Secure Fuzzy Logic to Study the Impact of Knowledge ... · light on some factors that affect knowledge management such as, leadership, culture, information technology… etc. Another

International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 24 (2018) pp. 16860-16877

© Research India Publications. http://www.ripublication.com

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Secure Fuzzy Logic to Study the Impact of Knowledge Management

Enablers on Organizational Performance through Decision Making

Mediator

Omar Wassef Hijazeen 1,*, Samson Oluwaseun Fadiya 2, †, Murat Akkaya 3, † and Arif Sari 4, †

1. Researcher Management Information Systems (Girne American University) 2. Assistant Prof. Management Information Systems (Girne American University) 3. Associate Prof. Management Information Systems (Girne American University) 4. Associate Prof. Management Information Systems (Girne American University)

† These authors contributed equally to this work.

Abstract

Nowadays, organizations have realized that knowledge is

considered as a key asset to achieve strategic benefits. Since,

it helps to define the organization’s desired goal and future

vision. For a better implementation, organizations should

understand knowledge management and carefully choose the

enablers (influencing factors). Therefore, this study aims to

identify enablers that can affect successful implementation of

knowledge management, and investigate the influence of the

effective decision making (as a mediated variable) on the

relationship between knowledge management enablers and

organizational performance. In doing so, firstly questionnaires

have been randomly distributed to Jordanian and non-

Jordanian commercial banks, some by hand and others

through email. Secondly, some interviews were conducted

with a consultant of the central bank of Jordan, and other

managers in commercial banks in Jordan.Consequently, (400)

questionnaires were involved in this study, to examine the

relationships between the proposed framework’s attributes

and to test the suggested direct hypotheses. The collected data

was analysed using an artificial intelligence approach

specifically, fuzzy logic method. The result revealed that there

is a significant impact of knowledge management enablers

(cultural attributes, leadership style, employee skills and

information technology infrastructure) on the performance of

the commercial banks, using decision making as a mediator.

Keywords: knowledge management; knowledge management

enablers; decision making; organizational performance;

commercial banks in Jordan; fuzzy logic method.

1. INTRODUCTION

Knowledge management is considered as a driving force for

organizations, which indicates success or failure of the overall

performance. However, knowledge management is considered

as a new tool that has complex processes, since it contains

many factors to be implemented. (Bennett and Gabriel 1999)

claimed that, there are no specific knowledge management

enablers that can positively affect the performance. Because it

dramatically depends on some vital surrounding factors such

as, the structure of the organization, size, the nature of culture

and the environment. (Skyrme and Amidon 1997) shed the

light on some factors that affect knowledge management such

as, leadership, culture, information technology… etc. Another

study was done by (Mathi 2004) which highlighted some

other important factors that must be taken into account when

implementing knowledge management like, people, process

and information technology. However, prior studies

investigated the knowledge enablers, processes, and

organizational performance as separate factors without

studying the relationships between them (lee and choi 2003).

Moreover, they did not consider the impact of knowledge

management enablers and decision making on organizational

output simultaneously.

In order to fill this research gap, this study is trying to

investigate the relationships among the suggested knowledge

management enablers, decision making and the performance

of commercial banks in Jordan. Also it examines the influence

of these factors on each others by answering the following

research questions:

What is the impact of knowledge management

enablers on the commercial bank performance in

Jordan as mediated by decision making?

What is the impact of decision making on the

commercial bank performance in Jordan?

What is the impact of knowledge management

enablers on decision making?

Many banks strive to implement the knowledge management

effectively because it becomes a primary source for achieving

the desired goals that they aspire to. The importance of this

study lies in specifying knowledge management enablers

which are: cultural attributes, leadership style, employee skills

and information technology infrastructure. Then, it aims to

study the relationship between these factors and performance

in the banking sector with the decision making as a mediator.



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In order to allow the top management of commercial banks in

Jordan to discover the power of applying knowledge

management, and, to create knowledge among departments

and employees, which would reflect on the quality of running

processes and workflow as well and, to enhance the

application of some weak enablers, and to introduce the

practical decision making. Thereby, this study is particularly

aimed to pinpoint the following objectives:

To determine the effect of knowledge management

enablers on the commercial bank performance in

Jordan considering decision making.

To determine the effectiveness of decision making on

the commercial bank performance in Jordan.

To determine the influence of knowledge

management enablers on decision making.

2. THEORETICAL BACKGROUND OF THE STUDY

This section discusses the historical development of

knowledge management and its definition from different

perspectives. Moreover, it sheds light on some related

previous studies that examine the relation between knowledge

management enablers and organizational performance. In

addition to that, it explores the relation between decision

making and organizational performance.

2.1 What is Knowledge Management?

The term “knowledge management” was used before (2)

decades ago. In addition, the evaluation of knowledge

management was traced by many researchers (Wiig 1996;

Ponzi and Koenig 2002). (Ponzi and Koenig 2002) stated that

knowledge management was born in the early 1990s and has

grown slowly till 1995. After that, knowledge management

was growing rapidly from the year 1996 to 1999. Because

knowledge is an invisible and intangible asset, it makes the

process of measuring or managing it via traditional parameter

very difficult (Al-Adaileh and Al-Atawi 2011). However,

managing the knowledge is much more complex than

managing the information, because knowledge consists of

information along with ideas, obligations, inspirations, human

talent, capabilities and perceptions (Grey 1996). Thus, it is

difficult to find a specific definition of knowledge

management. However, some of the definitions found in the

literature are shown in the following:

(Bassi 1997) defined the knowledge management as a process

of creating, capturing and using knowledge to improve the

organizational performance. Whereas, (Liebowitz and Wilcox

1997) said that knowledge management is the ability of

organizations to manage, store, value, and distribute

knowledge. (Bayyavarapu 2005) “Knowledge management is

a set of practices and processes to acquire and apply

knowledge to facilitate organizational operations”.

(Debowski 2006) defines knowledge management as the

process of identifying, capturing, organizing and

disseminating the intellectual assets that affect the

performance of any organization for a long term. (Zaim 2006)

knowledge management is the systematic management of all

activities and processes referred to generation and

development, codification and storage, transferring and

sharing and utilization of knowledge for an organization’s

competitive edge.

2.2 Literature Review and Previous Studies in the Same

Field

(Adan 2013) the main objective of this research was to

identify the key knowledge management enablers that affect

the performance of Kenya Revenue Authority. Therefore, the

study considered the organizational culture (collaboration,

mutual trust, learning, and leadership), structural issues

(centralization and formalization), people, and IT

infrastructure as significant factors of knowledge

management. Moreover, the results emphasized that these

enablers had moderate to high effect on the performance of

organization. . In addition, this provides a clue for academia

and the business field to consider knowledge management to

improve the overall performance.

(Majin et al. 2015) studied the role of knowledge management

enablers, and how it can affect the performance in MASKAN

banks of IRAN as the study’s sample. Therefore, the goal was

trying to determine which important factors are enabling in

order to share their knowledge on the effectiveness of

knowledge management and database performance.

Therefore, culture, structure, information technology and

employee skills were studied, because they had been

considered as the most important factors.

Thereby, the result revealed that all independent variables

have a positive effect on the effectiveness of knowledge

management. Moreover, employee skills and culture have a

significant impact on performance, whereas structures and

information technology had the lowest impact.

(Theriou et al. 2011) identified the critical success factors or

enablers that determine the knowledge management

effectiveness, which in turn influence the total performance of

the small, medium and large manufacturing companies in

Greece. Based on that, this study outlines five important

factors which are: leadership, culture, technology, knowledge

management strategy and people. Thereby, this study will

help organizations to understand the impact that different

enablers have on knowledge management successful

implementation and, how the effectiveness of knowledge

management affects the performance.

In conclusion, the empirical evidence presented here suggests

that organizational culture and leadership are the most

important enabler factors. The identification of these core sets

of factors will facilitate the evaluation, by organizations, of

the statues of knowledge management implementation and

identification of areas for improvements. Consequently,

organization that adopts effective knowledge management

today will achieve competitive advantage tomorrow.

(Scott and Bruce 1995) defined decision making as “the

learned habitual response pattern exhibited by an individual

when confronted with a decision situation.” Another study,



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carried out by (Rehman et al. 2012), created a model, in order

to investigate the impact of decision making on the

organization's performance using emotional intelligence as a

moderator.

Therefore, the population of this study contains (151) branch

(public and private) banks in Pakistan. The sample was

chosen randomly to collect data. Finally, the result of the

study described that rational and dependent decision making

impact strongly and positively the organization's performance,

while avoidant decision making has negative impact on it.

3. THE THEORETICAL FRAMEWORK OF THE

STUDY

Figure 1, below shows the proposed framework of this study.

The model was built on prior studies in the same field and the

interviews conducted with some experts in commercial banks

in Jordan. In order to determine the enablers that can

profoundly affect the entire performance of the banks.

Moreover, this framework contains independent variables

(knowledge management enablers), dependent variables

(organizational performance) and mediated variable (decision

making). For more clarification, each one of the chosen

enablers, decision making and organizational performance

will be explained separately.

Cultural Attributes

Many researchers were unanimous in that cultural attributes

play a crucial role in knowledge creation and knowledge

management. “Set of values, beliefs, customs, traditions and

practices of sustainable knowledge that the organizational

members will exchange, share and divide between each other”

(Watson 2008). Also, culture can be defined as a set of shared

values and beliefs among organizational members,

expectations, unwritten rules and habits that affect attitudes

and personality. In other words, it is the fundamental beliefs

that allow employees to understand each other and

communicate (Delong and Fahey 2010). Moreover, (De Long

1997) said that culture is not only the value of knowledge but

also what knowledge should be kept in the organization for

creation and innovation.

Leadership Style

A managerial influence is considered as a part of

organizational participants who are responsible for the

management of knowledge. “Leadership is an important factor

in the organization, to convert their culture into knowledge-

supporting culture”. (Ribière and Sitar 2003). Also, (Asoh and

Belardo 2007) defined the leadership as “the support of top

management for achieving knowledge management

activities”. Several studies were conducted to investigate and

emphasize the role of leadership in knowledge management

implementation, and the role of leader to guide a continuous

learning for others, how a leader should have an unusual

manner to achieve the highest level of organizational

performance (Stephen 2000). In addition, (Singh 2008)

affirmed that leadership plays a key role in knowledge

management to acquire competitive advantages as one of the

organizations’ goals. Moreover, he suggested (4) leadership

styles (directive, supportive, consulting and delegating) that

can affect knowledge management positively, while others do

not.

Employee Skills

Creation knowledge in an organization depends entirely on

human resource (Berraies et al. 2014). Moreover, (Eppler and

Sukowski 2000; Gottschalk 2000; Scott 2000), deemed that

people forms the center of creation knowledge within

organizations. (Scott 1998) studied this variable and left a

vital adage: knowledge management consists of (10%)

technology and (90%) people. Also, employees are considered

the heart of organizational creation knowledge (Wai Tat and

Hase 2007). (Nonaka and Takeuchi 1995) claimed that a new

employee with new skills will add to the organization a new

knowledge. Successful knowledge management is directly

related to people because learning new knowledge and sharing

knowledge depend on the social activities of people (Susanty

et al. 2012).

Information Technology Infrastructure

Information technology infrastructure should be widely

applied and invested within organizations, since it supports

different scientific activities (Gold et al. 2001). Researchers

highlighted the role of information technology infrastructure

in supporting creation knowledge process (Prax 2003; Mallet

et al. 2006; Lopez-cabroles et al. 2009). In the context,

information technology provides many tools such as the

internet, groupware, workflow, data mining, and video

conferencing that help organization to manage the knowledge.

Practically, “connecting the employees via some arranged

reusable knowledge, is considered as a channel between the

newly created knowledge” (Jeng and Dunk 2013). The

hierarchy existence of information technology infrastructure,

in the organization, provides many benefits for the

organization such as, reduce the effort and time to make

employees achieve the tasks more efficiently and timely, so it

is indisputable that information technology infrastructure

plays a principal role in the implementation of knowledge

management (Sadri McCampbell et al. 1999).

Decision Making

None of the organizations wish to lose, bust or get a low

growth in future. Thus, managers are always trying to find

new business operations to enhance the performance.

Therefore, introducing decision making mechanisms will

assist to reach perfect organizational performance, and to

achieve the desired or needed goals. The sustainable

information allows managers to make effective and efficient

business decisions (Rehman and Scholar 2011). While (Astley

and Van de Ven 1983) proved that decision makers affect

positively the organizational performance. Moreover, (March

and Olsen 2010) defined decision making as “the process of

making choices from some alternatives”. Furthermore, (Scott

and Bruce 1995) categorised the decision making style into



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(5) major sections, which are:

Rational decision making “looking for a logical

evaluation of alternatives”.

Intuitive decision making “depending upon hunches

and feelings”.

Dependent decision making “advice and direction

from others”.

Avoidant decision making “attempts to avoid

decision making or postpone it”.

Spontaneous decision making “taking a sudden and

impulsive decision”.

(Simon 1997; Mintzberg 2008; Drucker 2010) emphasised

that decision makers consider the most robust processes of all

management activities. Also, (McGregor 2001) noted that the

quality and speed of decision making can be measured by the

success and failure of an organization. While (Flüeler and

Blowers 2007) studied the quality of decision making process,

and how to make this process more critical and crucial by

identifying the goals, providing alternatives, then weighing

and balancing the values.

Organizational Performance

Nowadays, organizations or companies focus on the measure

of performance as one of its essential activities “what you

measure is what you get”. Generally, performance is a key

phase of strategy establishment and achievement, because it

can provide the organization's vision and strategic target to all

organizations’ members and top management (Zaied 2012).

As well as, (Moullin 2007) argued that organizational

performance has been considered as important factor to

investigate the organizational success. (Ngah and Ibrahim

2010) defined organizational performance as "comparing the

expected results with the actual ones, investigating deviations

from plans, assessing individual performance and examining

progress made towards meeting the targeted objectives".

Thereby, based on the organisational performance definition,

the indicators of organizational performance may assist

managers to assess the organizational activities and keep the

competitive position or superiority over competitors (Liao et

al. 2009; Visser and Sluiter 2007). Actually, (Sinotte 2004)

explained that performance could be measured or identified

by the quality of functions. So, the whole performance in

organizations refers to how organizational operations are by:

Describing how to use the resources in the

production process or how to provide services and

what is the relation between the real and the ideal,

used as inputs to achieve specific outputs.

Describing the desired goals of the organization.

4. RESEARCH HYPOTHESIS

Many experts and researchers have proposed several

suggestions of knowledge management enablers. Since

organizations are interested in implementing knowledge

management practices to achieve their desired goals, this

paper focuses on the common suggested knowledge

management key enablers which are: Organizational culture,

leadership, personnel, information technology (e.g., Cepeda-

Carrión 2006; Debowski 2006; Fernandez and Sabherwal

2006; Girard 2005; Stankosky 2005; Lee and Choi 2003).

(Almudallal et al. 2016) claimed that "Generally, these four

key enablers of KM can be compared to the legs of a four-

legged table; if one leg is missing then the table will collapse".

(Rehman 2012) conducted a research to investigate the

relation between decision making and organizational

performance. Generally, the findings of this study emphasized

that decision making has a high positive impact on the

organizational performance. While as, (Nicolas 2004) stated

that there is a deep relation between knowledge management

and decision making. This study found out that knowledge

management has a significant role on decision making

processes.

After considering the aforementioned researches, this paper

has identified (4) knowledge management enablers:

Organizational culture, leadership, personnel, information

technology. Also, it investigated the relations between

knowledge management enablers (as independent variables),

decision making (as mediated variable) and organizational

performance (as dependent variable). Based on these variables

classification, we developed the framework of this study and

the suggested hypotheses.

H1: Cultural attributes have a significant statistical

impact on organizational performance as mediated

by decision making.

H2: Leadership style has a significant statistical impact

on organizational performance as mediated by

decision making.

H3: Employee kills have a significant statistical impact

on organizational performance as mediated by

decision making.

H4: Information technology infrastructure has a

significant statistical impact on organizational

performance as mediated by decision making.

H5: Effectiveness of decision making has a significant

statistical impact on organizational performance.

H6: Cultural attributes have a significant statistical

impact on decision making.

H7: Leadership style has a significant statistical impact

on decision making.

H8: Employee skills have a significant statistical impact

on decision making.

H9: Information technology infrastructure has a

significant statistical impact on decision making.



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Figure 1. The theoretical framework of the study

5. RESEARCH METHODOLOGY

This section explains in details the methodological approach

that is applied in this study. Generally, it provides the readers

with a wide vision about the analytical approaches used such

as, questionnaire development, sample and data collection,

then historical sequences of the analysis tool used.

5.1 Questionnaire Development

After identifying the knowledge management enablers with

the mediated variable decision making factor, the researchers

supposed that there is a relationship between these considered

variables. Moreover, some interviews have been conducted

with a consultant of the central bank of Jordan, operational

manager of Housing Bank for Trade and Finance, operational

manager of Cairo Amman Bank and Chief Risk Officer

(CRO) of the Societe General _Jordan bank. And, in order to

achieve mindstorming with these interviewees, the conducted

interviews can be described as free interviews or discussions

to gain more information in details. Consequently, a

questionnaire was designed to gather primary data from the

employees of the commercial banking sector in Jordan. The

questionnaire was developed based on the conducted

interviews and some previous studies in the same field (Lee

and Choi 2003; Zaied 2012; Mahdavi Mazdeh and

Hesamamiri 2014; Adan 2013). The questions taken from

other studies have been rewritten to serve the goal of this

study. Before adopting the designed questionnaire, (5)

academics (4) of them in Mutah University, and (1) in applied

science university) pre-tested it for the conformity and

validity, in order to investigate the suggested framework and

test the proposed hypotheses. In doing so, questionnaires were

distributed randomly some by hand through visiting the

branches, others distributed by submitting the questionnaires

via email. Hence, all banks (Jordanian and non-Jordanian

commercial banks) were involved in this study.

The respondents have chosen their answer regarding the 5-

pointLikert scale ((1) = strongly disagree, (2) = disagree, (3) =

neutral, (4) = agree, (5) = strongly agree) (Likert 1932). The

questionnaire composed of (4) pages with (3) main parts and

with (42) questions arrangement as follows. However, the

questionnaire was translated into Arabic then back to English

to make it easier for employees. Appendix (A) includes

English version of the used questionnaire.

The first part, regarding the personal information includes

(4) questions (Gender, Age category, Education level and

Experience).

The second part of the questionnaire consisted of (3)

questions regarding the organizational information.

The third part includes the rest of this questionnaire with

(35) questions containing (3) main items: knowledge

management enablers, decision making and

organizational performance.

After structuring the questionnaire and asserting that the

questions used were sufficient to gather the primary data

which needed to achieve the intended goals of this study. A

pilot study was done represented in the distribution of (15)

copies of this instrument to (15) employees in different banks

in Amman- Jordan. In order to find out from the feedback if

there are any problems such as, question ambiguity, technical

jargon, mistakes in wording and context...etc. In order to

prevent the participants in the future to fill in mistakes or feel

bored during answering the questions. Then, after collecting

the pilot test questionnaires, a feedback was considered to

make some minor corrections before distributing the final

questionnaire.



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This study is designed as a case study. Since it is considered a

flexible design type for researchers, it provides opportunity to

researchers to keep the entire properties of real life events

during exploring the empirical events. (Yin 2009) emphasized

that using or implementing case study method is more

suitable, where the main goal of the study is exploratory.

Moreover, using case study method allows the researchers to

collect the needed information in a systematic way by

gathering data in different techniques (Cavana et al. 2001).

5.2 Sample and Data Collection

This study was applied to the commercial banks of Jordan.

The population of this study involved all employees in these

banks. In this research, the required data was collected by (2)

primary ways: firstly, interviews that have been conducted

with a consultant of the central bank of Jordan, operational

manager of Housing Bank for Trade and Finance, operational

manager of Cairo Amman Bank and Chief Risk Officer

(CRO) of Societe General _ Jordan, to determine which of the

most enablers that can impact effectively the banking sector

with the surrounding circumstance and environment.

Secondly, a questionnaire was built to measure the impact of

these proposed enablers and to what extent they can affect the

performance.

Total number of (450) questionnaires were distributed to

cover the chosen sample. However, (437) questionnaires were

returned successfully while (13) questionnaires were

dismissed or not returned. Out of the (437) questionnaires

returned, (37) questionnaires were eliminated from the study

because they were incomplete or not correct. This has yielded

the response rate of (97.1%), based on the conducted pilot

study. The collected questionnaires will be analysed using an

artificial intelligence approach specifically fuzzy logic method

(MATLAB® R2017b).

5.3 Fuzzy logic (Fuzzy Inference Systems (FISs))

Over years, fuzzy logic has been used in many applications

such as, finance and earthquake engineering. The historical

sequence of fuzzy logic has started in 1965, when Professor L.

A. Zadeh published the first paper entitled “Fuzzy sets”, then

the seed of this idea was proposed and published by the same

person in the years of 1968 and 1972. After that, fuzzy logic

has been described in more details in 1973 (Bal, M., Biricik,

C.G. and Sari, A. (2015); Cambazoglu, Ş. and Sari, A. (2015);

Sari, A. and Akkaya, M. (2015);, Sari, A. and Akkaya, M.

(2015); Obasuyi, G. and Sari, A. (2015); Sari, A. (2015); ). In

1974 Mamdani and Asslainmade made the first

implementation using fuzzy logic for a steam engine. Year by

year, fuzzy logic approach has grown and understood

perfectly, to be a basic building block for many other

applications. (Zadeh 1988, Sari, A.; Rahnama, B., (2013),

Sari, A., Kilic, S., (2017); Sari, A. (2015); Sari, A. (2015);

Sari, A. (2014); Sari, A. (2014); Megdadi, K., Akkaya, M., &

Sari, A. (2018); Rahnama, B., Sari, A., & Ghafour, M. Y.

(2016); Sari, A., (2015); Sari, A., Akkaya, M., Abdalla B.,

(2017); Sari, A. (2016); Sari, A. (2018), Sari, A., Alzubi, A.,

(2017)).

In general, FISs occupied a significant place in fuzzy logic

and fuzzy set theory as well. FISs were defined by (Yager et

al. 1994), as an intelligence mechanism using computational

operations to determine the output perfectly using fuzzy

inference rules, which go hand in hand with the input.

Technically, there are many reasons that tempted the

researchers to use FISs approach to analyze the collected data

of their studies. First, FISs are assigned to measure the impact

of independent variables on dependent variables. Second, they

use very simple mathematical equations. Third, this method

will provide very accurate decisions. Fourth, all possibilities

can be found but no IF-THEN statement can do that. Fifth, in

case of error, FISs give the ability to modify by adding or

even deleting some rules in order not to re-create new FISs

from the beginning. Finally, they are working in parallel with

very high speed. Therefore, it was the best mechanism that

can be used for analysis in this study, in order to make use of

its aforementioned benefits. Also, the researchers did not find

another study that adopted this mechanism for analysis (Sari,

A.,, Qayyum, Z.A, Onursal, O. (2017), Sari, A. (2017), Sari,

A, Akkaya, M., Fadiya, S., (2016), Alzubi, A. and Sari, A.

(2016), Sari,A., Akkaya, M. (2016).

Several studies conducted to expose different impact of

Artificial Intelligence and FIS in the literature related with

quality assurance, organizational performance and decision

making and find accurate results (Sari, A. Firat, A.,

Karaduman, A. (2016); Sopuru, J., Sari, A., (2016);

Kirencigil, B.Z., Yilmaz, O., Sari, A., (2016) , Yilmaz, O.,

Kirencigil, B.Z., Sari, A., (2016); Akkaya, M., Sari, A., Al-

Radaideh, A.T., (2016); Sari, A., Onursal, O. and Akkaya, M.

(2015).

6. ANALYSIS AND FINDINGS

This section discusses the research’s model outcomes

formulated from data analysis which are: demographic

outcome, independent variables phase, mediation variable, the

final result for the overall framework (3 Outputs), Decision

Making (DM) on Organizational Performance (OP). Finally,

the researcher will present the results for each phase using

FISs model.

6.1 Demographics Variables Profile

Table 1, below shows the personal information about the

employees who are involved in this study. (238) out of (400)

participants were males, which represents (59.5%) and the

rest, (162) were females that forms (40.5%). Moreover, (219)

out of the total sample have ages less than (30) years, where

(54.75%) were considered to occupy the highest rate in this

category. The third question looked for the education level of

the involved employees in commercial banks, where (312) out

of (400) respondents had bachelor degree and that represents

(78%), and the others were divided between diploma, master

and other. Based on the level of experience, the participants

had been classified into (4) categories: (176) employees with a

ratio (44%) had (5) years or less of job experience, (106)

employees had 6 to10 years, (70) employees had (11-15)

years which represnets (17.5%) and only (48) of the



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participants had (16) years or more which forms (12%).

Table 1. Demographic Frequency Statistic

Gender Count %

Male 238 59.5%

Female 162 40.5%

Total 400 100%

Age Count %

30 years or less 219 54.75%

31-40 years 138 34.5%

41-50 years 39 9.75%

50 years or more 4 1%

Total 400 100%

Education Count %

Diploma 31 7.75%

Bachelor 312 78%

Master 49 12.25%

other 8 2%

Total 400 100%

Experience Count %

5 years or less 176 44%

6 to 10 years 106 26.5%

11 to 15 years 70 17.5%

16 years or more 48 12%

Total 400 100%

Practically, the analysis includes (4) main stages: independent

variables phase (knowledge management enablers), mediation

variable (decision making), the final result for the overall

framework (3 outputs) and Decision Making on

Organizational Performance. Each one of these stages

required (4) steps to be performed. Note that, each step has

particular specifications: 5-point likert scale to indicate the

number of input's membership functions. Input and output

membership function type was “gaussmf”, the range of input's

membership functions was [400 2000] and, the range of

output’s membership functions was [0 100]. The section

below explains that in details.

6.2 Independent Variables Phase (Knowledge

Management Enablers)

Designing a model for chosen independent variables

knowledge Management Enablers (KMEs)

The first step of analysis is to designing a model to identify

the number of input and output variables, in order to find the

influence of the (4) chosen variables which are (cultural

attributes, leadership style, employee skills and information

technology infrastructure). In sum, this designed model

consists of (19) questions that represent the input which lead

to extract (4) outputs.

Creating membership function for independent

variables ( KMEs)

After finalizing the previous step, membership function must

be determined for the designed model. All the suggested

independent variables are categorized by the 5-point likert

scale. Hence, the questions from (1-19) in the designed

questionnaire are represented in the independent variables

where, the questions from (1-6) are represented in the cultural

attributes. Questions from (7-10) are related to leadership

style. From (11-15) returned to employee skills and (16 -19)

are designed for the information technology infrastructure.

Creating rules for independent variables (KMEs)

This step concerns the creation of rules. All the valid returned

questionnaires were stored in an excel sheet. Then, several

calculations were done such as, AVERAGE and SUM for all

items. Hence, the connection between input and output is

always (AND).

Rules viewer for independent variables

Based on the previous steps, the obtained results can be shown

by clicking on view list then select rules. The results show

that each independent variable has a different influence:

cultural attributes (C) had (62.9%), leadership style (L) had

(63.7%), employee skills (E) had the lowest influence equals

to (60.1%), and information technology infrastructure (I) had

(64.6%) which is considered the highest influencer. As shown

in Figure 2, below.



16867

Figure 2. Rules viewer for independent variables knowledge management enablers (Source: self-generated)

6.3 Mediation Variable (Decision Making)

Designing a model for the mediation variable Decision

Making (DM)

Designing a model for the next step that represents the (DM)

as a mediation variable. Thereby, this step formed the

stepping stone to find the result of next stage. Moreover, this

step is basically depending on the obtained results from

previous one, by integrating (4) inputs from KMEs with (6)

inputs of the mediation variable DM, in order to extract only

(1) output.

Creating membership function for the mediation

variable (DM)

Identifying the membership function for all used inputs

(KMEs and 6 items of the mediation variable DM) should be

done. The questions from (20-25) in the questionnaire

represent the DM variables.

Creating rules for the mediation variable (DM)

In order to get the desired result of this phase, the rules should

be entered which represent all returned responses from the

involved employees. As mentioned before, this phase is

totally depending on the previous stage. So the result of C, L,

E and I intersected with the membership function at (2) points

mf3 and mf4, which led the researcher to enter the rules twice

on the mentioned membership function. Therefore, (800) rules

were introduced in this stage to obtain a clear result and assert

that the outcome is more accurate.

Rules viewer for the mediation variable (DM)

After doing all the needed calculations on the excel sheet such

as, average and sum. The result will be used as an input for

the next stage. All in all, the result comes as the following:

KMEs and DM as a mediation variable is (60.7%). Figure 3,

shows the result of this stage.



16868

Figure 3. Rules viewer for independent (KMEs) with mediation variable (DM) (Source: self-generated).

6.4 The Final Result for the Overall Framework (3

Outputs)

Designing a model for the overall framework

(Organizational Performance (OP) with (3) Outputs)

In this step, the researcher has to enter the result (Output) of

phase (6.3) as an input, in order to find the influences on the

organizational performance (overall model). Hence, the

performance has been divided into (3) outputs, which are the

competitive position (CP), Market share (M) and Quality of

services (Q), to discover the influence of each one of them

alone on the designed model. This stage contains (11) inputs

distributed as: (1) input returned to (KMEs_DM), (10) inputs

belonged to OP. whereas, (3) outputs for CP, M and Q as

named in the FISs.

Creating membership function for the overall framework

(Organizational Performance (OP) with (3) Outputs)

Creating membership function is the next step in this phase as

done before. (1) Input (KMEs_DM) and (10) inputs regarding

the OP. The related questions for this stage are distributed as:

(26-29) for the competitive position (CP), (30-32) for the

market share (M) and the questions (33-35) for the quality of

services (Q).

Creating rules for the overall framework (Organizational

Performance (OP) with 3 Outputs)

The responses of the employees will be entered as rules. As

mentioned before, this phase depends on the outcomes of the

stage (6.3). The result also intersected with the membership

function at (2) points mf3 and mf4 that led to enter the rules

twice again.

Rules viewer for the overall framework (Organizational

Performance (OP) with 3 Outputs)

Finally, the rules viewer shows the final result of the KMEs

influence on the performance using the DM as mediation. As

before, the needed calculations (Average, Sum) are done on

the excel sheet. The results were the same for all outputs,

(60.7%) for Competitive Position (CP), Market share (M) and

Quality of services (Q) as well. Figure 4, shows the result.



16869

Figure 4. Rules viewer of the overall framework (Organizational Performance with (3) Outputs) (Source: Self-generated)

6.5 Decision Making (DM) on Organizational Performance

(OP)

Designing a model for DM on OP

This phase is trying to find out the influence of DM on the

overall performance. Therefore, the designed model will use

the questions for both DM and OP. This step contains (16)

inputs that are divided between DM and OP, with only (1)

output.

Creating membership function for DM on OP

Identifying the types of membership function and ranges. This

phase has (16) inputs, where the first (6) inputs return to DM

(the questions from (20-25)), and (10) questions refer to OP

(the questions from (26-35).

Creating Rules for DM on OP

Entering (400) rules that are related to DM and OP, in order to

find out the influences of DM on the entire performance.

Rules viewer for DM on OP

After performing the required calculations on excel sheet, the

result of this phase equals to (63.6%), and that would

represent the influence of DM on OP. Figure 5, below shows

the Rules Viewer result.



16870

Figure 5. Rules viewer of DM on OP (Source: Self-generated)

Figure 6, below shows the positive relationships between the

variables of this research which have emerged from the study

conducted on commercial banks. Whereas, the knowledge

management enablers affect positively the performance

through decision making variable as the following: cultural

attributes (62.9%), leadership style (63.7%), employee skills

(60.1%) and information technology infrastructure (64.6%).

Then these enablers, by decision making, influence the overall

performance with a rate of (60.7%); in details, this relation

affects the mentioned outputs of the organizational

performance which are (competitive position, market share

and quality of service) in the same ratio (60.7%). On the other

hand, decision making has impact on performance by a rate of

(63.6%).

Figure 6. Validated Framework of the study (Source: Self-generated)



16871

The result of this study confirmed the hypotheses which are:

cultural attributes have a positive impact on the commercial

banks performance in Jordan with a decision making as the

mediator, which support hypothesis (1), leadership style has a

positive impact on the commercial banks performance in

Jordan with a decision making as the mediator, which

supports hypothesis (2), employee skills have a positive

impact on the commercial banks performance in Jordan with a

decision making as the mediator, which support hypothesis

(3), information technology infrastructure has a positive

impact on the commercial banks performance in Jordan with a

decision making as the mediator, which supports hypothesis

(4), effectiveness of decision making has a positive impact on

the commercial banks performance in Jordan, which supports

hypothesis (5), cultural attributes have a positive impact on

the decision making, which support hypothesis (6), leadership

style has a positive impact on the decision making, which

supports hypothesis (7), employee skills have a positive

impact on the decision making, which supports hypothesis (8)

and information technology infrastructure has a positive

impact on the decision making, which supports hypothesis

(9).

7. DISCUSSION AND CONCLUSION

This study is considered as the first research that is trying to

examine the impact of knowledge management enablers on

the organizational performance using decision making as a

mediating variable in commercial banks of Jordan. Based on

the conducted interviews, it concluded that the most important

knowledge management enablers: cultural attributes,

leadership style, employee skills and information technology

infrastructure, in order to guarantee the best implementation

of knowledge management in these banks.

Accordingly, (400) questionnaires were distributed to

Jordanian and non-Jordanian commercial banks in Amman-

Jordan. Then, the collected data was analysed using the fuzzy

logic method. Finally, these findings can be used to enhance

better implementation of knowledge management in

commercial banks, and in order to reach higher level of

organizational performance. Moreover, it helps these types of

organizations to take advantage of knowledge management by

identifying the most important enablers.

Since a lot of crises happened, this study is recommended to

conduct more researches about applying knowledge

management in banking sector of Jordan. In sum, the

organization must understand knowledge management and

identify the influencing enablers for better performance. This

can help decision makers to avoid the consequences of

upcoming crises in future. Moreover, this study has found that

information technology infrastructure has a significant impact

on the effectiveness of applying knowledge management to

commercial banks. This leads to developing the deployed

information technology infrastructure and providing training

courses for employees to increase their skills in this side.

Both leaders and top management play a significant role in

implementing knowledge management, by enhancing

communication channels, trust and collaboration between

employees, this leads to improved internal environment where

creation, sharing, and transfer of knowledge could flourish.

However, employee skills factor had the lowest impact in this

study. But it is considered the heart of creation knowledge and

knowledge management implementation. Therefore, top

management must pay more attention by involving the

employees in some courses, symposia, conferences and

workshops. Moreover, human resources department must

employ new employees who have multiple skills. Researchers

would advise managers to encourage the employees to be

involved in decision making process, by expanding their

authorities or permissions and taking their perspectives into

account.

Based on the aforementioned findings, this research has

considered some inherent limitations and future suggestions.

Firstly, the vast majority of studies about knowledge

management have been conducted in some developing

economies. However, there is a lack in empirical findings in

commercial banks. Moreover; the researcher did not find any

study about applying knowledge management in Jordanian

commercial banks. Thus, this sector may be a fertile

environment for future studies. Secondly, researchers should

adopt this idea and conduct several studies using different

variables that can affect applying knowledge management

(socio-technical theory must be considered (Pan and

Scarbrough 1998)) in this sector to maintain the high quality

of performance. Thirdly, this study was conducted in a

specific sector (Jordanian and non-Jordanian commercial

banks), so the result cannot be generalized to other types of

banks or organizations, because the selected variables are

based on the type, size, structure and surrounding

environment of only these types of banks in Jordan. Fourthly,

there is no particular study that examines the relationship

between knowledge management, decision making and

organizational performance. Therefore, this could be a future

research to glean this relation in different types of

organizations. Finally, internal policies in some organizations

are very restricted. Since they prevent the researchers from

collecting the needed information for the sake of privacy. So,

the researchers may face many difficulties during the

conduction of interviews and the distribution of

questionnaires. Therefore, banks must create some sort of

departments to support the scientific research.

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APPENDIX A

Personal Information

1. Gender: Male Female

2. Age category: 30 years or less 31-40 years 41-50 years 50 years or more

3. Education: Diploma Bachelor Master Other

4. Experience: 5 years or less 6 to 10 years 11 to 15 years 16 years or more

Organizational Information

1. Compared with key competitors, the company is more successful. (Lee and Choi 2003)

2. Compared with key competitors, the company has a greater market share. (Lee and Choi 2003; Zaied 2012)

3. Compared with key competitors, the level of customer satisfaction is much better. (Mahdavi Mazdeh and Hesamamiri 2014)

Survey Questions

Cultural Attributes:

1. Organizational helps their employees to establish a good relationship between each other. (Adan 2013)

2. Organization provides facilities that allow collaborating between employees, via exchange information and

experience. (Adan 2013)

3. Organization seeks to provide a good environment to work within it. (Adan 2013)

4. Organization is always interested in developing the experience and knowledge of the employees. (Adan 2013)

5. Organization encourages its employees to continue their education and supports them to achieve this. (Adan

2013)

6. Organization culture encourages openness for perpetual change. (Developed by interviews)

Leadership Style:

7. Organization is keen on applying convenient leading techniques with their employee. (Adan 2013)

8. There is a variety of leadership techniques applied in the organization. (Adan 2013)

9. Organization managers have leadership capabilities to cope with different work situations. (Adan 2013)

10. Leaders within the organization encourage employees to participate in decision making. (Zaied 2012)

Employee Skills:

11. Employees within the organization have the required skills to accomplish their work. (Adan 2013; Zaied 2012)

12. Organization provides a convenient environment for employee to develop their experience and skills. (Adan

2013)

13. Organization schemes are keen on providing a various training courses that suit the employees’ needs and

abilities. (Adan 2013; Zaied 2012)

14. Organization is interested in evaluating the employees’ skills and capability and takes care of them. (Adan 2013)

15. Organization identifies the needed training courses according to the needs and capabilities of employees. (Adan

2013)



16877

Information Technology Infrastructure: (Developed by interviews)

16. Organization is always interested in developing the Information technology infrastructure.

17. Organization provides the needed technical support to the information technology permanently.

18. Organization is always interested in updating different technology and application.

19. Organization always tries to keep up with the technical and technological changes within the surrounded

environment.

Decision Making: (Developed by interviews)

20. Decision making process done within an organization in an organized manner.

21. Organization is interested in involving employee in decision making.

22. Organization seeks to enhance decision making process by using all available tools.

23. Organization is keen on making decisions dependent on confirmed and appropriated information.

24. Decision making process done according to environmental condition.

25. Decision making process is followed to ensure that is applied perfectly.

Organizational Performance: (Developed by interviews)

Competitive Position:

26. Organization is keen on putting a set of strategies and objectives to achieve a high level of organizational

performance.

27. Organization seeks to keep up with changes, in order to maintain a high level of performance.

28. Organization is concerned with customer satisfaction in order to achieve a high level of performance and

competitiveness.

29. Organization is concerned with what competitors provide and try to accomplish their works in better manner.

Market Share:

30. Organization is keen on studying the surrounded environment to identify the needs of customers and fulfill

them.

31. Organization takes into account the complaints and suggestions of the customers in order to increase the level of

satisfaction.

32. Organization provides many services in order to increase their market share.

Quality of Services:

33. Organization continuously assesses the level of quality for services and products.

34. Organization is always concerned with developing the quality by applying the highest quality standards.

35. Organization provides customers the service of suggestion and complaints for the quality, performance and

other transaction within it.

Thank You

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