4.1.1. Data normality.

Normal distribution of data is considered as the foremost basic assumption of regression

analysis. It can be checked through the statistical test of the Kolmogorov-Smirnov test and the

values of skewness, kurtosis (Hair et al., 2009). If the K-S test seems to significant (that is p-value

less than .05) then it refers to the data as “non-normal”. Similarly, if K-S tests are found to be non-

significant (that is p-value greater than .05) then the data is characterized as “normal” (Hair et al.,

2009). Skewness refers to the symmetry of data distribution and the normal data carries the

perfectly symmetric distribution (Hair et al., 2009). Data is termed as positively skewed if the

majority of scores are clustered at the left side with their tails extending towards the right side

(Hair et al., 2009). On the other hand, data is termed as negatively skewed if the majority of scores

are found to be clustered at right sight with their extended tails at left side. Kurtosis refers to the


119

weakness of the data distribution and the data is termed “normal” if its distribution is found to bell-

shaped (no too flat nor too peaked). The data is termed as normal if its value of skewness and

kurtosis falls in acceptable range of +1 and -1 (Hair et al., 2009).

Table 4.4. Results of Data Normality

Variables K-S Normality Test

Skewness Kurtosis Statistic Df Sig.

Innovation capabilities .036 427 .199 .054 .062

Service Innovation success .042 427 .075 .062 .118

Entrepreneurial orientation .036 427 .200 .029 .226

Employee resistance .034 427 .150 .023 .190

Business model innovation .033 427 .062 . 018 .169

Table 4.4 depicts the results of data normality of study variables. It is found that the sample

data of five study variables of this research work is a factual representation of the expected data

distribution with the non-significant p-values of .199, .075, .200, .150 and .062 > .05. The value

of skewness and kurtosis of the study variables are also found to lie within the range of .018 - .226

(that falls in an acceptable range of +1 and -1). Thus, these results imitate that the basic assumption

of data normality hence triumphs.

4.4.1.2. Linearity of residuals.

The linearity of residuals is another crucial assumption of regression analysis. It basically

denotes that the standardized residuals and the values of dependent variable are directly

proportional to each other with a defined linear pattern (Hair et al., 2009). A scatterplot is graphed

in which the values of dependent variable are marked at vertical y-axis and the values of

standardized residuals are plotted at horizontal x-axis. If the produced scatterplot follows a linear

pattern (not curvilinear), then it is believed that the assumption of linearity of residuals is truly met

(Hair et al., 2009). Figure 4.1 shows the scatterplot graph among the values of dependent variable

(business model innovation) at vertical y-axis and standardized residuals at horizontal x-axis. It

clearly shows the linear relationship and no curve can be seen among the values of dependent

variable and standardized residuals. Thus, the assumption of linearity of residuals is met.


120

Figure 4.1. Scatterplot depicting Linearity of Residuals

4.4.1.3. Multicollinearity.

Multicollinearity is another critical assumption of regression analysis. Multicollinearity is

considered to occur when any one of the explanatory variable (independent or moderator) possess

a strong linear relationship with others with strong accuracy of prediction (Hair et al., 2009).

Perfect multicollinearity or high multicollinearity is the violation of assumptions of regression

analysis. Multicollinearity is checked by witnessing the values of ‘Tolerance’ or ‘Variance

inflation factor’ (VIF) of each study variable (Hair et al., 2009). Tolerance represents the

variability of one explanatory variable that is not explained by the other explanatory variables.

Whereas, the variance inflation factor (VIF) is the inverse of tolerance. It is believed that the

tolerance value less than 0.10 and variance inflation factor value of 10 or above indicates the issue

of multicollinearity (Hair et al., 2009). Table 4.5 depicts the results of multicollinearity for all the

study variables of this research work. The results show that the tolerance value of all study

variables is greater than 0.10 with the values .649, .561, .767 and .841 that is in acceptable range.

Similarly, it is also found that variance inflation factor values of all study variables are below 10

with the values of 1.540, 1.782, 1.303 and 1.063. Thus, these results reveal that there exists no

issue of multicollinearity in data.


121

Table 4.5. Multicollinearity Statistics of Study Variables

Variables Tolerance VIF

Innovation capabilities .649 1.540

Service Innovation success .561 1.782

Entrepreneurial orientation .767 1.303

Employee resistance .841 1.063

Note. Dependent variable = business model innovation

4.4.2. Addressing Gap two - Testing the effect of ‘X’ on ‘Y’ (H-1)

Table 4.6 illustrates the effect of innovation capabilities (IV) on business model innovation

(DV). It showed that only 35.76% of variance on business model innovation is explained by

innovation capabilities with positive coefficient effect of .2813 and p-value of .001 that is less than

.05. Thus, these results reflects that there exists a positive significant effect of innovation

capabilities (independent variable) on business model innovation (dependent variable). Hence, it

testifies the hypothesis one (H1: Innovation capabilities may possess positive influence on

business model innovation) as correct.

Table 4.6. Regressing IV against DV in Simple Linear Regression

Variable Coeff Se T P

Constant 2.3658 .1511

Innovation capabilities .2813 .0438 6.4267 .000

R2 = 0.3576, F (1, 425) = 41.302, p = 0.000

4.4.3. Addressing Gap Three - Testing the mediation effect of ‘M’ on relationship of

‘X’ on ‘Y’ (H2-H4)

The mediation effect of service innovation success on the relationship of innovation

capabilities (X) and business model innovation (Y) is checked through the regression-based

process macro of Hayes (2017) using model 4.


122

Table 4.7 portrays the mediation model coefficient results of study variables. The results

show that 34.12 % of variance in service innovation success can be explained by innovation

capabilities with p-value of .000 that is less than .000. It was also found that innovation capabilities

positively affects the service innovation success with the standardized coefficient of α = .4936,

with significant t-value of 14.83 greater than 2 and p-value of .000 < .05. Hence, it reflects that

hypothesis two (H2: Innovation capabilities may possess positive influence on service innovation

success) stands to be valid.

It is also found that 42.01 % of variance in business model innovation can be explained by

both innovation capabilities and service innovation success. The results also show that service

innovation success (M) possess the significant positive effect of coefficient β = 0.4998 on business

model innovation (Y) with t-value of 8.455 > 2 and p-value of .000 < .05. Thus, it proves that

hypothesis three (H3: Service innovation success may possess positive influence on business

model innovation) stands to be correct.

Table 4.7 Mediation Model Coefficients of Study Variables

Precursors

M

(Innovation success)

Y

(Business model innovation)

Coeff S.E T P Coeff S.E T P

Constant i1 1.6936 .1148 14.74 .000 i2 1.519 .1721 8.829 .000

Innovation capabilities (X) a .4936 .0333 14.83 .000 c' .0346 .0499 .6932 .488

Innovation success(M) -- -- -- -- -- β .4998 .0591 8.455 .000

R2 = 0.3412,

F (1, 425) = 220.12

p = 0.000

R2 = 0.4201,

F (2, 424) = 59.82

p = 0.000

Figure 4.2. Statistical Diagram of Table 4.7

Innovation success

(M)

β = .4998

α = .4936

R2 = 0.4201,

p = 0.000

Innovation capabilities

(X)

c' = .0346

Business Model innovation

(Y)


123

In addition, table 4.8 depicts the results of total effect, direct effect and indirect effect of

mediation analysis. From table 4.7, multiplying the coefficient values of α and β yields (0.4936)

(0.4998) = 0.2467 also mentioned in table 4.8 as indirect effect. This indirect effect of 0.2467

means that two individuals who differ by one unit in their innovation capabilities are estimated to

differ by 0.2467 units in bringing business model innovation as a outcome of the propensity for

those individuals with relatively more innovation capabilities to attain more innovation success

(because the sign of α is positive), which in results brings the more business model innovation

(because the direction of β is positive).

Summing the direct effect and indirect effect c = c' + ab = (0.0346 + 0.2467) = .2813 yields

the total effect of innovation capabilities on business model innovation as shown in table 5.22 as

well as in table 4.7. Table 4.7 and 4.8 both depicts the direct effect of innovation capabilities as c'

= .0346. This direct effect reflects the estimated difference in business model innovation between

the two individuals who experience the same level of innovation success but they differ by one

unit in their experience of innovation capabilities. This direct effect of .0346 is positive in nature.

It refers that the more innovation capabilities would yield the equal service innovation success that

would achieve the .0346 unit more business model innovation. It is pertinent to mention here, that

this direct effect is not statistically significant with the p-value of .488 > .05 and t-value of .693 <

2. Hence, it proves that there exists a positive mediation effect of service innovation success with

the magnitude of .0346 among the relationship of innovation capabilities (X) and business model

innovation (Y). Hence, hypothesis four (H4: Service innovation success mediates the relationship

between innovation capabilities and business model innovation) also stands to be correct.

Table 4.8. Total Effect, Direct and Indirect Model of Mediation Analysis

Total Effect of X on Y Direct Effect of X on Y Indirect Effect of X on Y

Effect Se T P

Effect Se t P

Effect Boot SE

.2813 .043 6.42 .000 .0346 .049 .693 .488 .2467 .0323

4.4.4. Addressing Gap Four -Testing moderation effect of employee resistance ‘W’.

4.4.4.1. Testing the moderation effect of ‘W’ on relationship of ‘X’ on ‘Y’ (H-5).

Table 4.9 depicts the results of the moderation effect of employee resistance on the direct

relationship of innovation capabilities (X) and business model innovation (Y). The results show

that 31.34 % of variance on business model innovation (Y) can be explained by innovation


124

capabilities (X) and the moderator employee resistance (W) with p-value of .000 that is less than

.05. The results also reflect that the effect of employee resistance (W) is negatively significant on

the business model innovation with the t-value of -4.42 that is greater than 2; coefficient of β = -

.445 and significant p-value of .000. Furthermore, it is also found that interaction term “Int_1”

(multiple of innovation capabilities and employee resistance) possess the significant effect of .3723

with t-value of 4.218 > 2 and the p-value of .01 less than 0.05. This means that the moderation

effect of employee resistance is significantly negatively affecting the relationship between

innovation capabilities and business model innovation. In addition, it is also found that this

interaction effect of innovation capabilities and employee resistance have caused the decrease of

3.65 percent of variance on business model innovation explained by innovation capabilities with

the significant p-value of .000 < .05.

Table 4.9. Model Coefficients for Moderation Effect of Employee Resistance on X and Y

Precursor

Y

(Business Model Innovation)

Coeff S.E t P LLCI ULCI

Constant 7.117 1.07 6.61 .000 5.003 9.231

Employee Resistance (W) -.445 .3269 -4.42 .000 -2.0877 -.802

Innovation Capabilities (X) .9438 .2894 -3.26 .001 -1.512 -.375

Interaction_1 -.3723 .0882 4.218 .000 -.1988 -.545

R2 = 0.3134, F (3, 423) = 21.71; p = 0.000

R-Square decrease due to interaction = -.0365; F (1, 423) = 17.79; p = .000


R2 = 0.3134,

p = 0.000

.9438

-.445

Employee Resistance

(W)


(X)

Business Model Innovation

(Y)

Int_1 (XW)

-.3723


125

Table 4.10. Conditional Effect of X on Y at values of Employee Resistance (W)

Employee

Resistance (W)

Effect Se t P LLCI ULCI

Weak / Low .0416 .0683 .6095 .542 -.0926 .1759

Moderate .2332 .0443 5.26 .000 .1461 .3203

Strong / High .4247 .0582 7.29 .000 .3103 .5391

Table 4.10 depicts at which condition of employee resistance (W) does the interaction

effect (of innovation capabilities and employee resistance) significant on the relationship of

innovation capabilities (X) and business model innovation (Y). The results show that at lower

employee resistance the moderation effect is not significant on the effect of innovation capabilities

(X) on business model innovation (Y) with the t-value .6095 < 2 and p-value .542 > .05. However,

it is also found that at moderate and high level of employee resistance, the moderation effect of

.2332, .4247 are significant on the effect of innovation capabilities (X) on business model

innovation (Y) with the t-values 5.26, 7.29 and p-values of .000, .000 respectively. This conditional

moderation effect of employee resistance on X and Y relationship can also be view in figure 4.4.

Figure 4.4. Moderating effect of W on relationship of X and Y


126

It depicts that the individuals with high resistance to change tend to contribute less towards

the business model innovation. The graph also reflects that the individuals who feels lower level

of resistance to change and carries the higher innovation capabilities would tend to perform higher

towards business model innovation. However, the individuals who feels moderate level of

resistance to change and carries the higher innovation capabilities would tend to perform little less

than the previous individual who feels the lower resistance to change. This effect continues to

occur until the innovation capabilities are at lower stage.

Hence, these results reflect that hypothesis five (H5: Employee resistance to change

negatively moderates the relationship between innovation capabilities and business model

innovation in such a way that innovation capabilities – business model innovation relationship are

weaker with higher employee resistance and vice versa) is found to be correct.

4.4.4.2. Testing the moderation effect of ‘W’ on relationship of ‘X’ and ‘M’(H-6).

This step includes the testing of moderation effect of employee resistance ‘W’ on the

conditional effect of innovation capabilities (X) on mediator service innovation success (M). The

moderation effect is checked on the conditional effect of innovation capabilities (X) on business

model innovation (Y) through service innovation success (M) as depicted in figure 4.5. Hayes

(2017) has termed it as mediated moderation. Edwards and Lambert (2007) define such

measurement models as “first stage moderation”.

Table 4.11 shows the results of model coefficients for the moderation effect of employee

resistance on conditional effect of innovation capabilities (X) on business model innovation (Y)

through service innovation success (M). Table 4.11 depicts that the effect of employee resistance

(W) is (-1.036) negatively significant on the mediator service innovation success (M) with the t-

value of -4.16 > 2 and significant p-value of .000 < .05. It is also found that interaction term

“Interaction_1” (multiple of innovation capabilities and employee resistance) also possess the

significant effect of .2636 with t-value of 3.92 > 2 and the p-value of .01 less than 0.05. This means

that the moderation effect of employee resistance is significantly negatively affecting the

relationship between innovation capabilities and service innovation.


127

Table 4.11. Model Coefficients for Moderation Effect of Employee Resistance on X and M

Precursors

M


Y


Coeff Se T p Coeff Se T P

Constant 5.112 .8184 6.24 .000 1.519 .1721 8.829 .000

Innovation capabilities (X) -1.377 .2202 6.22 .000 .0346 .0499 .6932 .488

Employee Resistance (W) -1.036 .2487 -4.16 .000 -- -- -- --

Innovation success(M) -- -- -- -- .4998 .0591 8.455 .000

Interaction_1 .2636 .067 3.92 .001 -- -- -- --

R2 = 0.3722,

F (3, 423) = 83.609

p = 0.000

Direct effect of X on Y: Effect = .0346, t = .6932, p = .4886

Index of moderated mediation = .1318

Furthermore, table 4.11 also reflects that the mediation effect of service innovation success

(M) significantly exists between the innovation capabilities (X) and business model innovation

(Y) under the influence the employee resistance (W). It can be evident from the non-significant

direct effect of .0346 with the non-significant p-value of .488 (that is greater than .05) and t-value

of .6932 (that is less than acceptable 2). Thus, this evidences that the moderation effect of

employee resistance negatively moderates the mediation effect of service innovation success on

the conditional effect of innovation capabilities (X) on business model innovation (Y). And the

index of this moderated mediation is found to be .1318.


-.3772

-

1.03

6

.0346

Innovation success (M)

Employee Resistance (W)


(X)


(Y)

R2 = 0.3722,

p = 0.000

.4998

.2636

Interaction 1 (XW)


128

Thus, these results evidence that the hypothesis six of this research study (H6: Employee

resistance to change negatively moderates the relationship between innovation capabilities and

service innovation success) also stands to be valid.

4.4.5. Addressing Gap Five -Testing the moderation effect of ‘Z’.

4.4.5.1. Testing the moderation effect of ‘Z’ on relationship of ‘X’ on ‘Y’ (H-7).

Table 4.12 depicts the results of the moderation effect of management entrepreneurial

orientation on the direct relationship of innovation capabilities (X) and business model innovation

(Y). The results show that 68.89 % of variance on business model innovation (Y) can be explained

by innovation capabilities (X) and the moderator management entrepreneurial orientation (Z) with

p-value of .000 that is less than .05. The results also reflect that the effect of management

entrepreneurial orientation (Z) is positively significant on the business model innovation with the

t-value of 19.15 that is greater than 2; coefficient of β = .7965 and significant p-value of .000.

Table 4.12. Model Coefficients for Moderation Effect of Entrepreneurial Orientation on X and Y

Precursor

Y


Coeff Se t P LLCI ULCI

Constant .7506 .1384 5.42 .000 .4785 1.022

Entrepreneurial orientation

(Z) .7965 .041 19.15 .000 .7148 .8782

Innovation Capabilities (X) .1986 .041 4.95 .000 .2774 .1198

Interaction_1 .053 .011 4.46 .000 .0298 .0767

R2 = 0.6889, F (3, 423) = 1256.2; p = 0.000

R-Square increase due to interaction = .1005; F (1, 423) = 19.96; p = .000

Furthermore, it is also found that interaction term “Int_1” (multiple of innovation

capabilities and entrepreneurial orientation) possess the significant effect of .053 with t-value of

4.46 > 2 and the p-value of .000 less than 0.05. This means that the moderation effect of

entrepreneurial orientation is significantly positively effecting the relationship between innovation

capabilities and business model innovation. In addition, it is also found that this interaction effect

of innovation capabilities and entrepreneurial orientation have caused the increase of 10.05 percent


129

of variance on business model innovation explained by innovation capabilities with a significant

p-value of .000 < .05.


Table 4.13 depicts at which condition of entrepreneurial orientation (Z) does the interaction

effect (of innovation capabilities and entrepreneurial orientation) significant on the relationship of

innovation capabilities (X) and business model innovation (Y). The results show that at lower

entrepreneurial orientation the moderation effect is not significant on the effect of innovation

capabilities (X) on business model innovation (Y) with the t-value .1487 < 2 and p-value .881 >

.05. However, it is also found that at moderate and high level of entrepreneurial orientation, the

moderation effect of .0215, .0440 are significant on the effect of innovation capabilities (X) on

business model innovation (Y) with the t-values 4.19, 6.05 and p-values of .000, .000 respectively.

This conditional moderation effect of entrepreneurial orientation on X and Y relationship

can also be view in figure 4.7. It depicts that the individuals with higher entrepreneurial orientation

who carries the higher innovation capabilities would contribute higher in business model

innovation. The individuals who feel a a moderate level of entrepreneurial orientation and

simultaneously possessing the higher innovative capabilities would contribute less towards

business model innovation than that of previous individuals with higher entrepreneurial

orientation. The graph also depicts that the individuals with lower entrepreneurial orientation

carrying the higher innovative capabilities would contribute little less towards the business model

innovation than that of previous individuals with moderate and higher entrepreneurial orientation.

This effect continue to occur until the innovation capabilities are at a lower level.

R2 = 0.6889,

p = 0.000

.1986

.1986


(Z)


(X)


(Y)

Int_1 (XZ)

.053


130

Table 4.13. Conditional effect of X on Y at values of Entrepreneurial Orientation (Z)

Entrepreneurial

orientation (Z)

Effect Se T p LLCI ULCI

Weak / Low .0011 .007 .1487 .881 .0129 .0150

Moderate .0215 .005 4.19 .000 .0315 .0114

Strong / High .0440 .007 6.05 .000 .0582 .0297

Figure 4.7. Moderating effect of Z on relationship of X and Y

Hence, these results reflect that hypothesis seven (H7: Management entrepreneurial

orientation positively moderates the relationship between innovation capabilities and service

innovation success in such a way that the relationship is stronger with increased entrepreneurial

orientation) is found to be correct.

4.4.5.2. Testing the moderation effect of ‘Z’ on the relationship of ‘X’ and ‘M’(H-8).


131

This step includes the testing of moderation effect of entrepreneurial orientation ‘Z’ on the

conditional effect of innovation capabilities (X) on mediator service innovation success (M). The

moderation effect is checked on the conditional effect of innovation capabilities (X) on business

model innovation (Y) through service innovation success (M) as depicted in figure 4.8.

Table 4.14. Model Coefficients for Moderation Effect of Entrepreneurial Orientation on X and M

Precursors

M


Y


Coeff Se t P Coeff Se T P

Constant 2.765 .8788 3.14 .001 1.519 .1721 8.829 .000

Innovation capabilities (X) .6091 .2546 2.03 .000 .0346 .0499 .6932 .488


(Z) .2336 .0264 8.84 .000 -- -- -- --


Interaction_1 .1499 .075 2.00 .048 -- -- -- --

R2 = 0.6635,

F (3, 423) = 110.8

p = 0.000

Direct effect of X on Y: Effect = .0346, t = .6932, p = .4886

Index of moderated mediation = .0746


Table 4.14 shows the results of model coefficients for the moderation effect of

entrepreneurial orientation on the conditional effect of innovation capabilities (X) on business

model innovation (Y) through service innovation success (M). Table 4.14 depicts that the effect of

entrepreneurial orientation (Z) is (.2336) positively significant on the mediator service innovation

success (M) with the t-value of 8.84 > 2 and a significant p-value of .000 < .05. It is also found

.6091

.233

6

.0346


Entrepreneurial orientation (Z)


(X)


(Y)

R2 = 0.6635, p = 0.000

.4998

.1499

Interaction_1 (XZ)


132

that interaction term “Interaction_1” (multiple of innovation capabilities and entrepreneurial

orientation) also possess the significant effect of .1499 with t-value of 2 and the p-value of .048

less than 0.05. This means that the moderation effect of entrepreneurial orientation is significantly

positively affecting the relationship between innovation capabilities and service innovation.

Furthermore, table 4.14 also reflects that the mediation effect of service innovation success

(M) significantly exists between the innovation capabilities (X) and business model innovation

(Y) under the influence the entrepreneurial orientation (Z). It can be evident from the non-

significant direct effect of .3446 with the non-significant p-value of .4886 (that is greater than .05)

and t-value of .6932 (that is less than acceptable 2). Thus, this evidences that the moderation effect

of entrepreneurial orientation positively moderates the mediation effect of service innovation

success on the conditional effect of innovation capabilities (X) on business model innovation (Y).

And the index of this moderated mediation is found to be .0746. Thus, these results evidence that

the hypothesis eight of this research study (H8: Management entrepreneurial orientation moderates

the direct relationship of innovation capabilities and business model innovation) also stands to be

valid

4.4.6. Addressing Gap Six – Antecedents of Business Model Innovation

4.4.6.1. Testing the dual moderation effect of ‘W’ and ‘Z’ on relationship of ‘X’ on ‘Y’

with putative mediator held constant (H-9).

To testify the hypothesis nine, moderation effect of both moderators employee resistance

(W) and entrepreneurial orientation (Z) are checked with putative mediator service innovation

success considered to be held constant. Table 4.15 shows the results of double moderation analysis

on conditional effect of innovation capabilities (X) on business model innovation (Y).

The results show that 79.94 % of variance on business model innovation can be explained

by one independent innovation capabilities (X) and the two moderators employee resistance (W)

and the entrepreneurial orientation (Z) with the p-value .001 that is less than acceptable .05. The

results also reflect that the employee resistance (W) possess the significant negative effect of -

.5066 at the conditional effect of innovation capabilities (X) on business model innovation (Y)

with the service innovation success (M) held constant with the p-value .001; t-value of 12.35 > 2.

It is also found that the entrepreneurial orientation (Z) also carries the significant positive effect of


133

.8201 at the conditional effect of innovation capabilities (X) on business model innovation (Y)

with the p-value .001; t-value of 17.51 > 2. Furthermore, it is also found that the interaction term

“Int_1” (that is the product of innovation capabilities (X) and employee resistance (W) has also

found to possess the significant effect of .1059 with the p-value of .000 and t-value of 9.45 > 2.

Similarly, it is also found that the interaction term “Int_2” (that is the product of innovation

capabilities (X) and entrepreneurial orientation (Z) has also found to possess the significant effect

of .0469 with the p-value of .000 and t-value of 3.53 > 2.

Table 4.15. Moderation Effects of W and Z with Putative Mediator Held Constant


Antecedent

Y


Coeff. SE T P LLCI ULCI

Constant .4916 .2473 1.987 .067 .0054 .9777

Employee Resistance (W) -.5066 .0418 12.35 .000 -.0257 -.0138

Entrepreneurial orientation (Z) .8201 .0468 17.51 .000 .7281 .9121

Innovation capabilities (X) .2169 .0176 12.32 .000 .0061 .2598

Int_1 (WX) -.1059 .0112 9.45 .000 .0061 .0379

Int_2 (ZX) .0469 .0133 3.53 .004 .0209 .0730

R2 = 0.79.90, F (5, 421) = 7544.403, p = 0.000

R-Square increase due to interaction term:

Int_1 R2 change = -.0174; F(1, 421) = 20.153; p = .0000

Int_2 R2 change = .0212 ; F(1, 421) = 20.527; p = .0004

Both = .0137 ; F(1, 421) = 19.134; p = .0000

constant

-

.50666

.2169

(M) Held Constant

Employee Resistance

(W)


(X)


(Y)

R2 = 0.79.90,

p = 0.000

constant .8201


(Z)


134

Table 4.15 also reflects that the interaction effect of innovation capabilities and employee

resistance causes an overall decrease of 1.74 percent of the variance in business model innovation

with the significant p-value of .000 < .05. Whereas, it also refers that the interaction effect of

innovation capabilities and entrepreneurial orientation causes the overall increase of 2.12 percent

of the variance in business model innovation with the significant p-value of .000 < .05. The total

effect of this double moderation has caused the 1.37 percent of variance on business model

innovation.

Table 4.16 depicts at which condition of both employee resistance (W) and entrepreneurial

orientation (Z) do their interaction effects significant on the relationship of innovation capabilities

(X) and business model innovation (Y). The results show that at conditions of either medium

employee resistance or low-low interaction or high-high interactions of moderators, the double

moderation effect of combined moderators (W) and (Z) are not significant on the conditional

effect of (X) on (Y) with the t-values 1.307, -1.56, -.9205, -.1715, .8444, and p-value .074, .118,

.357, .863, .398. However, it is also found that at remaining conditions of low-medium, low-high,

high-low, high-medium interactions, the double moderation effect of combined moderators (W)

and (Z) are found to be significant with the t-values 5.80, 6.12, -4.02, -4.01 and p-value .000, .000,

.000, .000.

Table 4.16. Conditional Effect of X on Y at values of Both Moderators W and Z

Employee

Resistance (W)

Entrepreneurial

orientation (Z)

effect Se T P

Low Low -.0027 .1015 1.307 .074

Low Medium .0409 .0080 5.80 .000

Low High .0491 .0080 6.12 .000

Medium Low .0129 .0082 -1.56 .118

Medium Medium -.0012 .0073 -.1715 .863

Medium High -.0094 .0102 -.9205 .357

High Low -.0292 .0073 -4.01 .000

High Medium -.0211 .0052 -4.02 .000

High High .0069 .0082 .8444 .398


135

Hence, these results reflect that hypothesis nine (H9: Employee resistance and management

entrepreneurial orientation moderates the direct relationship of innovation capabilities and

business model innovation when the putative mediator service innovation success held constant)

is found to be correct.

4.4.6.2. Testing the dual moderated mediation effect of “W” “Z” and “M” on

relationship of “X” on “Y” (H-10).

This stage is the final consolidation of the previous four stages and results in a formation

of coherent single hypothesized research model of this research study. The hypothesized research

model of this research work is moderated moderated mediation model and also known as dual

moderated mediation (Hayes, 2017, 2018). Lambert and Edwards (2007) termed such

measurement model as first stage moderation direct effect model. This measurement model

consists of five key research variables, independent variable (X) possess the conditional effect on

dependent variable (Y) through a single mediator (M) that is moderated by double moderators (W)

and (Z). Double moderators have two kinds of moderation effect in this measurement model. A

moderation effect on the indirect effect of mediator (M) and the moderation effect on the direct

effect of independent (X) on dependent (Y). Table 4.17 reveals the results of this dual moderated

mediation model.

It reflects that the 68.09 percent of variance on the mediator service innovation success (M)

was explained by the independent variable (X) and the two moderators (W) and (Z) with the

significant p-value of .000 < .05. The results also revealed that there exist significant moderation

effect (.2610) of interaction term one “Int_1”(innovation capabilities (X) and employee resistance

(W)) with the t-value of 3.74 > 2 and significant p-value of .002 < .05. It was also found that there

exists a significant moderation effect (.3034) of interaction term two “Int_2” (innovation

capabilities (X) and entrepreneurial orientation (Z)) with the t-value of 3.67 > 2 and p-value of

.002 < .05. Thus, it proves the significant moderation effect of double moderators on the indirect

effect through mediator of independent (X) on dependent variable (Y).

Table 4.17 also shows that 79.94 percent of variance on the dependent business model

innovation (Y) was explained by the independent variable (X), the two moderators (W) and (Z),

and a mediator (M) with the significant p-value of .000 < .05. The results also shows that there


136

exist significant moderation effect (.0175) of interaction term three “Int_3”(innovation capabilities

(X) and employee resistance (W)) with the t-value of 12.5 > 2 and significant p-value of .000 <

.05. It is also found that there exists a significant moderation effect (.0451) of interaction term four

“Int_4” (innovation capabilities (X) and entrepreneurial orientation (Z)) on business model

innovation (Y) with the t-value of 3.34 > 2 and p-value of .000 < .05.

Table 4.17. Coefficients for Hypothesized Research Model of Study

Precursors

Model -1


Model – 2


Coeff Se T P Coeff Se T P

Constant 8.009 1.541 5.19 .000 .4433 .2553 1.73 .083

Innovation capabilities (X) .7456 .4216 3.45 .000 .1181 .0686 1.72 .086

Employee Resistance (W) -.7027 .2608 -3.93 .000 -.0628 .0226 -2.77 .000

Interaction_1 (XW) .2610 .0697 3.74 .002 -- -- -- --

Entrepreneurial orientation (Z) .8050 .2917 2.75 .006 .8249 .0473 17.45 .000

Interaction_2 (XZ) .3034 .0826 3.67 .003 -- -- -- --


Interaction_3 (XW) -- -- -- -- -.0175 .0014 -12.5 .000

Interaction_4(XZ) -- -- -- -- .0451 .0135 3.34 .000

R2 = 0.6809; F (5, 421) = 72.78

p = 0.000

R2 = 0.7994; F (6, 420) = 6281.03

p = 0.000


Thus, it proves the significant moderation effect of double moderators on the conditional

direct effect of independent (X) on dependent variable (Y). The non-significant effect of

.7456

R2 = 0.7994 p = 0.000

.824

9

-.0628

.805

0

Entrepreneurial orientation (Z)


.1181


(X)

.1060


(Y)

-.7027

Employee Resistance

(W)


137

independent variable (X) on dependent variable (Y) in model-2 with the t-value of 1.72 < 2 and p-

value of .086 > .05 evidences that the mediation effect of service innovation success exists between

the relationship of innovation capabilities (X) and business model innovation (Y). Table 4.18

reveals the conditional direct and indirect effect of innovation capabilities (X) on business model

innovation (Y) at values of both moderators.

Table 4.18. Conditional Direct, Indirect Effect of X on Y at values of Moderators

Employee

Resistance

(W)

Entrepreneurial

orientation (Z)

Direct Effect Indirect effect through mediator

Effect S.E T P Effect BootLLCI BootULCI

Low Low -.0143 .011 -1.14 .083 .2007 .0005 .0046

Low Medium .0234 .006 3.88 .000 .2115 .0018 .0059

Low High .0424 .008 5.12 .000 .2122 .0029 .0086

Medium Low -.0144 .008 -1.69 .091 .2115 .0018 .0057

Medium Medium -.0047 .008 -.5380 .590 .2123 .0030 .0083

Medium High -.0043 .008 -.5190 .604 .2131 .0041 .0115

High Low -.0514 .008 -6.01 .000 .2123 .0028 .0094

High Medium -.0323 .008 -3.88 .000 .2131 .0038 .0122

High High -.0133 .011 -1.16 .244 .2139 .0048 .0151

The direct effect (left column) shows at which condition of both employee resistance (W)

and entrepreneurial orientation (Z) do their interaction effects significant on the relationship of

innovation capabilities (X) and business model innovation (Y). The results show that at conditions

of either medium employee resistance or low-low interaction or high-high interactions of

moderators, the double moderation effect of combined moderators (W) and (Z) are not significant

on the conditional effect of (X) on (Y) with the t-values -1.14, -1.69, -.5380, -.5190, -1.16 and p-

values of .083, .091, .590, .604, .244. However, it is also found that at remaining conditions of

low-medium, low-high, high-low, high-medium interactions, the double moderation effect of

combined moderators (W) and (Z) are found to be significant with the t-values 3.88, 5.12, -6.01, -

3.88 and p-value .000, .000, .000, .000. The indirect effect (right column) shows at which condition

of both moderators (W) and (Z) do their interaction effect significant on the indirect effect of

innovation capabilities on business model innovation (Y) through mediator service innovation

success (M). The results reveal that the mediation effect at different conditions of moderators (i.e.


138

low, medium and high) are found to be significant with the values of BootLLCI and BootULCI

ranging different from zero. Thus, it can be said that the mediation effect of service innovation

success was positively significant at all conditions and interaction types of double moderators (W)

and (Z) in predicting the conditional effect of innovation capabilities (X) on business model

innovation (Y).

Thus, these results evidences that the hypothesis ten of this research study (H10: Service

innovation capabilities possess the positive indirect effect on the business model innovation

(through positive mediation effect of service innovation success), that is further negatively

moderated by employee resistance to change and positively moderated by the management

entrepreneurial orientation) also stands to be valid.

4.5. Checking the Fitness Indices of Dual Moderated Mediation Framework

The fitness of hypothesized theoretical framework (dual moderated mediation framework)

of this research work is also checked through structural equation modeling. The results of model

fitness summary of the hypothesized theoretical framework of this research work are shown in

table 4.19.

Table 4.19. Model Fitness Summary of Hypothesized Theoretical Framework

Fitness Indices Result Found Desired range Fit / Unfit

1) CMIN/df

p value

2.65

.087

< 3

>.05 Fit

2) Incremental Fitness Measures

• CFI

.974

> .90

Fit

• GFI .962 > .90 Fit

• AGFI .951 > .90 Fit

• TLI .907 > .90 Fit

• NFI .969 > .90 Fit

3) Absolute Fitness Measures

• RMSEA

.058

< .08

Fit

• PCLOSE .801 > .05 Fit

• SRMR .047 < .08 Fit

Generally, three forms of fitness indices may be noted in order to check the overall model

fitness. These include (i) CMIN ratio to degree of freedom, (ii) incremental fit indices and (iii)

absolute fit indices. It is believed that the value of “CMIN / df” below or equals to three (3) and


139

the non-significant p-value (greater than .05) reflects the goodness fit of the measurement model

(Marsh and Hocevar, 1985; Joreskog and Sorbom, 1993). It is also believed that the values of

incremental fitness measures such as such as comparative fit index (CFI), adjusted goodness of fit

(AGFI), tucker lewis index (TLI) and normed fit index (NFI) should be greater than 0.9 in order

to claim a model as good fit (Bentler & Bonett, 1980; Bollen, 1989; Tanaka & Huba, 1985).

Figure 4.11. Single Measurement Model of Hypothesized Research Model


140

Similarly, the measures of absolute fit indices such as root mean square error of

approximation (RMSEA), standardized root mean square residual (SRMR) and p of close fit

(PCLOSE) represents the bad fitness of model. The values of bad fitness measures SRMR and

RMSEA should be less than or equal to .08 (Browne and Cudeck, 1993). The values higher to .08

reflects the bad fitness of model and the value closer to zero (but less than .08) reflects the good

fitness of model. The value of PCLOSE should be greater than 0.05 for the good fit model in

comparison to close fitting (Kenny, 2014). The results reveal that the values of all the fitness

indices measures fall in the desired range. Thus, it is found that the hypothesized dual moderated

mediation framework of this research work possess the good fitness of measurement. The pattern

matrix builder of the measurement model is also shown in figure 4.11.


This chapter has shed light on the statistical tools and techniques used to empirically

validate and analyze the research constructs as well as the hypothesized relationships. First of all,

the demographic statistics are checked by overlooking the psychometric properties of the survey

participants. The results show that 71.19 percent of the respondent are males, 28.81 percent are

female, 3.98 percent are aged less than thirty years, 83.61 percent are aged between 31 years - 40

years and 12.41 percent are aged above than forty years. It is also found that 16.9 percent of

respondents are graduate, 71.90 percent are post-graduate qualified and 11.20 percent are MS or

MPhil or Doctorate or equivalent qualified. The descriptive statistics of the collected data is also

checked and it is found that the average mean score of innovation capabilities, service innovation

success, and entrepreneurial orientation falls under the category of “agree” of seven-point Likert

scale with the values of 5.0334, 5.0423 and 5.1370 respectively. On the other hand, the mean score

of employee resistance falls under the category of “disagree” of six-point Likert scale with the

value of 2.1734.

For testing the hypotheses, Regression based conditional process approach of Andrew

Hayes (2017, 2018) was adopted. The present theoretical framework of this research work is

termed as dual moderated mediation model by Hayes (2018). Before using the regression analysis

as statistical tool, the assumptions of data normality, multicollinearity and linearity were checked

and found to be satisfactory. The testing of all the ten proposed hypotheses of this research work

are embarked in five stages. In first stage, the simple mediation analysis is conducted to check the


141

mediation effect of service innovation success (M) on innovation capabilities (X) and business

model innovation (Y) relationship. This stage empirically tests the proposed hypotheses 1, 2, 3 and

4 of this study. In second stage, the moderation effect of entrepreneurial orientation (W) is checked

on the effect of innovation capabilities (X) and service innovation success (M). This empirically

tests the proposed hypothesis 5 of this study. Simultaneously, the moderation effect of

entrepreneurial orientation (W) is checked on the direct effect of innovation capabilities (X) and

business model innovation (Y) that empirically tests the proposed hypothesis 6 of this research

work. In third stage, the moderation effect of employee resistance (Z) is checked on the effect of

innovation capabilities (X) and service innovation success (M) that empirically tests the proposed

hypothesis 7. Simultaneously, the moderation effect of employee resistance (Z) is also checked on

the direct effect of innovation capabilities (X) and business model innovation (Y) that empirically

tests the proposed hypothesis 8 of this research work. In fourth stage, the moderation effect of both

entrepreneurial orientation (W) and employee resistance (Z) simultaneously check on the direct

relationship of innovation capabilities (X) and business model innovation (Y) with considering the

service innovation success (M) being held constant. This stage empirically tests the proposed

hypothesis 9 of this research work. In final fifth stage, overall the hypothesized theoretical

framework of this research work is tested that empirically tests the proposed hypothesis 10 of this

research work. The model fitness of the hypothesized theoretical framework of this research work

is also tested through Structural equation modeling. And it is found that the hypothesized dual

moderated mediation framework of this research work possess the good fitness of measurement.

Table 4.20 summarizes the results of hypotheses testing as follows;

Table 4.20. Summarizing Results of Research Hypotheses

Hypotheses Accepted or

Rejected

H1 Innovation capabilities may possess positive influence on business model

innovation. Accepted

H2 Innovation capabilities may possess positive influence on service innovation

success. Accepted

H3 Service innovation success may possess positive influence on business model

innovation Accepted

H4 Service innovation success mediates the relationship between innovation

capabilities and business model innovation Accepted


142

H5

Employee resistance to change moderates the direct relationship of innovation

capabilities and business model innovation, in such a way that the relationship

is stronger with lower employee resistance

Accepted

H6

Employee resistance to change negatively moderates the relationship between

innovation capabilities and service innovation success in such a way that the

relationship is stronger with lower employee resistance

Accepted

H7

Management entrepreneurial orientation moderates the direct relationship of

innovation capabilities and business model innovation, in such a way that the

relationship is stronger with increased entrepreneurial orientation

Accepted

H8

Management entrepreneurial orientation positively moderates the relationship

between innovation capabilities and service innovation success in such a way

that the relationship is stronger with increased entrepreneurial orientation.

Accepted

H9

Employee resistance and management entrepreneurial orientation moderates the

direct relationship of innovation capabilities and business model innovation

when the putative mediator service innovation success held constant

Accepted

H10

Service innovation capabilities possess the positive indirect effect on the

business model innovation (through positive mediation effect of service

innovation success), that is further negatively moderated by employee

resistance to change and positively moderated by the management

entrepreneurial orientation.

Accepted


143

CHAPTER 5

DISCUSSION, RECOMMENDATION AND CONCLUSION

This chapter deliberates the arguments derived from the results of data analysis in the light

of the posed research questions of this research work. On the basis of discussion, the conclusion

and major recommendations are made for practitioners. The future avenues of research are also

discussed in light of the limitations of this research work.

5.1. Discussion

This research work examines the concepts from three important streams of theoretical

underpinnings i.e. dynamic capabilities theory, strategic entrepreneurship theory and force field

theory of change.

5.1.1. Research Objective – 1.

Recent researches indicate that limited articles review the literature streams of business

model innovation elaborating the identified gaps and potential research questions for promotion of

new research on clarity of conception and development of theoretical frameworks (Schneider &

Spieth, 2014; Foss & Saebi, 2018, 2017; Teece, 2018, Geissdoerfer et al., 2018). This indicates

that the existing literature body on business model innovation has just begun to evolve with a need

to address the dimensions, facilitators and consequents of business model innovation (Saebi, Lien

& Foss, 2016; Teece, 2018; Foss & Saebi, 2018). There also exists a little agreement of researchers

on the dimensions of business model innovation as up till now very limited empirical analysis have

been conducted to establish the better understanding of the concept (Geissdoerfer et al., 2018; Foss

& Saebi, 2018). This serves as a gap in the existing literature. In order to contribute in addressing

this research gap, the research objective one was established as, “to empirically test the dimensions

of business model innovation in cultural context of Pakistan”. The empirical results of detailed

reliability and validity analysis affirmed the (ten factor based) operationalization of business model

innovation by Clauss (2017) in Pakistani cultural context. Thus, this work has attempted to address

the need for more empirical knowledge about the dimensions of business model innovation in

pursuance of laid down research objective one of study. Thus, in light of the findings of this

research work, the newly evolved concept of business model innovation can be defined as,


144

“Business model innovation refers to the acquisition of new capabilities, new technology or

equipment, new business partnerships and new business processes with an objective to offer new

products or services to address unmet needs of new markets or customers through more improved

distribution channels in order to attain the regulate the cordial customer relationship. This

phenomenon also involves the adoption of more improved and beneficial revenue model and cost

structures for the cellular organizations so that value can be captured for both i.e. customers as

well as the cellular organization”.


The research objective two of this research study was “to examine the role of service

innovation capabilities being the predictor of business model innovation”. This research objective

attempts to investigate, that does an organization adapt changes in its existing business model in

response to the internal driving forces of organizations such as innovation capabilities? The

empirical results of this research work shows that bringing substantial positive change in terms of

value in business model of organization depends upon the extent of organization’s capability to

smartly rework, co-design and co-produce on the new idea or new technological options along

with the diffusion of these new elements or concept of new services across the different functioning

of the organization. In particular, it has been found that the higher the innovative capable the

organization, the more likely that organization will bring the positive change in terms of value in

the existing business model. This finding is consistent with the dynamic capabilities theory, which

suggests that successful organization are the ones who are capable enough to timely respond to the

changing dynamics of the market through innovation (Teece et al., 1997). Even, Teece (2018) also

has conceptualized that strong innovation capabilities may yield strong business model innovation

and has recommended to be empirically tested in future researches. This empirical finding

contributes to the existing body of literature as some of the recent researches comprehend the need

to empirically explore the possible effect of innovation capabilities on business model innovation

(Scheinder & Speith, 2014; Foss & Saeibi, 2018, 2017; Teece, 2018).


The research objective three of this research study was “to examine the indirect mediation

impact of service innovation success on the association of service innovation capabilities and

business model innovation”. The empirical analysis in accomplishment of this laid down research


145

objectives, highlights that the executives of organization regulates the higher capabilities of

organization to smartly rework, co-design and co-produce on the new ideas or new technological

options. These executives regulates these capabilities in diffusion of these new elements or concept

of new services across the different functioning of the organization would achieve higher success.

This success could be illuminate in terms of adding substantial value to existing product or

services, sustained competitive position, financial success and precondition for future successes.

These successes by newly offered services further yield the substantial positive change in the

overall business model of the organization. Empirically, it can be stated from results that one unit

increase in innovation capabilities of organization would yield .4936 unit increase in innovation

success that would further yield .4998 unit increase in overall business model innovation. This

means that two executives of the cellular company who differ in regulating one unit of innovation

capabilities in the organization are estimated to differ in .2467 unit in bringing the substantial

positive change in terms of value in their existing business model. These findings are also found

to be consistent with the existing researches. These researches argue that the effect of innovation

capabilities on business model innovation is complex in nature (Teece, 2018). And further

conceptualize that there is a need to explore the association of these variables with some

performance indicators (as innovation success in this case) (Scheinder & Speith, 2014; Foss &

Saeibi, 2018; Teece, 2018). These empirical findings contribute to the existing body of knowledge

by addressing this need identified by existing researches (Scheinder & Speith, 2014; Foss & Saeibi,

2018; Teece, 2018). However, there further stands some inferences and barriers in an attempt to

achieve innovation success and business model innovation that further paves the way for research

objective four.


The research objective four of this research study was “to examine the moderation impact

of employee resistance on the direct and indirect association of service innovation capabilities and

business model innovation”. It is essential to discuss here that individuals of an organization are

the basic unit for the regulation of organizational processes inclusive of functional level, middle

level or top management level. It is obvious, that there may be some individuals that may carry

resistance to innovation due to their routine seeking behavior or close-mindedness or intolerance

of new adjustments or fear of losing control. The empirical analysis was conducted to accomplish

the laid down research objective four. And it also shows that organization’s capability to smartly


146

rework, co-design, co-produce and integrating the new idea or new technological options to bring

substantial valued change in business model is negatively affected by the employee’s resistance to

change if only if the overall employee resistance exists at higher levels among the executives and

senior managers. At an overall low level of employee resistance, its negative effect on the business

model innovation is nullified. It means that if the majority or maximum executive or senior

manager of any cellular firm carries the routine seeking behavior, or attribute of close-mindedness,

or intolerance to new adjustments and or fear of losing authority and control, then such cellular

firm may fails or minimally achieve the valued change in existing business model(s) irrespective

of pursuing higher intense firm’s innovative capabilities.

Similarly, it is also found that this resistive behavior of the individuals also prior affects

the innovation success of the firm that is also an outcome of organization’s innovation capabilities

and further paves the way forward towards the achievement of valued change in existing business

model(s). These results are also consistent with existing researches that claim the resistance of

individuals serve as a primary concern that affects the overall success ratio of business (Kegan &

Lahey, 2001; De Wit & Meyer, 2004). The recent researches also conceptualized that the employee

resistance is an essential internal factor that is critical to the achievement of business model

innovation (Foss & Saebi, 2017, 2018) and overall achievement of innovation success (Hao & Yu,

2011). They further pose a challenging research question that there is a need to empirically explore

the role of employee resistance on overall business model innovation of the organization (Foss &

Saebi, 2017, 2018). This finding also contributes to the existing body of knowledge by addressing

this posed research question of existing recent researches (Foss & Saebi, 2017, 2018).


The research objective five of this research study was “to examine the moderation impact

of management entrepreneurial orientation on the direct and indirect association of service

innovation capabilities and business model innovation”. It is essential to discuss here that,

generally, it is not necessary that all the individuals of the organization may carry this resistive

behavior. There may be some individuals (executives or senior managers) that may possess and

engage themselves in seeking unusual or novel opportunities with risk-taking with an intention to

adopt aggressive competitiveness against rivals and behave proactively to recent market trends. It

can be said because organizations continuously carry some routine forms of innovation in response

to its rivals or customer growing needs that guarantee its survival in competitive market dynamics.


147

Identifying the unusual or novel opportunities is something precursor to innovation success and

bringing substantial valued change in business models. Similarly, the empirical analysis was

conducted to accomplish the research objective five. And the findings also highlight that the

organization’s capability to smartly rework, co-design, co-produce and integrating the new ideas

or new technological options to bring substantial valued change in business model is substantially

affected by the management entrepreneurial stance, if and only if the overall management

entrepreneurial stance exists at moderate or higher levels among middle and top management. At

an overall low level of entrepreneurial orientation, its substantial enhancing effect on the business

model innovation is not empirically justified by the findings of this work. It means that if the

majority or equal number of executives or senior managers of any cellular firm carry the

entrepreneurial stance of readiness to innovate, follow aggressive competitiveness, act market

proactively and believe on risk-taking, then such cellular firm may successfully achieve the valued

change in their existing business model(s) with enhancing the overall effect of higher intense

firm’s innovative capabilities. Similarly, it was also found that this entrepreneurial stance of

middle and top management also substantially affects the innovation success of the firm that is an

outcome of organization’s innovation capabilities and further pave the way forward towards the

achievement of valued change in existing business model(s). These results are also consistent with

existing researches that claims the innovation as a heart of entrepreneurial activities (Baker &

Sinkula, 2009). Foss and Saebi (2018) also argue that the role of entrepreneurial orientation is

critical to business model innovation. They further pose a challenging research question that there

is a need to empirically explore the role of the entrepreneurial orientation of management on

overall business model innovation of the organization (Foss & Saebi, 2017, 2018). The above

finding also contributes to the existing body of knowledge by addressing this identified research

gap posed by the existing recent researches (Foss & Saebi, 2017, 2018).


Presently, the majority of the researches on the determinants of the business model

innovation are conceptual in nature and there are negligible or few research studies that offer

empirical evidence on what actually determines the business model innovation?. It is pertinent to

mention here that recent research studies have conceptually predicted that the business model

innovation may likely to occur in the influence of organization’s internal drivers of innovation

capabilities, entrepreneurial orientation and employee resistance that needs to be further


148

empirically explored (Teece, 2018; Foss & Saebi, 2018). This also serves as a research gap. In

light of above, the research objective six was established as “to examine the overall indirect effect

of service innovation capabilities on business model innovation (through mediation effect of

service innovation success) that are further moderated by employee resistance and management

entrepreneurial orientation”. In accomplishment of this research objective, this work presents the

empirical evidence on the effects of management entrepreneurial orientation and employee

resistance to change under which the innovation capabilities drive the organization to adopt

innovation in existing business models.

It is essential to discuss that the organizations may encompass a blend of both attributes

of individuals i.e. resistive-nature and entrepreneurial-nature. Generally, this statement can be

justified with the fact that organizations carry both winners and losers at the same time for the

attainment of business success (Foss & Saebi, 2017). The loser’s attempts to behave negatively

towards the ongoing or initiated innovation activities while the winner’s struggles to act positively

to bring substantial novel change. Hypothesis 9 and 10 of this research work can be elaborated in

this regard that proposed the influential tempering effect of employee resistance and management

entrepreneurial orientation at the same time on the role of innovation capabilities in shaping

business model innovation. The overall findings of this work indicate that if the innovation success

is considered constant, then the employee resistance casts the decreasing effect of 1.74 percent

variance in the attainment of business model innovation. On the other hand, the management

entrepreneurial orientation casts the increasing effect of 2.12 percent variance in the achievement

of substantial value in the business model simultaneously. The employee resistance and

management entrepreneurial orientation both attempts to cast their (negative and positive

respectively) effects on the indirect effect of innovation capabilities on business model innovation

(through innovation success). It is essential to discuss that the overall cumulative effect of both

forces (i.e. employee resistance and entrepreneurial orientation) is positive on the achievement of

business model innovation when the employee resistance (negative force) is at lower levels in

comparison to entrepreneurial orientation (positive force). The overall cumulative effect of both

forces are negative on the achievement of business model innovation when the entrepreneurial

orientation (positive force) is at lower levels in comparison to employee resistance (negative

force).


149

These findings are also consistent with the force field theory of change (Lewin, 1951;

Burnes, 2014). This theory states that there are two types of forces within the organization that

affects the change process. One is the driving force that accelerate the changes within the

organization while the other force is resistive in nature that opposes the on-going change

mechanism. The theory also claims that the driving forces should be higher than the resistive forces

in order to bring substantial novel change within the organization (Lewin, 1951). The findings of

this research work are found to be consistent with this previously established theory of force field

of change (Lewin, 1951; Burnes, 2014). The findings of this research work are significant as the

majority of previous researches have adopted the qualitative research methodology with the

limited or negligible empirical testing of the determinants as well as associations (Teece, 2018;

Foss & Saebi, 2018, 2017; Clauss, 2017; Saebi et al., 2017; Scheinder & Speith, 2014). The

explanation on the antecedents of business model innovation is also found to be limited with no or

negligible empirical evidence in previous researches (Teece, 2018; Foss & Saeibi, 2018, 2017;

Clauss, 2017; Saebi et al., 2017; Scheinder & Speith, 2014). This research work, to best of

knowledge, is the first empirical study on the validation of operationalization of business model

innovation and investigation of antecedents of business model innovation specifically in the

cultural context of Pakistan. This research work also implies the crucial findings for the

practitioners in the managerial implications section.

5.2. Recommendations

This research work concludes with two forms of recommendations. Recommendations for

the practitioners of cellular companies of Pakistan are discussed as ‘managerial implications’. On

the other hand, the recommendations for academicians that lay downs the vision for future

researches are discussed as ‘limitations and future research directions’.

5.2.1. Managerial Implications

The findings of this research work imply some critical recommendations for the managers

and executives of cellular companies that are explained as below;

5.2.1.1. Need to consider business model innovation

Generally, it is believed that innovating the new products or services and bringing

innovation in existing processes (i.e. cost reduction techniques etc) paves the way for business

success in comparison to rivals. However, these elements are proved to be insufficient, in practice,


150

to ensure competitiveness and overall business success (Chesbrough, 2010). With the advent of

“internet of things”, the concept of “e-commerce”, “digital economy” and “national financial

inclusion strategy” by the Pakistan Telecommunication Authority (PTA), the practitioners of

cellular companies needs to manage the speed of change along with the breathtaking pace of

technological advancements. Innovating in terms of new products, services or better-tailored

processes can easily be copied and thus, cannot be relied on for sustainability in such complex

market dynamics of the telecom sector. Furthermore, the returns attained from innovating product,

service or processes are not guaranteed in the longer run and erodes with the time. Cellular

companies need a different type of innovation that can allow a cellular company to change the rule

of games and let an organization prove itself more competitive. This required new form of

innovation is business model innovation that is difficult to replicate or copy or follow by

competitors as replication or copy or follow may require substantial time and efforts by the rivals.

Consequently, it also results in more consistent returns. This study has provided a deeper insight

into the business model innovation that what are the constituents of business model innovation in

the cultural context of the cellular company. Usually, it is also believed that an organization can

innovate their business models by altering their value mechanisms by integrating more advanced

technology. However, it is pertinent to explain that business model innovation is innovating

inclusive of all, classified in groups of creating value, proposition a value and capturing value.

5.2.1.2. Need to consider value creation

Practitioners of cellular companies can create value through new capabilities, new

technologies and equipments, new processes and structures, and developing new partnerships.

Capabilities are something that is embedded in activities. New capabilities can succeed and

develop through continuous learning of organizational members. Integration of new knowledge

relating technologies, market recent trends, new business practices, exploration and exploitation

of new ideas, empowerment of organizational members to experiment self-learn and self-develop

(through training, seminars, informational platforms and developmental opportunities) are all

sources to acquire the new capabilities. Similarly, the adoption of new technological trends, new

technological equipments and aligning these technological developments to the existing are the

contributing element to business model innovation. In addition to these, new processes and

structures also serve as a basis for achieving business model innovation. This factor is an essential

ingredient and critical for the introduction of product or service’s personalized customization


151

offers. Little altering or addition of new process at the last stage of production of product or service

offering can lead to personalized customization offers to the customer that would serve as an

innovation in the business model.

5.2.1.3. Need to consider value proposition

Practitioners of cellular companies can also achieve innovation in business models through

extending proposition value that requires new offerings, new customers and markets, new channels

and strong customer relationships. Practitioners can make new offerings by addressing the unmet

needs of customers, offer more innovative product or service in comparison to rivals and engage

themselves in a continuous struggle to solve customer needs that are left unmet by rivals. New

customers and markets are also a source for ensuring business model innovation through value

proposition. It includes taking an opportunity to penetrate in growing or new markets and seeks to

target the new customer segments on a regular basis. However, increasing the customer base

should not the only strategy to achieve business model innovation. Practitioners should also focus

to retain the existing customers by developing a cordial relationship with them.

5.2.1.4. Need to consider value capture

Furthermore, another important aspect is the capture of value. This capture of value can be

made by practitioners of cellular company through introduction of new revenue model and new

cost structures. Practitioners can introduce the new revenue models by developing new revenue

opportunities (such as additional sales or cross-selling etc.) and replace one-time transaction

revenues with the long-term recurring revenue models (such as leasing). Similarly, new cost

structures can be adopted regularly by reflecting the price-quantity strategy, seek ways to cut down

manufacturing costs, upgrade the cost structures with changing market prices and utilize the

opportunities of price differentiation as needed. These are some crucial indicators and constituents

of business model innovation. The practitioners of cellular companies need to strengthen these

discussed parameters as they reflect the extent of business model innovation carried by their

organization. However, the findings of this research work also suggest that there are also some

enablers and barrier to business model innovation. Practitioners of the cellular company also need

to consider these enablers and barrier in order to achieve maximum business model innovation.

5.2.1.5. Need to consider capabilities to innovate


152

The results of this research work suggest that the factor of innovation capabilities should

also be aligned and synchronized with the business model innovation efforts of the organization.

Strategist of the cellular company should spend more time, energies and efforts on new

technological options, customer needs and market opportunities. Strategist needs to smartly re-

work on these newly sensed elements to create something new product or service offerings to

market. However, the findings of this research work suggest that this higher effort of innovation

capabilities may still hamper organizational inertia in overall efforts of attaining business model

innovation. There are some other critical factors that also need to be considered by the strategist

and practitioners of the cellular company along with the above explained elements.

5.2.1.6. Need to manage behavioral resistance

It is essential to state that managing the organizational members (in context of behavioral

resistance) is as crucial for the organization, as the other efforts put forth for accelerating the

innovation capabilities and entrepreneurial orientation for the success of innovation mechanism.

The findings of this work also indicate that the resistance to change is the major barrier that

devastatingly effects the above discussed constituents and enabler of business model innovation.

Practitioners and strategists need to seriously look into this barrier that plays a role of trauma to

the attainment of overall business model innovation. This resistance would not be uniform among

members instead it would vary as per the individual’s personality (Oreg, 2003). Those individuals

who carries low level of this dispositional resistance to change will be supposed to accept the novel

changes. While on the other hand, the members who carry a high level of this dispositional

resistance will attempt to reject the novel changes. Now, those individuals with high dispositional

resistance may carry resistance due to the attributes of routine seeking behavior, emotional reaction

fear of loss of control, closed mindedness and weak stimulation for experiencing something

different or new.

The resistance caused by the routine seeking behavior, close mindedness and weak

stimulation for experiencing something new, can be managed by the organization through effective

communication strategies and participative roles of employees (Oreg, 2003; Burnes, 2014).

Constructively engaging these individuals in novel change’s process and convincing them through

communication may help. There is a need to realize them a sense of urgency by discussing the

potential crises or major opportunities. Inquiry and dialogue may be used to communicate them

with the underlying problems that require those novel changes and then, engaging them in finding


153

the solutions of the problem, may automatically disposition the higher resistance by these

individuals to minimal or negligible levels. It is obvious that the employees if provided with the

full authority to exercise their assigned jobs / targets with freedom further strengthens the

innovative culture with higher innovative productivities and sense of accountability. The literature

also supports the arguments that the employees provided with challenges, freedom, openness, risk-

taking, liveliness and humor encourages the creative climate among the organizational members

(Ekvall, 1996; Deal & Kennedy, 1982; Lawson & Samson, 2001).

Another essential aspect here is the influence of transformational leadership attributes of a

single individual on another. An individual with transformation leadership attributes motivates the

surrounding individuals to strive for more long-term goals rather than short-term profits (Burnes,

2014). Therefore, interactions (through formal meetings or informal gatherings) among the

executives and senior managers play a crucial role in spreading motivation across the top and a

middle layer of management by the transformational leadership attributes of the single individual.

The resistance of members due to emotional reactions of fear of control loss may also overcome

by stimulating the positive emotions about the novel change by reappraising the situation. Again,

the above explained parameters would be helpful to change the mindsets of individuals by

emphasizing on the positive outcomes of the novel changes and realizing the need for urgency.

5.2.1.7. Need to consider management entrepreneurial skills

The findings of this work also suggest that the entrepreneurial skills of management along

with the innovation capabilities casts a synergizing effect on the business model innovation. These

entrepreneurial orientation involves the risk-taking behavior of management, encouragement of

new ways of doing thinks, seeking novel solutions or opportunities, facilitating employees in

taking risks, struggles to initiate leading foremost actions in comparison to competitors, facilitates

research and development, technological leadership and continuously markets new lines of product

with more improvements. This synergizing effect of entrepreneurial orientation also attempts to

nullify the devastating effect of resistance to change. The findings have also highlighted that the

stronger entrepreneurial stance of the organization in comparison to resistance would yield a

substantial enhancing change in business model innovation. However, the findings also pointed

that the lower entrepreneurial stance of the organization in comparison to resistance level would

yield the devastating effect on the business model innovation (by terminating the effects of higher

innovation capabilities of organization). Thus, the strategist and practitioners of the cellular


154

company of Pakistan need to consider these factors wholeheartedly for the pursuit of business

model innovation.

5.2.1.8. Research instrument as practicing tool for practitioners

Another important implication for the practitioners of the cellular company are the research

instruments (questionnaire) of this research work. Strategists and practitioners of the cellular

company can use the research instruments of this study in order to identify the relevant problem

areas of their organization and further stimulate the extent of business model innovation through

addressing those identified problem areas. These research questionnaires would help the

practitioners to self-assess their organization’s business innovation strategies, resistance level,

entrepreneurial orientation level and extent of business model innovation captured by the cellular

company. Proper allocation of resources can be made in the right way by assessing the extent of

different constituents of business model innovation. Furthermore, resistance to change

questionnaire can be used for the personnel selection of key management positions of the cellular

company. It can also be used to identify and select change-resilient personnel for the role positions

that entail frequent changes. Overall, it can be said that more informed decisions can be made on

the basis of the gathered knowledge by using these research questionnaire.

5.2.2. Limitations and Future Research Directions

This work has attempted to address some of the literary gaps by empirically investigating

the enablers and elements influencing the business model innovation, however still this research

study carries some limitations. Firstly, this work carries a methodological limitation as the

collection of data are based on multiple respondents from a single organization selected under the

umbrella of simple random sampling technique. This work is based on single-industry that is

cellular companies of Pakistan. Thus, the empirical testing of enablers of business model

innovation cannot be claimed to be generalized on other service segments / industries of the

cultural context of Pakistan. This limitation was because of limited time and financial budgetary

constraints. Another limitation of this study that this research work has not cited the role of

experimentation and learning processes in identifying the different innovative capabilities and its

influence on other enablers. The existing literature also pertains the evidences that the learning

processes, knowledge exploration and exploitative practices are required to enhance the innovative

capabilities of the organization, however their nature of influence as value creating attribute have


155

not yet been studied. This further opens the new avenues for research. There are many other

organizational variables that are left out by this research work. Bringing innovation in business

model stands as a cognitive structures that requires a philosophy of earmarking the boundaries of

organization’s internal structures, mechanisms to generate value and enduring its corporate

governance. This perspective highlights the role of organizational and managerial cognition as key

foci for regulating the innovation in business model. Although, this research work has attempted

to study the entrepreneurial orientation of the management but the role of organizational cognition

has not taken in account. This serves as a limitation. A separate detailed research can be conducted

to investigate the role of different cognitive processes of management in decisions of business

model innovation. Other organizational factors such as strategic flexibility including resource and

coordination flexibility, organizational culture may also be explored as the influencers of business

model innovation. The role of product market strategies, promotional and pricing strategies,

customer brand knowledge and brand reputation are other influencing factors that may impact the

innovative success of new business models that needs to be studied in future studies. In this way,

business model innovation may be undertaken as strategy of process optimization or value creation

that may ultimately attains the better financial or sustainable results.

Summarizing, future researches are recommended to further testify the theoretical

framework of this research work by taking in account the large sample of Pakistani service sector.

It is recommended that future researches may empirically testify the theoretical framework of this

research work in different nature of industries and cultural contexts. Furthermore, based on the

theoretical framework of this research work, future researches may also carry a comparative study

among the four cellular companies relating the extent of business model innovation achieved and

their effect on the competitive positioning of the organization in the telecom industry. New

researches can also extend the present theoretical framework by investigating the role of other

organizational factors such as learning processes, knowledge exploration and exploitation

practices, organizational cognition processes, structural flexibility, organizational culture etc.

5.3. Conclusion

This study attempts to investigate the antecedents of business model innovation. The

review of extensive literature has revealed six crucial research gaps pointed by existing recent

researches. An attempt to address these identified six research gaps further paves the way for the

establishment of research objectives and research questions of this research work.


156

The objective of this research work is to examine the role of innovation capabilities in

determining the business model innovation and to further empirically investigate the role of service

innovation success, employee resistance and entrepreneurial orientation on the direct association

of innovation capabilities and business model innovation. In addition to this, it is also aimed to

examine the overall indirect effect of innovation capabilities on business model innovation

(through the mediation effect of service innovation success), that is moderated by employee

resistance and entrepreneurial orientation. It is also aimed to empirically validate the

operationalization of business model innovation.

On the basis of these laid down research objectives, six research questions have been

framed. The quest to answer these guiding six research questions inevitably addresses the

identified six research gaps of this research work and further paves the way for the formation of

ten research hypotheses.

The review of extensive literature body and the empirical results of this research work has

shown that the employee resistance (a resistive negative factor) and entrepreneurial orientation

(driving accelerating factor) both need special attention by managers and executives in daily

organizational activities and processes. Gearing up the innovation capabilities of the organization

alone may not produce a substantial effect on the attainment of innovation success and business

model innovation. The diagnosis of the extent of the two forces (employee resistance and

management entrepreneurial orientation) are critical for the organizations in order to understand

how substantial value effect in business models may be achieved. Referring to diagnosis here

means the extent of sub-elements of these forces that cumulatively measure the overall effect of

these two forces. The findings of this research work serve as critical implications for the managers

and executives of cellular companies of Pakistan. To sum up, these findings and managerial

implications serve as an initial step for practitioners who are striving for the innovation in their

current business model. It may help the practitioners in determining the extent of various sub-

elements of employee resistance and management entrepreneurial, and to deeply understand their

nature of effect that further yield the positive desired outcome of business model innovation.

In light of all above remarks, it can be concluded that the innovation capabilities,

entrepreneurial orientation, synergizing interaction effect of entrepreneurial orientation

(interaction of innovation capabilities and entrepreneurial orientation), employee resistance and


157

the devastating interaction effect of employee resistance (interaction of innovation capabilities and

employee resistance), all these five constructs cast an overwhelming effect on service innovation

success and business model innovation. Therefore, these factors can be considered and termed as

an antecedent factor of business model innovation.


158

REFERENCES

Adler, P. S., & Shenbar, A. (1990). Adapting your technological base: The organizational

challenge. Sloan management review, 32(1), 25-37.

Adrodegari, F., Pashou, T., & Saccani, N. (2017). Business model innovation: process and tools

for service transformation of industrial firms. Procedia CIRP, 64, 103-108.

Amit, R., & Schoemaker, P. J. (1993). Strategic assets and organizational rent. Strategic

Management Journal, 14(1), 33-46.

Amit, R., & Zott, C. (2012). Creating value through business model innovation. MIT Sloan

Management Review, 53(3), 41-49.

Araujo, L., & Spring, M. (2006). Services, products, and the institutional structure of production.

Industrial Marketing Management, 35(7), 797-805.

Arvanitis, S., & Stucki, T. (2012). What determines the innovation capability of firm founders?

Industrial and Corporate Change, 21(4), 1049-1084.

Ashforth, B. E., & Mael, F. A. (1998). Sustaining Valued Identities. Power and influence in

organizations, 89.

Aspara, J., Rajala, R., & Tuunainen, V. K. (2012). The future of banking services.

Atuahene-Gima, K. (2003). The effects of centrifugal and centripetal forces on product

development speed and quality: How does problem solving matter? Academy of

Management Journal, 46(3), 359-373.

Avlonitis, G. J., & Salavou, H. E. (2007). Entrepreneurial orientation of SMEs, product

innovativeness, and performance. Journal of Business Research, 60(5), 566-575.

Aziati, A. N., Tasmin, R. H., Jia, L. B., & Abdullah, N. H. (2014). The relationship of

technological innovation capabilities and business innovation capabilities on organization

performance: Preliminary findings of Malaysian food processing SMEs. Paper presented

at the Engineering, Technology and Innovation (ICE), 2014 International ICE Conference

on.

Baden-Fuller, C., & Haefliger, S. (2013). Business models and technological innovation. Long

range planning, 46(6), 419-426.


159

Baer, M. (2007). Innovation in organizations: The generation and implementation of radical ideas.

University of Illinois at Urbana-Champaign.

Baker, W. E., & Sinkula, J. M. (2009). The complementary effects of market orientation and

entrepreneurial orientation on profitability in small businesses. Journal of small business

management, 47(4), 443-464.

Barnard, C. (1938). 1.(1938). The functions of the executive.

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of management,

17(1), 99-120.

Barney, J. B. (1996). The resource-based theory of the firm. Organization science, 7(5), 469-469.

Barney, J., Wright, M., & Ketchen Jr, D. J. (2001). The resource-based view of the firm: Ten years

after 1991. Journal of management, 27(6), 625-641.

Barrett, M., Davidson, E., Prabhu, J., & Vargo, S. L. (2015). Service innovation in the digital age:

key contributions and future directions. MIS quarterly, 39(1), 135-154.

Bartolucci, F., Bacci, S., & Gnaldi, M. (2015). Statistical analysis of questionnaires: A unified

approach based on R and Stata: Chapman and Hall/CRC.

Bashir, M., & Verma, R. (2019). Internal factors & consequences of business model

innovation. Management Decision, 57(1), 262-290.

Bellman, R. (1957). E. 1957. Dynamic programming. Princeton University Press. Bellman

Dynamic programming1957, 151.

Bentler, P. M. (1992). On the fit of models to covariances and methodology to the Bulletin.

Psychological bulletin, 112(3), 400.

Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of

covariance structures. Psychological bulletin, 88(3), 588.

Björkdahl, J., & Börjesson, S. (2012). Assessing firm capabilities for innovation. International

Journal of Knowledge Management Studies, 5(1-2), 171-184.

Bollen, K. A. (1989). A new incremental fit index for general structural equation models.

Sociological Methods & Research, 17(3), 303-316.

Breznik, L., & D. Hisrich, R. (2014). Dynamic capabilities vs. innovation capability: are they


160

related? Journal of small business and enterprise development, 21(3), 368-384.

Brockhaus Sr, R. H. (1980). Risk taking propensity of entrepreneurs. Academy of Management

Journal, 23(3), 509-520.

Brower, R. S., & Abolafia, M. Y. (1995). The structural embeddedness of resistance among public

managers. Group & Organization Management, 20(2), 149-166.

Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. Sage focus editions,

154, 136-136.

Bryson, J. R., & Daniels, P. W. (2010). Service Worlds service worlds Handbook of service science

(pp. 79-104): Springer.

Bucherer, E., Eisert, U., & Gassmann, O. (2012). Towards systematic business model innovation:

lessons from product innovation management. Creativity and innovation management,

21(2), 183-198.

Burnes, B. (2015). Understanding resistance to change–building on Coch and French. Journal of

change management, 15(2), 92-116.

Camelo-Ordaz, C., Garcia-Cruz, J., Sousa-Ginel, E., & Valle-Cabrera, R. (2011). The influence of

human resource management on knowledge sharing and innovation in Spain: the mediating

role of affective commitment. The International Journal of Human Resource Management,

22(07), 1442-1463.

Cameron, E., & Green, M. (2015). Making sense of change management: A complete guide to the

models, tools and techniques of organizational change. Kogan Page Publishers.

Campos, A. C., Mendes, J., Valle, P. O. d., & Scott, N. (2018). Co-creation of tourist experiences:

A literature review. Current Issues in Tourism, 21(4), 369-400.

Capaldo, A. (2001). The leveraging of a dual network as a distinctive relational capability.

Evidence from three longitudinal case studies. Paper presented at the 2001 Academy of

Management (AOM) Conference.

Casadesus-Masanell, R., & Ricart, J. E. (2012). 22 Competing through business

models1. Handbook of Research on Competitive Strategy, 460.

Castellacci, F., & Natera, J. M. (2013). The dynamics of national innovation systems: A panel


161

cointegration analysis of the coevolution between innovative capability and absorptive

capacity. Research policy, 42(3), 579-594.

Cavana, R., & Delahaye, B. Uma Sekaran (2001). Applied Business Research: Qualitative &

Quantitative Method.

Chae, B. K. (2012). An evolutionary framework for service innovation: Insights of complexity

theory for service science. International journal of production economics, 135(2), 813-

822.

Chamsuk, W., Fongsuwan, W., & Takala, J. (2017). The Effects of R&D and Innovation

Capabilities on the Thai Automotive Industry Part’s Competitive Advantage: A SEM

Approach. Management and Production Engineering Review, 8(1), 101-112.

Chan Kim, W., & Mauborgne, R. (2004). Value innovation: The strategic logic of high growth.

Harvard business review, 82(7-8), 172-180.

Chandler, A. D. (1992). Organizational capabilities and the economic history of the industrial

enterprise. The Journal of Economic Perspectives, 6(3), 79-100.

Chandy, R. K., & Tellis, G. J. (2000). The incumbent’s curse? Incumbency, size, and radical

product innovation. Journal of marketing, 64(3), 1-17.

Chang, S., Gong, Y., & Shum, C. (2011). Promoting innovation in hospitality companies through

human resource management practices. International Journal of Hospitality Management,

30(4), 812-818.

Chen, J.-S., Tsou, H. T., & Huang, A. Y.-H. (2009). Service delivery innovation: Antecedents and

impact on firm performance. Journal of Service Research, 12(1), 36-55.

Chen, J.-S., Weng, H.-H., & Huang, C.-L. (2018). A multilevel analysis of customer engagement,

its antecedents, and the effects on service innovation. Total Quality Management &

Business Excellence, 29(3-4), 410-428.

Chesbrough, H., & Rosenbloom, R. S. (2002). The role of the business model in capturing value

from innovation: evidence from Xerox Corporation's technology spin‐off companies.

Industrial and Corporate Change, 11(3), 529-555.

Chiesa, V., Coughlan, P., & Voss, C. A. (1996). Development of a technical innovation audit.

Journal of Product Innovation Management: AN INTERNATIONAL PUBLICATION OF


162

THE PRODUCT DEVELOPMENT & MANAGEMENT ASSOCIATION, 13(2), 105-136.

Christensen, C. M., & Raynor, M. E. (2003). The innovation’s solution. Harvard Business School

Press, Boston, Massachusetts.

Christensen, J. F. s. (1996). Innovative assets and inter-asset linkages—A resource-based approach

to innovation. Economics of Innovation and New Technology, 4(3), 193-210.

Chung, G. H., Choi, J. N., & Du, J. (2017). Tired of innovations? Learned helplessness and fatigue

in the context of continuous streams of innovation implementation. Journal of

Organizational Behavior, 38(7), 1130-1148.

Clauss, T. (2017). Measuring business model innovation: conceptualization, scale development,

and proof of performance. R&D Management, 47(3), 385-403.

Coch, L., & French Jr, J. R. (1948). Overcoming resistance to change. Human relations, 1(4), 512-

532.

Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning

and innovation. Administrative science quarterly, 128-152.

Comes, S., & Berniker, L. (2008). Business model innovation From strategy to execution (pp. 65-

86): Springer.

Comes, S., & Berniker, L. (2008). Business model innovation. In From strategy to execution (pp.

65-86). Springer, Berlin, Heidelberg.

Conner, K. R., & Prahalad, C. K. (1996). A resource-based theory of the firm: Knowledge versus

opportunism. Organization science, 7(5), 477-501.

Corley, K. G., & Gioia, D. A. (2011). Building theory about theory building: what constitutes a

theoretical contribution?. Academy of management review, 36(1), 12-32.

Covin, J. G., & Lumpkin, G. T. (2011). Entrepreneurial orientation theory and research:

Reflections on a needed construct. Entrepreneurship theory and practice, 35(5), 855-872.

Covin, J. G., & Miles, M. P. (1999). Corporate entrepreneurship and the pursuit of competitive

advantage. Entrepreneurship theory and practice, 23(3), 47-63.

Covin, J. G., & Slevin, D. P. (1989). Strategic management of small firms in hostile and benign

environments. Strategic Management Journal, 10(1), 75-87.


163

Covin, J. G., & Wales, W. J. (2012). The measurement of entrepreneurial orientation.

Entrepreneurship theory and practice, 36(4), 677-702.

Cui, A. S., & Wu, F. (2017). The Impact of Customer Involvement on New Product Development:

Contingent and Substitutive Effects. Journal of Product Innovation Management, 34(1),

60-80.

Cummings, A., & Oldham, G. R. (1997). Enhancing creativity: Managing work contexts for the

high potential employee. California Management Review, 40(1), 22-38.

Danneels, E. (2004). Disruptive technology reconsidered: A critique and research agenda. Journal

of Product Innovation Management, 21(4), 246-258.

Dawes, J. (2008). Do data characteristics change according to the number of scale points used? An

experiment using 5-point, 7-point and 10-point scales. International journal of market

research, 50(1), 61-104.

Day, G. S. (1994). The capabilities of market-driven organizations. The Journal of Marketing, 37-

52.

De Brentani, U., & Ragot, E. (1996). Developing new business-to-business professional services:

what factors impact performance? Industrial Marketing Management, 25(6), 517-530.

Deal, T. E., & Kennedy, A. A. (1983). Culture: A new look through old lenses. The journal of

applied behavioral science, 19(4), 498-505.

Del Canto, J. G., & Gonzalez, I. S. (1999). A resource-based analysis of the factors determining a

firm's R&D activities. Research policy, 28(8), 891-905.

Den Hertog, P., Van der Aa, W., & De Jong, M. W. (2010). Capabilities for managing service

innovation: towards a conceptual framework. Journal of service Management, 21(4), 490-

514.

Dent, E. B., & Goldberg, S. G. (1999). Challenging “resistance to change”. The Journal of applied

behavioral science, 35(1), 25-41.

Desyllas, P., & Sako, M. (2013). Profiting from business model innovation: Evidence from Pay-

As-You-Drive auto insurance. Research policy, 42(1), 101-116.

Dosi, G., Nelson, R., & Winter, S. (2001). The nature and dynamics of organizational capabilities:


164

OUP Oxford.

Doz, Y. L., & Kosonen, M. (2010). Embedding strategic agility: A leadership agenda for

accelerating business model renewal. Long range planning, 43(2-3), 370-382.

Du Preez, N. D., Louw, L., & Essmann, H. (2006). An innovation process model for improving

innovation capability. J. High Technol. Manag. Res, 1-24.

Duane Ireland, R., Kuratko, D. F., & Morris, M. H. (2006). A health audit for corporate

entrepreneurship: innovation at all levels: part I. Journal of business strategy, 27(1), 10-

17.

Edvardsson, B. (1997). Quality in new service development: Key concepts and a frame of

reference. International journal of production economics, 52(1-2), 31-46.

Edvardsson, B., & Olsson, J. (1996). Key concepts for new service development. Service

Industries Journal, 16(2), 140-164.

Edwards, J. R., & Lambert, L. S. (2007). Methods for integrating moderation and mediation: a

general analytical framework using moderated path analysis. Psychological

methods, 12(1), 1.

Egan, R. W., & Fjermestad, J. (2005). Change and Resistance help for the practitioner of change.

Paper presented at the System Sciences, 2005. HICSS'05. Proceedings of the 38th Annual

Hawaii International Conference on.

Eggers, J. P., & Kaplan, S. (2013). Cognition and capabilities: A multi-level perspective. Academy

of Management Annals, 7(1), 295-340.

Eid, M. (2000). A multitrait-multimethod model with minimal assumptions. Psychometrika, 65(2),

241-261.

Ekvall, G. (1996). Organizational climate for creativity and innovation. European journal of work

and organizational psychology, 5(1), 105-123.

Eppler, M. J., Hoffmann, F., & Bresciani, S. (2011). New business models through collaborative

idea generation. International Journal of Innovation Management, 15(06), 1323-1341.

Euchner, J., & Ganguly, A. (2014). Business model innovation in practice. Research-Technology

Management, 57(6), 33-39.


165

Evans, S., Vladimirova, D., Holgado, M., Van Fossen, K., Yang, M., Silva, E. A., & Barlow, C.

Y. (2017). Business model innovation for sustainability: Towards a unified perspective for

creation of sustainable business models. Business Strategy and the Environment, 26(5),

597-608.

F. Hair Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares

structural equation modeling (PLS-SEM) An emerging tool in business research. European

Business Review, 26(2), 106-121.

F. Hair Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares

structural equation modeling (PLS-SEM) An emerging tool in business research. European

Business Review, 26(2), 106-121.

Fisk, R. P., Brown, S. W., & Bitner, M. J. (1993). Tracking the evolution of the services marketing

literature. Journal of retailing, 69(1), 61-103.

Fleury, A., Fleury, M. T. L., & Borini, F. M. (2013). The Brazilian multinationals' approaches to

innovation. Journal of International Management, 19(3), 260-275.

Flikkema, M., Jansen, P., & Van Der Sluis, L. (2007). Identifying neo-Schumpeterian innovation

in service firms: A conceptual essay with a novel classification. Economics of Innovation

and New Technology, 16(7), 541-558.

Flower, O. D. (1962). Overcoming resistance to change [Film]. Beverly Hills, CA: Roundtable

Productions.

Folger, R., & Skarlicki, D. P. (1999). Unfairness and resistance to change: Hardship as

mistreatment. Journal of organizational change management, 12(1), 35-50.

Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and

measurement error: Algebra and statistics. Journal of Marketing research, 382-388.

Foss, N. J., & Saebi, T. (2017). Fifteen years of research on business model innovation: how far

have we come, and where should we go?. Journal of Management, 43(1), 200-227.

Foss, N. J., & Saebi, T. (2018). Business models and business model innovation: Between wicked

and paradigmatic problems. Long range planning, 51(1), 9-21.

Fox, K. J. (1999). Changing violent minds: Discursive correction and resistance in the cognitive

treatment of violent offenders in prison. Social Problems, 46(1), 88-103.


166

Freel, M. S. (2005). Patterns of innovation and skills in small firms. Technovation, 25(2), 123-134.

Freeman, C., & Soete, L. (2009). Developing science, technology and innovation indicators: What

we can learn from the past. Research policy, 38(4), 583-589.

Froehle, C. M., Roth, A. V., Chase, R. B., & Voss, C. A. (2000). Antecedents of new service

development effectiveness: an exploratory examination of strategic operations choices.

Journal of Service Research, 3(1), 3-17.

Fu, X. (2008). Foreign direct investment, absorptive capacity and regional innovation capabilities:

evidence from China. Oxford Development Studies, 36(1), 89-110.

Furr, R. M., & Bacharach, V. R. (2014). Test dimensionality and factor analysis. Psychometrics:

an introduction, 61-77.

Furseth, P. I., & Cuthbertson, R. (2013). The service innovation triangle: a tool for exploring value

creation through service innovation. International Journal of Technology Marketing 24,

8(2), 159-176.

Gallouj, F., & Weinstein, O. (1997). Innovation in services. Research policy, 26(4-5), 537-556.

Gallouj, F., & Windrum, P. (2009). Services and services innovation: Springer.

Gambardella, A., & McGahan, A. M. (2010). Business-model innovation: General purpose

technologies and their implications for industry structure. Long range planning, 43(2-3),

262-271.

Gatignon, H., Tushman, M. L., Smith, W., & Anderson, P. (2002). A structural approach to

assessing innovation: Construct development of innovation locus, type, and characteristics.

Management science, 48(9), 1103-1122.

Gebauer, H., Worch, H., & Truffer, B. (2012). Absorptive capacity, learning processes and

combinative capabilities as determinants of strategic innovation. European Management

Journal, 30(1), 57-73.

Geissdoerfer, M., Vladimirova, D., Van Fossen, K., & Evans, S. (2018). Product, service, and

business model innovation: A discussion. Procedia Manufacturing, 21, 165-172.

George, G., & Bock, A. J. (2011). The business model in practice and its implications for

entrepreneurship research. Entrepreneurship theory and practice, 35(1), 83-111.


167

Gerbing, D. W., & Anderson, J. C. (1988). An updated paradigm for scale development

incorporating unidimensionality and its assessment. Journal of marketing research, 25(2),

186-192.

Ghezzi, A., Cortimiglia, M. N., & Frank, A. G. (2015). Strategy and business model design in

dynamic telecommunications industries: A study on Italian mobile network

operators. Technological Forecasting and Social Change, 90, 346-354.

Giraud Voss, Z., Voss, G. B., & Moorman, C. (2005). An empirical examination of the complex

relationships between entrepreneurial orientation and stakeholder support. European

journal of Marketing, 39(9/10), 1132-1150.

Grant, R. M. (1996). Toward a knowledge‐based theory of the firm. Strategic Management

Journal, 17(S2), 109-122.

Green, S. G., Welsh, M. A., & Dehler, G. E. (2003). Advocacy, performance, and threshold

influences on decisions to terminate new product development. Academy of Management

Journal, 46(4), 419-434.

Guan, J., & Ma, N. (2003). Innovative capability and export performance of Chinese firms.

Technovation, 23(9), 737-747.

Gupta, A. K., Smith, K. G., & Shalley, C. E. (2006). The interplay between exploration and

exploitation. Academy of Management Journal, 49(4), 693-706.

Hacklin, F., Björkdahl, J., & Wallin, M. W. (2018). Strategies for business model innovation: How

firms reel in migrating value. Long range planning, 51(1), 82-110.

Hair, J. F. (2010). Black, WC, Babin, BJ, & Anderson, RE (2010). Multivariate data analysis, 7.

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2012). Partial least squares: the better approach to

structural equation modeling?. Long Range Planning, 45(5-6), 312-319.

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling:

Rigorous applications, better results and higher acceptance. Long range planning, 46(1-2),

1-12.

Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial

least squares structural equation modeling in marketing research. Journal of the academy

of marketing science, 40(3), 414-433.


168

Hambrick, D. C., & Mason, P. A. (1984). Upper echelons: The organization as a reflection of its

top managers. Academy of management review, 9(2), 193-206.

Hamel, G. (2001). Leading the revolution: An interview with Gary Hamel. Strategy &

Leadership, 29(1), 4-10.

Hao, S., & Yu, B. (2011). The impact of technology selection on innovation success and

organizational performance. Ibusiness, 3(04), 366.

Hao, S., & Yu, B. (2011). The impact of technology selection on innovation success and

organizational performance. Ibusiness, 3(04), 366.

Harrison, R., & Mason, C. (1992). The role of investors in entrepreneurial companies: a

comparison of informal investors and venture capitalists: University of Southampton,

Urban Policy Research Unit.

Hart, S. L. (1992). An integrative framework for strategy-making processes. Academy of

management review, 17(2), 327-351.

Hauschildt, J. (1999). Opposition to innovations—destructive or constructive? The dynamics of

innovation (pp. 213-236): Springer.

Hauschildt, J., & Schewe, G. (2000). Gatekeeper and process promotor: key persons in agile and

innovative organizations. International Journal of Agile Management Systems, 2(2), 96-

103.

Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A

regression-based approach. Guilford Publications.

Hayes, A. F. (2018). Partial, conditional, and moderated moderated mediation: Quantification,

inference, and interpretation. Communication Monographs, 85(1), 4-40.

He, Z.-L., & Wong, P.-K. (2004). Exploration vs. exploitation: An empirical test of the

ambidexterity hypothesis. Organization science, 15(4), 481-494.

Hedman, J., & Kalling, T. (2003). The business model concept: theoretical underpinnings and

empirical illustrations. European journal of information systems, 12(1), 49-59.

Hernández-Espallardo, M., Sánchez-Pérez, M., & Segovia-López, C. (2011). Exploitation-and

exploration-based innovations: the role of knowledge in inter-firm relationships with


169

distributors. Technovation, 31(5-6), 203-215.

Hertog, P. d. (2000). Knowledge-intensive business services as co-producers of innovation.

International Journal of Innovation Management, 4(04), 491-528.

Hii, J., & Neely, A. (2000). Innovative capacity of firms: on why some firms are more innovative

than others.

Hinterhuber, A., & Liozu, S. M. (2014). Is innovation in pricing your next source of competitive

advantage? Business Horizons, 57(3), 413-423.

Hitt, M. A., Bierman, L., Shimizu, K., & Kochhar, R. (2001). Direct and moderating effects of

human capital on strategy and performance in professional service firms: A resource-based

perspective. Academy of Management Journal, 44(1), 13-28.

Hitt, M. A., Ireland, R. D., Camp, S. M., & Sexton, D. L. (2001). Strategic entrepreneurship:

Entrepreneurial strategies for wealth creation. Strategic Management Journal, 22(6‐7),

479-491.

Hitt, M. A., Ireland, R. D., Sirmon, D. G., & Trahms, C. A. (2011). Strategic entrepreneurship:

creating value for individuals, organizations, and society. Academy of management

perspectives, 25(2), 57-75.

Hoffman, P. J., Festinger, L., & Lawrence, D. H. (1954). Tendencies toward group comparability

in competitive bargaining. Human Relations, 7(2), 141-159.

Hofstede, G. (2001). Culture's consequences: Comparing values, behaviors, institutions and

organizations across nations: Sage publications.

Hogan, S. J., Soutar, G. N., McColl-Kennedy, J. R., & Sweeney, J. C. (2011). Reconceptualizing

professional service firm innovation capability: Scale development. Industrial Marketing

Management, 40(8), 1264-1273.

Holcomb, T. R., Ireland, R. D., Holmes Jr, R. M., & Hitt, M. A. (2009). Architecture of

entrepreneurial learning: Exploring the link among heuristics, knowledge, and action.


Hoopes, D. G., Madsen, T. L., & Walker, G. (2003). Guest editors' introduction to the special

issue: why is there a resource‐based view? Toward a theory of competitive heterogeneity.

Strategic Management Journal, 24(10), 889-902.


170

Hossain, M. (2018). Business model innovation: past research, current debates, and future

directions. Journal of Strategy and Management, 10(3), 342-359.

Huarng, K.-H., & Ribeiro-Soriano, D. E. (2014). Developmental management: Theories, methods,

and applications in entrepreneurship, innovation, and sensemaking. Journal of Business

Research, 67(5), 657-662.

Huarng, K.-H., Cervera, A., & Mas-Verdu, F. (2018). Innovation and service-dominant logic:

Springer.

Hult, G. T. M., & Ketchen Jr, D. J. (2001). Does market orientation matter?: A test of the

relationship between positional advantage and performance. Strategic management

journal, 22(9), 899-906.

Hurley, R. F., & Hult, G. T. M. (1998). Innovation, market orientation, and organizational learning:

an integration and empirical examination. The Journal of Marketing, 42-54.

Hwang, E. H., Singh, P. V., & Argote, L. (2015). Knowledge sharing in online communities:

Learning to cross geographic and hierarchical boundaries. Organization science, 26(6),

1593-1611.

Iddris, F. (2016). Measurement of innovation capability in supply chain: an exploratory study.

International Journal of Innovation Science, 8(4), 331-349.

Ireland, R. D., & Webb, J. W. (2009). Crossing the great divide of strategic entrepreneurship:

Transitioning between exploration and exploitation. Business horizons, 52(5), 469-479.

Ireland, R. D., Hitt, M. A., & Sirmon, D. G. (2003). A model of strategic entrepreneurship: The

construct and its dimensions. Journal of management, 29(6), 963-989.

Ireland, R. D., Hitt, M. A., & Sirmon, D. G. (2003). A model of strategic entrepreneurship: The

construct and its dimensions. Journal of management, 29(6), 963-989.

Johne, A., & Storey, C. (1998). New service development: a review of the literature and annotated

bibliography. European journal of Marketing, 32(3/4), 184-251.

Johnson, G., Scholes, K., & Whittington, R. (2008). Exploring corporate strategy: text & cases:

Pearson education.

Jöreskog, K. G., & Sörbom, D. (1993). LISREL 8: Structural equation modeling with the SIMPLIS


171

command language: Scientific Software International.

Kallio, A., Kujansivu, P., & Parjanen, S. (2012). Locating the weak points of innovation capability

before launching a development project. Interdisciplinary Journal of Information,

Knowledge, and Management, 7(1), 21-38.

Kamoche, K. (1996). Strategic human resource management within a resource‐capability view of

the firm. Journal of Management studies, 33(2), 213-233.

Kang, S. C., & Snell, S. A. (2009). Intellectual capital architectures and ambidextrous learning: a

framework for human resource management. Journal of Management studies, 46(1), 65-

92.

Kanter, R. M. (1984). Change masters: Simon and Schuster.

Keen, P. G. (1981). Value analysis: justifying decision support systems. MIS quarterly, 1-15.

Kegan, R., & Lahey, L. L. (2001). The real reason people won’t change. HBR’s 10 Must Reads on

Change, 77.

Kelloway, E. K. (1998). Using LISREL for structural equation modeling: A researcher's guide:

Sage.

Kenny, D. A. (2014). Measuring model fit.

Keskin, H. (2006). Market orientation, learning orientation, and innovation capabilities in SMEs:

An extended model. European Journal of innovation management, 9(4), 396-417.

Kiani, M. N., & Gillani, S. H. M. (2014). The impact of learning organization practices on

organizational effectiveness. PAKISTAN BUSINESS REVIEW, 248.

Kim, J., Lee, S., Geum, Y., & Park, Y. (2012). Patterns of innovation in digital content services:

The case of App Store applications. Innovation, 14(4), 540-556.

Kim, W. C., & Mauborgne, R. (2004). Blue ocean strategy. If you read nothing else on strategy,

read thesebest-selling articles., 71.

King, D. R., Dalton, D. R., Daily, C. M., & Covin, J. G. (2004). Meta‐analyses of post‐acquisition

performance: Indications of unidentified moderators. Strategic Management Journal,

25(2), 187-200.

Knight, G. A., & Cavusgil, S. T. (2004). Innovation, organizational capabilities, and the born-


172

global firm. Journal of international business studies, 35(2), 124-141.

Knowles, C., Hansen, E., & Dibrell, C. (2008). Measuring firm innovativeness: Development and

refinement of a new scale. Journal of Forest Products Business Research, 5(5), 1-24.

Koen, P. A., Bertels, H. M., & Elsum, I. R. (2011). The three faces of business model innovation:

Challenges for established firms. Research-Technology Management, 54(3), 52-59.

Kogut, B., & Zander, U. (1992). Knowledge of the firm, combinative capabilities, and the

replication of technology. Organization science, 3(3), 383-397.

Kotabe, M., Srinivasan, S. S., & Aulakh, P. S. (2002). Multinationality and firm performance: The

moderating role of R&D and marketing capabilities. Journal of international business

studies, 33(1), 79-97.

Koufteros, X. A. (1999). Testing a model of pull production: a paradigm for manufacturing

research using structural equation modeling. Journal of Operations Management, 17(4),

467-488.

Kowalkowski, C., Kindström, D., & Brehmer, P.-O. (2011). Managing industrial service offerings

in global business markets. Journal of Business & Industrial Marketing, 26(3), 181-192.

Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities.

Educational and psychological measurement, 30(3), 607-610.

Kungu, G., Desta, I., & Ngui, T. (2014). An assessment of the effectiveness of competitive

strategies by commercial banks: A case of Equity bank. International Journal of Education

and Research, 2(12), 333-346.

Lambert, S. C., & Davidson, R. A. (2013). Applications of the business model in studies of

enterprise success, innovation and classification: An analysis of empirical research from

1996 to 2010. European Management Journal, 31(6), 668-681.

Lau, C. M., & Woodman, R. W. (1995). Understanding organizational change: A schematic

perspective. Academy of management journal, 38(2), 537-554.

Lawson, B., & Samson, D. (2001). Developing innovation capability in organisations: a dynamic

capabilities approach. International Journal of Innovation Management, 5(03), 377-400.

Lenfle, S., & Midler, C. (2009). The launch of innovative product-related services: lessons from


173

automotive telematics. Research policy, 38(1), 156-169.

Lewin, K. (1951). Field theory in social science (D. Cartwright, Ed.). New York, 165.

Liao, S.-H., Fei, W.-C., & Chen, C.-C. (2007). Knowledge sharing, absorptive capacity, and

innovation capability: an empirical study of Taiwan's knowledge-intensive industries.

Journal of information science, 33(3), 340-359.

Lichtenthaler, U. (2009). Absorptive capacity, environmental turbulence, and the complementarity

of organizational learning processes: Academy of Management Briarcliff Manor, NY.

Lichtenthaler, U., & Lichtenthaler, E. (2009). A capability‐based framework for open innovation:

Complementing absorptive capacity. Journal of Management studies, 46(8), 1315-1338.

Loon, M., & Chik, R. (2018). Efficiency-centered, innovation-enabling business models of high

tech SMEs: Evidence from Hong Kong. Asia Pacific Journal of Management, 1-25.

Lumpkin, G. T., & Dess, G. G. (1996). Clarifying the entrepreneurial orientation construct and

linking it to performance. Academy of management review, 21(1), 135-172.

Lund Vinding, A. (2006). Absorptive capacity and innovative performance: A human capital

approach. Economics of Innovation and New Technology, 15(4-5), 507-517.

Maglio, P. P., & Spohrer, J. (2014). A service science perspective on business model innovation.

Industrial Marketing Management, 42(5), 665-670.

Makadok, R. (2001). Toward a synthesis of the resource‐based and dynamic‐capability views of

rent creation. Strategic Management Journal, 22(5), 387-401.

Malhotra, Y. (2000). Knowledge management for e-business performance: advancing information

strategy to “internet time”. Information Strategy: The Executive's Journal, 16(4), 5-16.

Marsh, H. W., & Hocevar, D. (1985). Application of confirmatory factor analysis to the study of

self-concept: First-and higher order factor models and their invariance across groups.

Psychological bulletin, 97(3), 562.

Martinez-Roman, J. A., Gamero, J., & Tamayo, J. A. (2011). Analysis of innovation in SMEs

using an innovative capability-based non-linear model: A study in the province of Seville

(Spain). Technovation, 31(9), 459-475.

Mazzei, M. J., Ketchen, D. J., & Shook, C. L. (2017). Understanding strategic entrepreneurship: a


174

“theoretical toolbox” approach. International Entrepreneurship and Management

Journal, 13(2), 631-663.

McClelland, D. C. (1961). The achievement society. Princenton, NJ: Von Nostrand.

McGrath, R. G. (2010). Business models: A discovery driven approach. Long range planning,

43(2-3), 247-261.

Mennens, K., Van Gils, A., Odekerken-Schröder, G., & Letterie, W. (2018). Exploring antecedents

of service innovation performance in manufacturing SMEs. International Small Business

Journal, 0266242617749687.

Menor, L. J., & Roth, A. V. (2007). New service development competence in retail banking:

Construct development and measurement validation. Journal of Operations Management,

25(4), 825-846.

Menor, L. J., Tatikonda, M. V., & Sampson, S. E. (2002). New service development: areas for

exploitation and exploration. Journal of Operations Management, 20(2), 135-157.

Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: The concept and its measurement.

Journal of consumer research, 4(4), 229-242.

Miles, I. (1993). Services in the new industrial economy. Futures, 25(6), 653-672.

Miller, D., & Friesen, P. H. (1982). Innovation in conservative and entrepreneurial firms: Two

models of strategic momentum. Strategic Management Journal, 3(1), 1-25.

Miller, D., & Le Breton–Miller, I. (2011). Governance, social identity, and entrepreneurial

orientation in closely held public companies. Entrepreneurship Theory and

practice, 35(5), 1051-1076.

Mintzberg, H. (2017). Planning on the left side, managing on the right Leadership Perspectives

(pp. 413-426): Routledge.

Mitchell, D., & Coles, C. (2003). The ultimate competitive advantage of continuing business

model innovation. Journal of business strategy, 24(5), 15-21.

Mitnick, B. M. (1975). The theory of agency. Public Choice, 24(1), 27-42.

Mitnick, B. M. (1982). REGULATION AND THE THEORY OF AGENCY 1. Review of Policy

Research, 1(3), 442-453.


175

Mom, T. J., Van Den Bosch, F. A., & Volberda, H. W. (2007). Investigating managers' exploration

and exploitation activities: The influence of top‐down, bottom‐up, and horizontal

knowledge inflows. Journal of Management studies, 44(6), 910-931.

Momeni, M., Nielsen, S. B., & Kafash, M. H. (2015). Determination of Innovation Capability of

Organizations: Qualitative Meta Synthesis and Delphi Method. Proceedings of

RESER2015-Innovative Services in the 21st Century.

Morris, M. H., Webb, J. W., & Franklin, R. J. (2011). Understanding the manifestation of

entrepreneurial orientation in the nonprofit context. Entrepreneurship theory and practice,

35(5), 947-971.

Morris, M., Schindehutte, M., & Allen, J. (2005). The entrepreneur's business model: toward a

unified perspective. Journal of Business Research, 58(6), 726-735.

Nachtigall, C., Kroehne, U., Funke, F., & Steyer, R. (2003). Pros and cons of structural equation

modeling. Methods Psychological Research Online, 8(2), 1-22.

Narcizo, R. B., Canen, A. G., & Tammela, I. (2017). A conceptual framework to represent the

theoretical domain of “innovation capability” in organizations.

Narver, J. C., Slater, S. F., & Tietje, B. (1998). Creating a market orientation. Journal of market-

focused management, 2(3), 241-255.

Neely, A., Filippini, R., Forza, C., Vinelli, A., & Hii, J. (2001). A framework for analysing

business performance, firm innovation and related contextual factors: perceptions of

managers and policy makers in two European regions. Integrated manufacturing systems,

12(2), 114-124.

Nijssen, E. J., Hillebrand, B., Vermeulen, P. A., & Kemp, R. G. (2006). Exploring product and

service innovation similarities and differences. International Journal of Research in

Marketing, 23(3), 241-251.

Nilsson, F., Regnell, B., Larsson, T., & Ritzén, S. (2010). Measuring for innovation-A guide for

innovative teams. Applied Innovation Management(3).

Nisula, A.-M., & Kianto, A. (2013). Evaluating and developing innovation capabilities with a

structured method. IJIKM, 8.

O'Connor, G. C. (2008). Major innovation as a dynamic capability: A systems approach. Journal


176

of Product Innovation Management, 25(4), 313-330.

Oreg, S. (2003). Resistance to change: Developing an individual differences measure. Journal of

applied psychology, 88(4), 680.

Oreg, S. (2006). Personality, context, and resistance to organizational change. European journal

of work and organizational psychology, 15(1), 73-101.

Oreg, S., & Sverdlik, N. (2011). Ambivalence toward imposed change: The conflict between

dispositional resistance to change and the orientation toward the change agent. Journal of

Applied Psychology, 96(2), 337.

Oreg, S., Bayazit, M., Vakola, M., Arciniega, L., Armenakis, A., Barkauskiene, R., ... &

Hřebíčková, M. (2008). Dispositional resistance to change: Measurement equivalence and

the link to personal values across 17 nations. Journal of Applied Psychology, 93(4), 935.

Ostrom, A. L., Bitner, M. J., Brown, S. W., Burkhard, K. A., Goul, M., Smith-Daniels, V.,

Rabinovich, E. (2010). Moving forward and making a difference: research priorities for the

science of service. Journal of Service Research, 13(1), 4-36.

Page, A. L., & Schirr, G. R. (2008). Growth and development of a body of knowledge: 16 years

of new product development research, 1989–2004. Journal of Product Innovation

Management, 25(3), 233-248.

Parkman, I. D., Holloway, S. S., & Sebastiao, H. (2012). Creative industries: aligning

entrepreneurial orientation and innovation capacity. Journal of Research in Marketing and

Entrepreneurship, 14(1), 95-114.

Pearce, J. A., Fritz, D. A., & Davis, P. S. (2010). Entrepreneurial orientation and the performance

of religious congregations as predicted by rational choice theory. Entrepreneurship theory

and practice, 34(1), 219-248.

Pelham, A. M. (1997). Mediating influences on the relationsmp between market orientation and

profitability in small industrial firms. Journal of Marketing Theory and Practice, 5(3), 55-

76.

Penrose, E., & Penrose, E. T. (2009). The Theory of the Growth of the Firm: Oxford university

press.

Pisano, G. P. (1994). Knowledge, integration, and the locus of learning: An empirical analysis of


177

process development. Strategic Management Journal, 15(S1), 85-100.

Porter, M. E., Michael, & Gibbs, i. (2001). Strategy and the Internet.

Preissl, B. (2000). Service innovation: what makes it different? Empirical evidence from Germany.

In Innovation systems in the service economy (pp. 125-148). Springer, Boston, MA.

Priem, R. L., & Butler, J. E. (2001). Is the resource-based “view” a useful perspective for strategic

management research? Academy of management review, 26(1), 22-40.

Proctor, T. (2014). Strategic marketing: an introduction: Routledge.

PTA. (2018). PTA Annual Report 2018. Islamabad.

Raisch, S., Birkinshaw, J., Probst, G., & Tushman, M. L. (2009). Organizational ambidexterity:

Balancing exploitation and exploration for sustained performance. Organization science,

20(4), 685-695.

Rangus, K., & Slavec, A. (2017). The interplay of decentralization, employee involvement and

absorptive capacity on firms' innovation and business performance. Technological

Forecasting and Social Change.

Rauch, A., Wiklund, J., Lumpkin, G. T., & Frese, M. (2009). Entrepreneurial orientation and

business performance: An assessment of past research and suggestions for the future.


Reinhold, O., & Alt, R. (2012). Social Customer Relationship Management: State of the Art and

Learnings from Current Projects. Paper presented at the Bled eConference.

Richardson, G. B. (2003). The organization of industry re-visited. Paper presented at the DRUID

Summer Conference.

Richter, M. (2013). Business model innovation for sustainable energy: German utilities and

renewable energy. Energy Policy, 62, 1226-1237.

Robbins, P., & O'Gorman, C. (2015). Innovating the innovation process: an organisational

experiment in global pharma pursuing radical innovation. R&D Management, 45(1), 76-

93.

Romijn, H., & Albaladejo, M. (2002). Determinants of innovation capability in small electronics

and software firms in southeast England. Research policy, 31(7), 1053-1067.


178

Roscoe, J. T. (1975). Fundamental research statistics for the behavioral sciences [by] John T.

Roscoe.

Rousseau, D. (1995). Psychological contracts in organizations: Understanding written and

unwritten agreements. Sage publications.

Saebi, T., & Foss, N. J. (2015). Business models for open innovation: Matching heterogeneous

open innovation strategies with business model dimensions. European Management

Journal, 33(3), 201-213.

Saebi, T., Lien, L., & Foss, N. J. (2017). What drives business model adaptation? The impact of

opportunities, threats and strategic orientation. Long range planning, 50(5), 567-581.

Santos, F. M. (2012). A positive theory of social entrepreneurship. Journal of business ethics,

111(3), 335-351.

Santos, F. M., & Eisenhardt, K. M. (2009). Constructing markets and shaping boundaries:

Entrepreneurial power in nascent fields. Academy of Management Journal, 52(4), 643-671.

Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students: Pearson

education.

Saunila, M. (2014). Innovation capability for SME success: perspectives of financial and

operational performance. Journal of Advances in Management Research, 11(2), 163-175.

Sborn, A. (1992). Foster innovation and creative talent for the public, translated by Hasan

GhasemZadeh. Tehran: Niloofar Pub.

Schirmer, M., Hartmann, J., Bertel, S., & Echtler, F. (2015). Shoe me the way: a shoe-based tactile

interface for eyes-free urban navigation. Paper presented at the Proceedings of the 17th

International Conference on Human-Computer Interaction with Mobile Devices and

Services.

Schneider, S., & Spieth, P. (2013). Business model innovation: Towards an integrated future

research agenda. International Journal of Innovation Management, 17(01), 1340001.

Schreyögg, G., & Kliesch‐Eberl, M. (2007). How dynamic can organizational capabilities be?

Towards a dual‐process model of capability dynamization. Strategic Management Journal,

28(9), 913-933.


179

Selznick, P. (2011). Leadership in administration: A sociological interpretation: Quid Pro Books.

Sirmon, D. G., Hitt, M. A., Ireland, R. D., & Gilbert, B. A. (2011). Resource orchestration to create

competitive advantage: Breadth, depth, and life cycle effects. Journal of management,

37(5), 1390-1412.

Smith, M., Busi, M., Ball, P., & Van der Meer, R. (2008). Factors influencing an organisation's

ability to manage innovation: a structured literature review and conceptual model.

International Journal of Innovation Management, 12(04), 655-676.

Snow, C. C., & Hrebiniak, L. G. (1980). Strategy, distinctive competence, and organizational

performance. Administrative science quarterly, 317-336.

Soltani Tirani, F. (1999). Institutional Innovation in Organizations. the Institute for Cultural

Services Resa Publishing-Printing, 10, 2310-0079.

Song, M., Nason, R. W., & Di Benedetto, C. A. (2008). Distinctive marketing and information

technology capabilities and strategic types: A cross-national investigation. Journal of

International Marketing, 16(1), 4-38.

Sousa-Zomer, T. T., & Cauchick-Miguel, P. A. (2019). Exploring business model innovation for

sustainability: an investigation of two product-service systems. Total Quality Management

& Business Excellence, 30(5-6), 594-612.

Spieth, P., & Meissner Née Schuchert, S. (2018). Business Model Innovation Alliances: How To

Open Business Models For Cooperation. International Journal of Innovation Management,

22(04), 1850042.

Spieth, P., & Schneider, S. (2016). Business model innovativeness: designing a formative measure

for business model innovation. Journal of business Economics, 86(6), 671-696.

Spieth, P., Schneckenberg, D., & Matzler, K. (2016). Exploring the linkage between business

model (&) innovation and the strategy of the firm. R&D Management, 46(3), 403-413.

Spieth, P., Schneckenberg, D., & Ricart, J. E. (2014). Business model innovation–state of the art

and future challenges for the field. R&D Management, 44(3), 237-247.

Srivastava, S. C., & Shainesh, G. (2015). Bridging the Service Divide Through Digitally Enabled

Service innovations; Evidence from Indian Health Care Service Providers. MIS Q, 39(1).


180

Stambaugh, J. E., Yu, A., & Dubinsky, A. J. (2011). Before the attack: a typology of strategies for

competitive aggressiveness. Journal of Management Policy and Practice, 12(1), 49.

Storey, C., & Hull, F. M. (2010). Service development success: a contingent approach by

knowledge strategy. Journal of service Management, 21(2), 140-161.

Story, V. M., Raddats, C., Burton, J., Zolkiewski, J., & Baines, T. (2017). Capabilities for

advanced services: A multi-actor perspective. Industrial Marketing Management, 60, 54-

68.

Strebel, P. (1996). Why do employees resist change?. Harvard business review, 74(3), 86.

Subramaniam, M., & Youndt, M. A. (2005). THE INFLUENCE OF INTELLECTUAL CAPITAL

ON THE TYPES OF INNOVATIVE CAPABILITIES. [Article]. Academy of Management

Journal, 48(3), 450-463. doi: 10.5465/amj.2005.17407911

Sundbo, J. (1996). The balancing of empowerment. A strategic resource based model of organizing

innovation activities in service and low-tech firms. Technovation, 16(8), 397445-409446.

Swink, M., & Harvey Hegarty, W. (1998). Core manufacturing capabilities and their links to

product differentiation. International Journal of Operations & Production Management,

18(4), 374-396.

Tanaka, J. S., & Huba, G. J. (1985). A fit index for covariance structure models under arbitrary

GLS estimation. British Journal of Mathematical and Statistical Psychology, 38(2), 197-

201.

Tavassoli, M., Faramarzi, G. R., & Saen, R. F. (2014). Efficiency and effectiveness in airline

performance using a SBM-NDEA model in the presence of shared input. Journal of Air

Transport Management, 34, 146-153.

Teece, D. J. (2010). Business models, business strategy and innovation. Long range planning,

43(2-3), 172-194.

Teece, D. J. (2012). Dynamic capabilities: Routines versus entrepreneurial action. Journal of

Management studies, 49(8), 1395-1401.

Teece, D. J. (2018). Business models and dynamic capabilities. Long range planning, 51(1), 40-

49.


181

Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management.

Strategic Management Journal, 18(7), 509-533.

Terziovski, M. (2007). Building innovation capability in organizations: An international cross-

case perspective (Vol. 13): Imperial College Press.

Tether, B. S. (2003). The sources and aims of innovation in services: variety between and within

sectors. Economics of Innovation and New Technology, 12(6), 481-505.

Tian, L., & Wilding, G. E. (2008). Confidence interval estimation of a common correlation

coefficient. Computational statistics & data analysis, 52(10), 4872-4877.

Tidd, J., Bessant, J., & Pavitt, K. (2005). Managing innovation integrating technological, market

and organizational change: John Wiley and Sons Ltd.

Toivonen, M., & Tuominen, T. (2009). Emergence of innovations in services. The Service

Industries Journal, 29(7), 887-902.

Tonnessen, T. (2005). Continuous innovation through company wide employee participation. The

TQM Magazine, 17(2), 195-207.

Trapp, M., Voigt, K.-I., & Brem, A. (2018). Business models for corporate innovation

management: Introduction of a business model innovation tool for established firms.

International Journal of Innovation Management, 22(01), 1850007.

Valter, P., Lindgren, P., & Prasad, R. (2018). Valter’s Seven Forces; a Model for Analyzing the

Forces Affecting the Business Model Innovation Process. Nordic and Baltic Journal of

Information and Communications Technologies, 2018(1), 47-64.

Van Leeuwen, G., & Klomp, L. (2006). On the contribution of innovation to multi-factor

productivity growth. Economics of Innovation and New Technology, 15(4-5), 367-390.

Van Riel, A. C., & Lievens, A. (2004). New service development in high tech sectors: A decision-

making perspective. International Journal of Service Industry Management, 15(1), 72-101.

Van Riel, A. C., Lemmink, J., & Ouwersloot, H. (2004). High‐technology service innovation

success: a decision‐making perspective. Journal of Product Innovation

Management, 21(5), 348-359.

Van Riel, A. C., Lemmink, J., & Ouwersloot, H. (2004). High‐technology service innovation


182

success: a decision‐making perspective. Journal of Product Innovation Management,

21(5), 348-359.

Velu, C. (2016). Evolutionary or revolutionary business model innovation through coopetition?

The role of dominance in network markets. Industrial Marketing Management, 53, 124-

135.

Verhees, F. J., & Meulenberg, M. T. (2004). Market orientation, innovativeness, product

innovation, and performance in small firms. Journal of small business management, 42(2),

134-154.

Wales, W. J. (2016). Entrepreneurial orientation: A review and synthesis of promising research

directions. International Small Business Journal, 34(1), 3-15.

Wang, C.-h., Lu, I.-y., & Chen, C.-b. (2008). Evaluating firm technological innovation capability

under uncertainty. Technovation, 28(6), 349-363.

Watanabe, K., Fukuda, K., & Nishimura, T. (2015). A technology-assisted design methodology

for employee-driven innovation in services. Technology Innovation Management Review,

5(2).

Wernerfelt, B. (1984). A resource‐based view of the firm. Strategic Management Journal, 5(2),

171-180.

Wiklund, J., & Shepherd, D. (2005). Entrepreneurial orientation and small business performance:

a configurational approach. Journal of Business Venturing, 20(1), 71-91.

Wiklund, J., & Shepherd, D. A. (2008). Portfolio entrepreneurship: Habitual and novice founders,

new entry, and mode of organizing. Entrepreneurship theory and practice, 32(4), 701-725.

Wirtz, B. W., Pistoia, A., Ullrich, S., & Göttel, V. (2016). Business models: Origin, development

and future research perspectives. Long range planning, 49(1), 36-54.

Witell, L., & Löfgren, M. (2013). From service for free to service for fee: business model

innovation in manufacturing firms. Journal of service Management, 24(5), 520-533.

Witell, L., Anderson, L., Brodie, R. J., Colurcio, M., Edvardsson, B., Kristensson, P., . . . Wallin

Andreassen, T. (2015). Exploring dualities of service innovation: implications for service

research. Journal of Services Marketing, 29(6/7), 436-441.


183

Yam, R. C., Guan, J. C., Pun, K. F., & Tang, E. P. (2004). An audit of technological innovation

capabilities in Chinese firms: some empirical findings in Beijing, China. Research policy,

33(8), 1123-1140.

Yam, R. C., Lo, W., Tang, E. P., & Lau, A. K. (2011). Analysis of sources of innovation,

technological innovation capabilities, and performance: An empirical study of Hong Kong

manufacturing industries. Research policy, 40(3), 391-402.

Yıldız, S., Baştürk, F., & Boz, İ. T. (2014). The effect of leadership and innovativeness on business

performance. Procedia-Social and Behavioral Sciences, 150, 785-793.

Yoo, W.-J., Choo, H., & Lee, S. (2018). A Study on the sustainable growth of SMEs: The

mediating role of organizational metacognition. Sustainability, 10(8), 2829.

Yunus, M., Moingeon, B., & Lehmann-Ortega, L. (2010). Building social business models:

Lessons from the Grameen experience. Long range planning, 43(2-3), 308-325.

Zack, M., McKeen, J., & Singh, S. (2009). Knowledge management and organizational

performance: an exploratory analysis. Journal of knowledge management, 13(6), 392-409.

Zahra, S. A., & Neubaum, D. O. (1998). Environmental adversity and the entrepreneurial activities

of new ventures. Journal of developmental entrepreneurship, 3(2), 123.

Zander, A. (1950). Resistance to change—its analysis and prevention. Advanced Management

Journal.

Zawislak, P. A., Cherubini Alves, A., Tello-Gamarra, J., Barbieux, D., & Reichert, F. M. (2012).

Innovation capability: From technology development to transaction capability. Journal of

technology management & innovation, 7(2), 14-27.

Zheng, Y., Liu, J., & George, G. (2010). The dynamic impact of innovative capability and inter-

firm network on firm valuation: A longitudinal study of biotechnology start-ups. Journal

of Business Venturing, 25(6), 593-609.

Zott, C., Amit, R., & Massa, L. (2011). The business model: recent developments and future

research. Journal of management, 37(4), 1019-1042.

Zwick, T. (2002). Employee resistance against innovations. International journal of Manpower,

23(6), 542-552.


184

APPENDIX - I

RESEARCH SURVEY QUESTIONNAIRE

Respected Sir / Madam,

I am a PhD (scholar) from SZABIST Islamabad, pursuing my degree in Management Sciences program. It is

requested to please fill in this questionnaire to be carried for my dissertation work. I would like to inform you

that the information provided on this questionnaire solely for research purpose and it will be held confidential.

Thank you for your precious time!

A) Service Innovation Capabilities

How much do you agree with each statement?

1 ___________2_________3____________________4___________5__________6____________7

Strongly Disagree Disagree Slightly Disagree Neutral Slightly Agree Agree Strongly Agree

Sensing user needs

1 We systematically observe and evaluate the need of our customers 1 2 3 4 5 6 7

2 We analyze the actual use of our services 1 2 3 4 5 6 7

3 Our organization is strong in distinguishing different groups of users

and market segments 1 2 3 4 5 6 7

Sensing technological options

4 Staying up to date with promising new services and technologies is

important for our organization 1 2 3 4 5 6 7

5 In order to identify the possibilities for new services, we use different

information sources 1 2 3 4 5 6 7

6 We follow which technologies our competitors use 1 2 3 4 5 6 7

Conceptualizing

7 We are innovative in coming up with ideas for new service concepts 1 2 3 4 5 6 7

8 Our organization experiments with new service concepts 1 2 3 4 5 6 7

9 We align new service offerings with our current business and

processes 1 2 3 4 5 6 7

Coproducing and orchestrating

10 Collaborations with other organizations helps us in improving or

introducing new services 1 2 3 4 5 6 7

11 Our organization is strong in coordinating service innovation

activities involving several parties 1 2 3 4 5 6 7

12 Our organization is efficient in initiatives and maintaining the

partnerships 1 2 3 4 5 6 7

Scaling and stretching


185

13 In the development of new services, we take into account our

branding strategy 1 2 3 4 5 6 7

14 Our organization is actively engaged in promoting its new services 1 2 3 4 5 6 7

15 We introduce new services by following our marketing plan 1 2 3 4 5 6 7

B) Service Innovation Success


1 ___________2_________3____________________4___________5__________6____________7


Short term success

16 The new service is an overall success 1 2 3 4 5 6

17 Success exceeds expectations. 1 2 3 4 5 6

18 The new service contributed to financial success 1 2 3 4 5 6

19 The new service was a good idea to invest in 1 2 3 4 5 6

20 The new service adds substantial value to other products and

services 1 2 3 4 5 6

Long term success

21 The new service contributed to commercial success. 1 2 3 4 5 6

22 The new service improved our competitive position. 1 2 3 4 5 6

23 The new service improved brand equity and reputation. 1 2 3 4 5 6

24 The new service enabled expansion into new markets 1 2 3 4 5 6

25 The new service increased customer satisfaction and loyalty 1 2 3 4 5 6

Indirect success

26 The new service increased in-house technological knowledge 1 2 3 4 5 6

27 The new service increased employee satisfaction. 1 2 3 4 5 6

28 The new service created innovation opportunities 1 2 3 4 5 6

C) Management Entrepreneurial Orientation


1 ___________2_________3____________________4___________5__________6____________7


Ready to Innovate

29. In general, the top managers of our organization favor a strong emphasis on

research and development, technological leadership and innovations. 1 2 3 4 5 6 7


186

30. In the past five years, our organization has marketed a large variety of new lines of

products or services. 1 2 3 4 5 6 7

31. In the past five years, changes in our product or service lines have been mostly of

a minor nature (reverse coded) 1 2 3 4 5 6 7

Aggressively Competitiveness

32. In dealing with competitors, our organization often leads the competition,

initiating actions to which our competitors have to respond. 1 2 3 4 5 6 7

33. In dealing with competitors, our organization typically adopts a very competitive

posture aiming at overtaking the competitors. 1 2 3 4 5 6 7

Market Proactiveness

34. In general, the top managers of my organization have a strong propensity for high

risk projects (with chances of high return) 1 2 3 4 5 6 7

35. The top managers believe owing to the nature of environment, bold, wide-ranging

acts are necessary to achieve our organization objectives 1 2 3 4 5 6 7

36. When there is uncertainty, our organization typically adopts a “wait and see”

posture in order to minimize the probability of making costly decisions (reverse coded) 1 2 3 4 5 6 7

Risk Taking

37. Management actively responds to the adoption of “new ways of doing things” by

main competitors 1 2 3 4 5 6 7

38. We are willing to try new ways of doing things and seek usual, novel solutions. 1 2 3 4 5 6 7

39. We encourage people to think and behave in original and novel ways. 1 2 3 4 5 6 7

D) Employee Resistance


1 _______________2____________3______________4______________5_____________6

Strongly Disagree Disagree Slightly Disagree Slightly Agree Agree Strongly Agree

Routine seeking

40 I would rather be bored than surprise. 1 2 3 4 5 6

41 Generally change is not good 1 2 3 4 5 6

42 Whenever my life forms a stable routine, I look for ways to change it. 1 2 3 4 5 6

43 I prefer having a stable routine to experiencing change in my life 1 2 3 4 5 6

Emotional Reaction

44 If I were to be informed that there’s going to be a significant change

regarding the way things are done at work, I would probably feel stressed. 1 2 3 4 5 6

45

If I were to be informed that there’s going to be a change in one of my

assignment at work, prior to knowing what the change actually is, it

would probably stress me out.

1 2 3 4 5 6

46 When I am informed of a change of plans, I tense up a bit. 1 2 3 4 5 6


187

47

If my boss changed the criteria of evaluating employees, it would

probably make me feel uncomfortable even if I thought I’d do just as well

without having to do any extra work.

1 2 3 4 5 6

48

If in the middle of the work year, I were to be informed that there’s going

to be a change in schedule of deadlines, prior to knowing what the change

actually is, I would probably presume that the change is worse

1 2 3 4 5 6

Short term focus

49 Changing plans seems like a real hassle to me 1 2 3 4 5 6

50 When someone pressures me to change something, I tend to resist it even

if I think the change may ultimately benefit me. 1 2 3 4 5 6

51 Once I have made plans, I am not likely to change them. 1 2 3 4 5 6

Cognitive Rigidity

52 I don’t change my mind easily 1 2 3 4 5 6

53 I don’t often change my mind 1 2 3 4 5 6

54 My views are very consistent over time. 1 2 3 4 5 6

E) Business Model Innovation


1 _________________2_________________3____________________4_________________5

Strongly Disagree Disagree Neutral Agree Strongly

Agree

E.1 Value Creation Innovation

New capabilities

55 Our employees constantly receive training in order to develop new

competences 1 2 3 4 5

56

Relative to our direct competitors, our employees have very up-to-date

knowledge and capabilities. 1 2 3 4 5

57

We constantly reflect on which new competencies need to be established in

order to adapt to changing market requirements. 1 2 3 4 5

New technology / equipment

58 We keep the technical resources of our company up-to-date. 1 2 3 4 5

59 Relative to our competitors our technical equipment is very innovative. 1 2 3 4 5

60

We regularly utilize new technical opportunities in order to extend our product

and service portfolio. 1 2 3 4 5

New partnerships

61 We are constantly searching for new collaboration partners. 1 2 3 4 5

62

We regularly utilize opportunities that arise from integration of new partners

into our processes. 1 2 3 4 5

63 We regularly evaluate the potential benefits of outsourcing. 1 2 3 4 5

64 New collaboration partners regularly help us to further develop our business

model. 1 2 3 4 5


188

New processes

65 We were recently able to significantly improve our internal processes. 1 2 3 4 5

66

We utilize innovative procedures and processes during the manufacturing of

our products as well as in all business processes. 1 2 3 4 5

67 Existing processes are regularly assessed and significantly changed if needed. 1 2 3 4 5

E.2 Value Proposition Innovation

New offerings

68 We regularly address new unmet customer needs. 1 2 3 4 5

69 Our products or services are very innovative in relation to our competitors. 1 2 3 4 5

70

Our products or services regularly solve customer needs, which were not

solved by competitors. 1 2 3 4 5

New customers and markets

71 We regularly take opportunities that arise in new or growing markets. 1 2 3 4 5

72 We regularly address new, unserved market segments. 1 2 3 4 5

73

We are constantly seeking new customer segments and markets for our

products and services. 1 2 3 4 5

New channels

74 We regularly utilize new distribution channels for our products and services. 1 2 3 4 5

75

Constant changes of our channels have led to improved efficiency of our

channel functions. 1 2 3 4 5

76 We consistently change our portfolio of distribution channels. 1 2 3 4 5

New customer relationships

77 We try to increase customer retention by new service offerings. 1 2 3 4 5

78 We emphasize innovative/modern actions to increase customer retention (e.g.

CRM). 1 2 3 4 5

79 We recently took many actions in order to strengthen customer relationships. 1 2 3 4 5

E.3 Value Capture Innovation

New revenue models

80 We recently developed new revenue opportunities (e.g. additional sales, cross-

selling). 1 2 3 4 5

81

We increasingly offer integrated services (e.g. maintenance contracts) in order

to realize long-term financial returns. 1 2 3 4 5

82

We recently complemented or replaced one-time transaction revenues with

long-term recurring revenue models (e.g. Leasing). 1 2 3 4 5

83 We do not rely on the durability of our existing revenue sources. 1 2 3 4 5

New cost structures

84 We regularly reflect on our price-quantity strategy. 1 2 3 4 5

85 We actively seek opportunities to save manufacturing costs. 1 2 3 4 5

86

Our production costs are constantly examined and if necessary amended

according to market prices. 1 2 3 4 5

87 We regularly utilize opportunities which arise through price differentiation. 1 2 3 4 5

F) Demographics

88. Gender: Male/Female Organization: ___________________________________

89. Age: (1) Less than 30 yrs (2) 31 yrs - 40 yrs (3) Above than 40 yrs

90. Education: (1) Graduate (2) Post Graduation (3) MS/MPhil/PhD or Equivalent


189

APPENDIX - II

RESULTS OF CONFIRMATORY FACTOR ANALYSIS FOR ALL

CONSTRUCTS

Table 3.8. Results of Confirmatory Factor Analysis for All Constructs

Construct Sub-

Constructs Items

Factor

loadings

Error

term t-value

R2

(Item

reliability)

Model Fit Indices

Innovation

Capabilities

Sensing user

needs

1

2

3

.77

.83

.74

.06

.06

.07

12.84

13.84

10.57

.606

.685

.647 CMIN / df =2.01

P = .000

Absolute Fit measures:

RMSEA = .049, PCLOSE

= .758,

SRMR = .014

Incremental Fit measures:

NFI = .935, TLI = .957,

CFI = .966, GFI = .955,

AGFI = .933

Sensing

technological

options

4

5

6

.67

.74

.85

.10

.09

.08

6.70

8.22

10.62

.648

.649

.721

Conceptualiz

ation

7

8

9

.63

*Excluded

.93

.08

--

.06

7.87

--

15.5

.865

--

.699

Coproducing

and

Orchestrating

10

11

12

.69

.79

.76

.09

.08

.09

7.67

9.87

8.44

.675

.620

.685

Scaling and

Stretching

13

14

15

.69

.51

.75

.10

.09

.10

6.90

5.67

7.50

.671

**.262

.661

Innovation

Success

Short term

success

16

17

18

19

.774

.812

.745

.803

.05

.04

.06

.04

15.48

20.3

12.41

20.07

.600

.660

.654

.645

CMIN / df =2.62

P = .000



= .603,

SRMR = .069


NFI = .938, TLI = .949,

CFI = .961, GFI = .952,

AGFI = .927

Long term

success

20

21

22

23

24

25

*Excluded

.664

.567

.503

.658

.752

--

.09

.10

.08

.05

.07

--

7.38

5.67

6.29

13.16

10.74

--

.641

.621

**.253

.634

.666

Indirect

success

26

27

28

.717

.738

.863

.10

.08

.07

7.170

9.225

12.33

.614

.645

.746

Entrepreneur

ial

Orientation

Ready to

innovate

29

30

31

.810

.757

.797

.05

.06

.05

16.20

12.62

15.94

.656

.673

.636

CMIN / df =1.69

P = .003



= .828,

SRMR = .012


NFI = .962, TLI = .979,

CFI = .984, GFI = .971,

AGFI = .955

Aggressively

competitive

32

33

.931

.630

.07

.06

13.30

10.50

.867

.697

Market

Proactiveness

34

35

36

.672

.737

.843

.09

.08

.07

6.967

10.53

12.04

.652

.643

.711

Risk taking

37

38

39

.689

.792

.756

.09

.08

.09

7.656

9.900

8.400

.675

.628

.672


190

Employee

Resistance

Routine

seeking

40

41

42

43

.832

.793

.698

.753

.04

.04

.05

.04

20.80

19.82

13.90

18.83

.692

.629

**.487

.667

CMIN / df =2.29

P = .000



= .906,

SRMR = .018


NFI = .909, TLI = .935,

CFI = .946, GFI = .947,

AGFI = .926

Emotional

Reaction

44

45

46

47

48

.755

.625

.561

*Excluded

.513

.07

.07

.05

--

.04

10.79

8.929

11.22

--

12.82

.671

.690

.614

--

**.263

Short term

focus

49

50

51

.740

.687

.851

.07

.06

.05

10.57

11.45

17.02

.648

.672

.724

Cognitive

Rigidity

52

53

54

.719

.786

.753

.08

.06

.07

8.988

13.10

10.76

.617

.618

.668

Business

Model

Innovation

New

capabilities

55

56

57

.902

.979

.971

.01

.01

.01

90.2

97.9

97.1

.813

.958

.943

CMIN / df =2.37

P = .000



= .628,

SRMR = .029


NFI = .961, TLI = .965,

CFI = .985, GFI = .962,

AGFI = .951

New

technology

58

59

60

.886

.994

.999

.01

.004

.004

88.6

248.5

249.75

.785

.988

.998

New

partnerships

61

62

63

64

*Excluded

.979

.967

.977

--

.005

.006

.005

--

195.8

161.16

195.4

--

.959

.935

.954

New

processes

65

66

67

.847

.971

.973

.029

.016

.018

29.21

60.68

54.06

.718

.942

.947

New

offerings

68

69

70

.996

.971

.997

.001

.004

.001

996.0

242.75

997.0

.997

.943

.993

New

customer and

markets

71

72

73

.967

.971

.976

.007

.004

.004

138.1

242.7

244.0

.935

.942

.952

New channels

74

75

76

.973

*Excluded

.902

.005

--

.007

194.6

--

128.8

.969

--

.941

New

customer

relationships

77

78

79

.627

.847

*Excluded

.116

.036

--

5.405

23.52

--

.934

.717

--

New revenue

models

80

81

82

83

.814

.965

.964

.962

.015

.013

.014

.007

54.26

74.23

68.85

137.4

.663

.931

.929

.925

New cost

structures

84

85

86

87

.997

.871

.816

.993

.001

.022

.019

.001

997.0

39.59

42.94

993.0

.998

.758

.666

.998

Note. *Excluded = items that were previously excluded in light of EFA results and are not considered in latter stage

of construct reliability and confirmatory factor analysis. **values = possess lower item reliability and qualifies to be

dropped from final version of instrument.

Documents

Impact of Service Innovation Capabilities on Business