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Workplaces that Work: Examining the
Relationships between Conflict, Subjective
Well-being, Employee Performance and
Turnover Intentions
By
Razia Shaukat
CIIT/FA10-PMS-001/ISB
PhD Thesis
In
Management Sciences
COMSATS Institute of Information Technology
Islamabad Campus - Pakistan
Fall, 2016
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COMSATS Institute of Information Technology
Workplaces that Work: Examining the
Relationships between Conflict, Subjective Well-
being, Employee Performance and Turnover
Intentions
A Thesis Presented to
COMSATS Institute of Information Technology, Islamabad
In partial fulfillment
of the requirement for the degree of
PhD (Management Sciences)
By
Razia Shaukat
CIIT/FA10-PMS-001/ISB
Fall, 2016
3
Workplaces that Work: Examining the
Relationships between Conflict, Subjective Well-
being, Employee Performance and Turnover
Intentions
A Post Graduate Thesis submitted to the department of Management Sciences
as partial fulfillment of the requirement for the award of Degree of Ph.D in
(Management Sciences).
Name
Registration Number
Razia Shaukat
CIIT / FA10-PMS-001/ISB
Supervisor
Dr. Amna Yousaf
Assistant Professor Department of Management Sciences
COMSATS Institute of Information Technology (CIIT) Islamabad
Campus
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5
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DEDICATION To my parents, my husband and kids whose unwavering support and love enabled me
to complete my work. May Almighty ALLAH bless and protect them.
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PUBLICATIONS
1. Paper titled ―Examining the linkages between relationship conflict,
performance and turnover intentions: role of job burnout as a mediator‖ is accepted in
International Journal of Conflict Management in April, 2016.
2. Paper titled ―Workplaces that work: Examining the relationships between task
conflict, work engagement, job performance and turnover‖ is under revise and
resubmit in journal ―Negotiation and Conflict Management Research‖
3. Paper titled ―Relationship conflict and employee well-being: role of
interpersonal strain at work as a mediator‖ is under review in journal ―Review of
Managerial Sciences‖.
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ABSTRACT
Workplaces that Work: Examining the Relationships between
Conflict, Subjective Well-being, Employee Performance and
Turnover Intentions
Conflict is an inherent part of organizational life and it has been recognized to
affect work behaviors in substantial ways. The conflict research abounds with studies
on the direct relationships of conflict types and work behaviors with few exceptions
whereas underlying psychological mechanisms linking these direct relationships have
not been explored. Furthermore, little is known about whether western findings
regarding the effects of task conflict and relationship conflict still hold across non-
western cultures.
This thesis offers insights regarding the consequences of task conflict and
relationship conflict among employees in terms of their task performance, contextual
performance and turnover intentions. The study proposed and tested two underlying
mechanisms linking task/relationship conflict and work behaviors. More specifically,
utilizing a resource investment/acquisition approach and related corollary of gain
spirals in the backdrop of Conservation of Resources (COR) theory, it was suggested
that work engagement and job satisfaction distinctively mediate the link between task
conflict and work behaviors. Furthermore, guided by the resource depletion approach
and related corollary of loss spirals of the COR theory, it was proposed that the three
dimensions of burnout (exhaustion, cynicism and interpersonal strain) play a
mediating role in influencing the linkages between relationship conflict and outcomes.
Data was collected from 508 telecom engineers and their supervisors and
analyzed using structural equation modeling to test the interrelationships among the
study constructs. The results reveal that task conflict in non-routine complex jobs acts
as a resource and facilitates task performance and contextual performance and reduces
turnover intentions through work engagement as well as job satisfaction. With
respect to relationship conflict results indicated that relationship conflict is negatively
related to task performance, contextual performance and turnover intentions, and that
the three dimensions of job burnout i.e., exhaustion, cynicism and interpersonal strain
at work, distinctively mediate the linkages between relationship conflict, task and
contextual performance and turnover intentions.
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The current study contributes to the conflict literature by delineating a
resource investment/acquisition process in the backdrop of the Conservation of
Resources (COR) theory whereby task conflict (an exchange of cognitive resources)
leads to resource gain (work engagement), which in turn lead to positive outcomes in
individuals. It also adds valuable knowledge by suggesting and validating resource
depletion process which explicates how relationship conflict transmits its effect to job
performance and turnover intentions through mediation of burnout. All in all, the
findings have important practical as well as theoretical implications for managers and
academicians alike.
Keywords: Task conflict, relationship conflict, task performance, contextual
performance, turnover intentions, workplace well-being, work engagement, job
satisfaction, job burnout-exhaustion, cynicism, interpersonal strain at work.
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TABLE OF CONTENTS
1. Introduction 1
1.1 Theoretical Background 2
1.2 Aims and Objectives 8
1.3 Problem Statement 12
1.4 Research Questions 12
1.5 Context of the Study 13
1.6 Significance of the Study 16
1.7 Managerial Implications of the Study 19
1.8 Thesis Structure 19
1.9 Summary 20
2. Critical Review of Literature 21
2.1 The Conservation of Resources (COR Theory) 22
2.2 Conflict 25
2.2.1 Conceptualization of Interpersonal Conflict 27
2.2.2 Conflict with Coworkers 28
2.2.3 Consequences of Task Conflict 30
2.2.4 Consequences of Relationship Conflict 33
2.3 Conceptualization of Outcome Variables 36
2.3.1 Task and Contextual Performance 36
2.3.2 Turnover Intentions 38
2.4 Workplace Subjective Well-being 40
2.4.1 Work Engagement 41
2.4.2 Job Satisfaction 45
2.5 Burnout 49
2.5.1 Exhaustion 52
2.5.2 Cynicism 53
2.5.3 Interpersonal Strain at Work 54
2.6 Summary 55
3. Theoretical Framework 56
3.1 Task Conflict and Task/Contextual Performance 57
3.2 Task Conflict and Turnover Intentions 58
3.2.1 Studies Linking Task Conflict and Turnover Intentions 58
3.2.2 Substantiating Evidences from the Literature 59
3.3 First Route of Theoretical Framework… 60
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3.3.1 Resource Investment/Acquisition Principle of the COR theory
and Gain Spirals 61
3.3.2 Direct Relationship among Task Conflict and Work Behavior 62
3.3.3 Mediation of Work Engagement / Job Satisfaction in the
Relationship Between Task Conflict and Work Behaviors 64
3.4 Relationship Conflict and Job Performance 72
3.5 Relationship Conflict and Turnover Intentions 72
3.6 Substantiating Evidences from the Literature 73
3.7 Route Two of Theoretical Framework: 74
3.7.1 The Conservation of Resources Theory (Primacy of Loss
Principle and Loss Spirals) 75
3.7.2 The Direct association of Relationship Conflict and Work
Behaviors 77
3.7.3 The Mediation of Job Burnout in the Link between Relationship
Conflict and Work Behaviors 80
3.8 Complete Model 90
3.9 Summary 93
4. Research Methodology 94
4.1 Research Philosophy 95
4.2 Research Approach 98
4.3 Research Design and Corresponding Strategy 99
4.4 Sample Design 100
4.4.1 Target Population 101
4.4.2 Sampling Frame 101
4.4.3 Sampling Technique and Methods 101
4.4.4 Sample Size 102
4.4.5 Data Collection 103
4.5 Survey Design 105
4.6 Tools / Questionnaires 106
4.6.1 Interpersonal Conflict 106
4.6.2 Task Conflict 106
4.6.3 Relationship Conflict 106
4.6.4 Workplace Subjective Well-being 106
4.6.4.1 Work Engagement 107
4.6.4.2 Job Satisfaction 107
4.6.5 Job Burnout 108
4.6.5.1 Exhaustion 108
4.6.5.2 Cynicism 108
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4.6.5.3 Interpersonal Strain at Work 108
4.6.6 Task Performance 109
4.6.7 Contextual Performance 109
4.6.8 Organizational Turnover Intentions 109
4.7 Common Method Variance 109
4.8 Survey Pre-Testing 110
4.9 Data Analysis 110
4.9.1 Preliminary Data Analysis 111
4.9.1.1 Data Screening 111
4.9.1.1.1 Missing Values 111
4.9.1.1.2 Outliers 112
4.9.1.1.3 Normality 112
4.9.2 Reliability and Validity of Scales 113
4.9.3 Exploratory Factor Analysis 114
4.9.4 Descriptive Statistics 116
4.9.5 Hypothesis Testing using Structural Equation Modeling 116
4.9.5.1. Measurement Model 117
4.9.5.2 Unidimensionality 120
4.9.5.3 Composite Reliability 120
4.9.5.4 Construct Validity 120
4.9.5.5 The Structural Model 121
4.10 Testing of Mediation 121
4.11 Ethical Considerations 122
4.12 Conclusion 123
5. Results….. 124
5.1 Non-response Bias 125
5.2 Demographic Characteristics of the Participants 127
5.3 Preliminary Analysis of the Data 128
5.3.1 Data Cleaning and Screening 128
5.3.1.1 Missing Values 128
5.3.1.2 Outliers 129
5.3.1.3 Normality 129
5.3.1.4 Correlations among the Study Variables 130
5.3.1.5 Exploratory Factor Analysis 132
5.3.1.5.1 Validation of Task Conflict 132
5.3.1.5.2 Validation of Relationship Conflict 133
5.3.1.5.3 Validation of Work Engagement 133
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5.3.1.5.4 Validation of Job Satisfaction 134
5.3.1.5.5 Validation of Exhaustion 134
5.3.1.5.6 Validation of Cynicism 135
5.3.1.5.7 Validation of Interpersonal Strain at Work 136
5.3.1.5.8 Validation of Task Performance 136
5.3.1.5.9 Validation of Contextual Performance 137
5.3.1.5.10 Validation of Org. Turnover Intentions 137
5.4 Common Method Bias 138
5.5 Structural Equation Modeling 138
5.6 The Measurement Model 139
5.6.1 Unidimensionality 141
5.6.2 Validity 141
5.6.2.1 Convergent Validity 141
5.6.2.2 Construct Validity 141
5.6.2.3 Discriminant Validity 142
5.7 Reliability of the Measurement Model 143
5.8 Direct Relationship 143
5.8.1 Task Conflict and Task/Contextual Performance and Turnover
Intentions 144
5.8.2 Relationship Conflict and Task/Contextual Performance and
Turnover Intentions 144
5.9 Testing of Mediation 145
5.9.1 Prerequisites for Mediation Testing 145
5.9.2 Mediation of Work Engagement 148
5.9.3 Mediation of Job Satisfaction 148
5.9.4 Mediation of Exhaustion 148
5.9.5 Mediation of Cynicism 149
5.9.6 Mediation of Interpersonal Strain At Work 149
5.10 Summary of Results 149
6. Discussion 151
6.1 Research Contributions 161
6.2 Research Limitations 167
6.3 Directions for Future Research 169
6.4 Theoretical Implications 173
6.5 Practical Implications 176
6.6 Conclusion 178
7. References 182
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8. Appendices 219
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LIST OF FIGURES Fig 3.1 Task Conflict, Well-being and Work Behaviors Model ………….....71
Fig 3.2 Relationship Conflict, Burnout and Job Performance Model 89
Fig 3.3 Conflict, Well-being and Job Performance Model 92
Fig 4.1 Layers of Onion 95
Fig 4.2 Foundation of Research, Source; Tuli, 2011 97
Fig 4.3 The 5-step Exploratory Factor Analysis Protocol 115
Fig 5.1 Confirmatory Factor Analysis of the Model 140
Fig 5.2 Direct Relationship 143
Fig 5.3 Mediation Model 147
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LIST OF TABLES
Table 1.1 Summary of Empirical Studies in the Link between Interpersonal Conflicts
and Group Level Outcomes 220
Table 1.2 Summary of Empirical Studies in the Link between Interpersonal Conflicts
and Individual Level Outcomes 227
Table 1.3 Summary of Empirical Studies in the Link between Interpersonal Conflicts
and Individual Level Outcomes in Pakistani Context 229
Table 1.4 Summary of Chapter 1 20
Table 2.1 Summary of Chapter 2 55
Table 3.1 Summary of Chapter 3 93
Table 4.1 Sample Size 103
Table 4.2 Various Phases of Data Collection 105
Table 4.3 Goodness of Fit Statistics in SEM 119
Table 4.4 Details of the Research Methodology 123
Table 5.1 Statistics of Early and Late Responses 126
Table 5.2 t-test for Comparison of Early vs Late Respondents. 126
Table 5.3 Demographic Profile of the Respondents 127
Table 5.4 Mahalanobis Distance 238
Table 5.5 Assessment of Normality 241
Table 5.6 Correlations, Std. Deviations, Mean & Reliability Statistics 131
Table 5.7 Component Matrix-Task Conflict 132
Table 5.8 Component Matrix- Relationship Conflict 133
Table 5.9 Component Matrix- Work Engagement 134
Table 5.10 Component Matrix- Job Satisfaction 134
Table 5.11 Component Matrix- Exhaustion 135
Table 5.12 Component Matrix-Cynicism 135
Table 5.13 Component Matrix- Interpersonal Strain at Work 136
Table 5.14 Component Matrix- Task Performance 137
Table 5.15 Component Matrix- Contextual Performance 137
Table 5.16 Component Matrix- Organizational Turnover Intentions 138
Table 5.17 Common Method Bias 243
Table 5.18 Goodness of Fit Indices 142
Table 5.19 Discriminant Validity Index 142
Table 5.20 Average Variance Extracted & Composite Reliability Values 245
Table 5.21 The Std. Regression Weights & Its Significance for Each Path 144
Table 5.22 Results of Mediations 146
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Table 5.23 Summary of Direct Hypotheses 150
Table 5.24 Summary of Indirect Hypotheses 150
Table 6.1 Key Findings of the Study 160
Chapter 1
Introduction
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1.1 Theoretical Background
Interpersonal conflict is pervasive in every sphere of life and organizations are
no exception. It is inherent part of organizations and researchers predict that the
conflict ridden nature of organizations is going to be intense in future (De Dreu, Van
Dierendonck, & Dijkstra, 2004). Interpersonal conflict interferes with employees
routine work responsibilities and their interrelationships; hence it becomes imperative
to understand how it operates at individual level.
Individuals usually come across two types of conflicts which may be task
related or people related, also known as task and relationship conflicts (Choi, 2010).
Task conflict entails ―differences of opinion about the goals of content of the work
and is often based on facts, data or evidence or the interpretation and application
thereof‖ (Loughry & Amason, 2014). Relationship conflict refers to ―interpersonal
incompatibilities among group members, which typically include tension, animosity,
and annoyance among members within a group‖ (Jehn, 1995, p.258).
Previous research on conflict (Aaldering & De Dreu, 2012;De Drue &
Weingart, 2003;De Wit, Greer, & Jehn, 2012; Jehn, 1995; 1997) has mainly focused
on group level studies and explored team-level outcomes such as group decision
quality (Amason, 1996), groups‘ task performance (Ayoko, 2007), team
performance/team member satisfaction (De Dreu, & Weingart, 2003; Jiang, Zhang, &
Tjosvold, 2013; Passos & Caetano, 2005; ;Puck & Pregernig, 2014), team‘s affective
climate (Gamero, González-Romá, & Peiró, 2008), group performance, decision
quality, financial performance (De Wit, Greer and Jehn, 2012), interpersonal
commitment, satisfaction, in-role/extra-role performance (Lau & Cobb), satisfaction,
wellbeing, and propensity to leave the job (Medina, Munduate, Dorado, Martínez, &
Guerra, 2005). Whereas, most of this research has focused on team level outcomes
(De Wit, Scheepers, & Jehn, 2013; Lu, Zhou & Leung, 2011; Puck & Pregernig,
2014),there is a growing need for studies to be conducted at individual level (De Wit
et al., 2013; Jehn et al., 2010; Lu et al., 2011; Solansky, Singh, & Huang, 2014). Taris
and Schaufeli (2014) state that ―group-level concepts do not necessarily correlate
highly with apparently similar individual-level concepts, implying that concepts
measured at different levels are substantively different‖.
Moreover, group level research on conflict has largely assumed that all
individuals in a group share an equal amount of conflict and this reliance on group
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averages of the perceptions of conflicts results in loss of distinction in individual
perceptions of conflict (Jehn, Rispens, & Thatcher, 2010). Researchers (De Wit, Jehn,
& Scheepers, 2013; Jehn et al., 2010) contend that perception of conflict varies from
person to person, and that studies conducted at individual level should not be
aggregated at team level since Lu et al., (2011) argue that conflict‘s impact on team-
level outcomes may differ from its impact on individual-level outcomes. However, it
has been suggested that research beyond group conflict domain help understand the
role of individual perceptions of conflict on multiple factors like individual behaviors
and attitudes (Solansky, Singh, and Huang, 2014). Kozlowski and Bell (2003) argue
that ―teams do not think, feel, or behave; individuals do‖. They further contend that
―in team level research, where researchers assess data or conduct analysis at the
individual level and aggregate to the team level mostly end up in drawing imprecise
generalizations. Team level studies require multilevel conceptualization which
necessitates that constructs, data, and analyses be aligned with the level to which
conclusions are to be drawn‖ (Kozlowski & Bell, 2003).
Solansky et al., (2014) state that unless we decouple task conflict and
relationship conflict, the distinctive impact of both on individual outcomes cannot be
understood and we would continue to have inconsistent results. It has been argued by
conflict researchers (De Drue et al., 1999; Jehn 1997; Simons & Peterson, 2000) that
relationship conflicts and task conflicts are different phenomena with different
dynamics. Moreover, our knowledge of the process that explains how task conflict
and relationship conflict differentially influence behavior and intentions has been
grounded in a somewhat narrow conceptual lens that has not been examined
extensively. In mainstream conflict research, contingency perspective (Jehn &
Bendersky, 2003) dominated as the prime explanatory framework. Contingency
perspective explains the conditions under which conflict can be constructive or
destructive. Unfortunately, the conflict researchers have not paid much attention to
other factors that can influence the conflict-job performance, and conflict-turnover
intentions relationship. This gap in knowledge is also widened by the fact that less
effort has been made for the identification of factors which may account for the
positive effect of task conflict and negative effect of relationship conflict at individual
level (Lu et al., 2011). To address this gap in theory and research, we adopt
Conservation of resources theory (COR) (Hobfoll, 1989), to explain the relationships
between conflict types and work behaviors.
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Second, in the wider conflict literature dedicated to understanding the task
conflict-work behaviors relationships, findings are still elusive. Particularly, in studies
that consider the effects of task conflict on work behaviors such as performance and
turnover intentions, the results are far from conclusive. This body of research on
consequences of task conflict has yielded paradoxical results (Puck & Pregernig,
2014; De Drue, 2004; De Wit, Greer, & Jehn, 2012; Beldow et al., 2009; De Drue &
Weingart, 2003). Some researchers argue that task conflict yields positive results such
as infusion of creativity in individuals (Matsuo, 2006; Ehie, 2010), improved
performance (Tjosvold, 2008), decision quality and decision commitment (Parayitam
& Dooley, 2009), innovative behaviors and knowledge-sharing behaviors (Lu et al.,
2011) and perceived efficacy (Solansky, Singh, & Huang, 2014). Zhang and Zhang
(2012) argue that task conflict facilitates exchange of information and there is a
positive relationship between task conflict, satisfaction and performance whereas
relationship conflict causes stress and animosity and is largely dysfunctional. Similar
views have been expressed by Ehie (2010) who goes on to say that managers should
strive to contain conflict at task-related issues where it serves as a source of
constructive tension between organizational units. Yet, the findings of the two most
cited meta-analyses i.e., De Dreu and Weingart (2003) and de Wit et al., (2012)
contradict the findings related to positive impact of task conflict. De Dreu and
Weingart (2003) demonstrated that task conflict had a negative impact on team
performance. However, De Wit et al., (2012) did not find any relationship between
task conflict and performance, though they found positive relationship of task conflict
and performance for top management teams than non-top management teams.
Loughry and Amason (2014) contend that intragroup conflict is not dysfunctional per
se, certain types of conflict, under right circumstances and conditions could be
functional. These inconsistent findings call for a more refined and in-depth research at
individual level to gain generalizability of findings on these relationships.
Third, a review of conflict literature indicates that relationship conflict has
received relatively less attention as compared to task conflict (Ismail, Richard, and
Taylor, 2012). It is important to study relationship conflict since negative relations in
social system carry more significance as compared to positive relations for
understanding attitudes and behaviors for the reason that negative relations are more
critical and are shown to have negative impact on behaviors (Sparrowe, Liden,
Wayne, and Kraimer, 2001). Additionally, studies on the consequences of relationship
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conflict have unequivocally proven the deleterious impacts of relationship conflict on
job performance as well as decision making, team effectiveness, job satisfaction,
commitment, and productivity (De Dreu & Weingart, 2003; Passos & Caetano, 2005;
Tjosvold, 2006; Mooney et al., 2007; Gamero et al., 2008; Jehn & Jonsen, 2010;
Huttermann & Boerner, 2011; McKenzie, 2012; Ismail, Richard & Taylor, 2012; De
Wit, Greer, & Jehn, 2012). Relationship conflict was also found to be positively
related to job deviant behaviors and withdrawal behaviors (Choi, 2010; Tepper, Moss,
& Duffy, 2011). While, most of this research has focused on direct relationships, the
underlying mechanisms between task/relationship conflict and work behaviors have
not been explored.
Finally, previous conflict research has primarily devoted itself to task
performance with little emphasis on contextual performance (Choi, 2010; De Drue
and Weingart, 2003; Jehn, 1995). In the next section we provide a critical synthesis of
the key studies in three tables. Table 1.1 presents findings of group-level studies
conducted in western countries (Appendix A). Table 1.2 presents the findings of the
individual-level studies in the same context i.e., western culture, and table 1.3
presents findings of the individual level studies carried out in Pakistan (Appendix B &
C).
We have summarized the findings of key studies in the field of conflict. The
table 1.1 presents the group level studies conducted in Western countries. This also
includes two highly cited meta-analyses by De Drue and Weingart (2003) and De Wit
et al., (2012). The key findings of these studies reveal that findings related to
relationship conflict are equivocal that it negatively affects work behaviors whereas
findings related to task conflict are mixed. Moreover, the focus of this research was
direct relationships except few studies.
Table 1.2 enlightens a summary of findings of individual-level studies. The
findings of these individual level studies reveal that both task and relationship
conflicts differentially predicted individuals‘ workplace behaviors except study by
Avgar et al., (2014) in which both conflict types were positively related with stress
and turnover intentions. In these individual level studies, research conducted by
Kurtzberg and Mueller, (2005) revealed that task conflict had a positive impact on
perceptions of creativity at individual level but the relationship turned negative at
team level. This supports our contention that findings obtained at one level may not
translate at other level.
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Table 1.3 presents the individual level studies conducted in Pakistan in which
focus was on direct relationships except study by Ul-Haq (2011). Relationship
conflict had a negative impact on individual outcomes whereas findings related to task
conflict were mixed. All in all, the findings of these studies reveal that more research
is needed that could address the inconsistencies found in effects of task conflict and
search for the underlying psychological mechanisms linking conflict types with work
behaviors. Therefore, in order to address these gaps in theory and research, we use the
Conservation of Resources (COR) theory as a guiding framework.
The Conservation of Resources (COR) theory (Hobfoll, 1989) is adopted from
the occupational health psychology literature to examine the impact of employees‘
perceptions of task and relationship conflict on employees‘ work behaviors and to
explore the underlying linking mechanisms that explain these relationships. The two
basic principles of the theory will help explain the differential impact of task conflict
and relationship conflict on individual outcomes. The basic tenet of the COR theory is
that ―individuals are motivated to protect their current resources (conservation) and
acquire new resources (acquisition)‖ (Halbesleben, Neveu, Underdahl, & Westman,
2014). The things they value are termed resources that may be defined as objects,
states, conditions, and other things that carry value (Hobfoll, 1988). Based on this
conservation and acquisition tenet, two principles emerge. The first principle of the
COR theory states that ―loss of resources has primacy over resource gain whilst the
second principle is that people invest resources in order to protect against resource
loss, recover from losses, and gain resources‖ (Hobfoll, 2001).
The principle related to resource investment/acquisition may help find the
missing link in the relationship between task conflict and work behaviors such as task
performance, contextual performance, and turnover intentions. This notion gets
stronger with the paradoxical results of studies on the effects of task conflict (Jehn,
1995; Tjosvold, 2008; Zhang & Zhang, 2012). Task conflict entails differences of
ideas, opinions and perspectives on the contents of the task (Jehn, 1995; Solansky et
al., 2014). People exchange their cognitive resources during task conflicts which may
make them more engaged and satisfied with their work since idea sharing, expressing
one‘s preferences/concerns over contents of a task, and differing view-points among
coworkers indicate those activities that may help individuals to voice their concerns,
express themselves and become more focused on their work in technical jobs.
Consistent with the principle of the COR theory pertaining to resource investment, the
26
linking mechanism between task conflict and individual outcomes can be understood
as it is hypothesized that employees invest their cognitive resources in order to
become more engaged and to perform well at work.
The other principle of Conservation of Resources (COR) theory explicates the
resource depletion process in individuals. The COR theory posits that individuals
strive to conserve their valued resources in order to achieve their goals (Hobfoll,
2001). However, the loss of resources is more salient than resource gain. In a similar
vein, the theory states that ―individuals with fewer resources are more vulnerable to
resource loss and less capable of resource gain‖ (Hobfoll, 2001). The theory
articulates that stress occurs in one of the three conditions which are: when resources
are threatened with loss, are actually lost, or when the individuals fail to gain return
on the investment of their resources (Hobfoll, 2001). Using the lens of the COR
theory, the study tests the linking mechanism between relationship conflict and
individual outcomes. In doing so, it argues that relationship conflict is mainly about
the loss of social ties at workplace which creates stress (burnout) and this stress leads
to negative outcomes in individuals.
COR is a motivational theory that builds its foundation on the basic instinct of
individuals related to resource acquisition as well as primacy of loss principal
(Hobfoll, 2001). Using the lens of this theory, the interrelationships between study
variables conflict have been explained. More specifically it is argued that task conflict
is mainly the exchange of cognitive resources among individuals by virtue of differing
opinions, viewpoints and ideas. Moreover, relationship conflict is the loss of social
ties which begets other losses that manifest as burnout which leads to negative
outcomes. Taken together, the present study is an effort to deepen our understanding
of the relationship between task conflict, relationship conflict, different facets of
workplace subjective well-being, task and contextual performance and turnover
intentions of telecom engineers.
The present study incorporates insights from corollary of gain spirals of the
COR theory to explain mediation of different facets of workplace subjective well-
being (work engagement, job satisfaction) in the relationship between task conflict
and work behaviors and intentions. Furthermore, the study borrows the concepts of
corollary of loss spirals of the COR theory to explain the link between relationship
conflict, job burnout and work behaviors at individual level.
27
The introduction section provided an overview of the conflict research. This is
followed by aims and objectives, research questions, significance of the study
alongwith managerial implications leading to research contributions, and limitations.
It concludes with proposed thesis structure.
1.2 Aims and Objectives
The present study aims to provide researchers and practitioners with a better
understanding of the relationship between task/relationship conflict and work
behaviors in the context of technical jobs. By doing so, we also suggest different
underlying mechanisms linking these conflict types with individual outcomes. More
precisely, the present study explores the impact of two dimensions of interpersonal
conflict i.e., task conflict and relationship conflict on three organizationally relevant
outcomes i.e., task performance, contextual performance and turnover intentions
which are key indicators of organizational effectiveness (Newton and Jimmieson,
2009). Hogan and Shelton (1998) argue that performance largely hinges upon social
interactions in most of the present day jobs, an individual‘s interpersonal conflict also
is an important part of the socioanalytic perspective on performance prediction.
According to this perspective people are motivated to get along and get ahead. For
smooth sailing, people need to comply and cooperate with other in a congenial
manner (Hogan & Holland, 2003). Based on this reasoning, studying the factors
associated with job performance and turnover intentions is practical and valuable and
conflict might be particularly relevant here.
Job performance is considered as the most important employee outcome since
it contributes to organizational goals (Bakker, Demerouti, & Verbeke, 2004; Rotundo
& Rotman, 2002; Zhang, LePine, Buckman, & Wei, 2014; Platis, Reklitis, & Zimeras,
2015). ―Job performance is a major contributor of an employee‘s worth to the
organization‖ (Arvey & Murphy, 1998). Zhang et al., (2014) define job performance as
―the aggregated value of the activities that employees contribute both directly and
indirectly, and positively and negatively, to achieve organizational goals‖. Task
performance is the most considered and studied work-related criterion among
academics and practitioners (Devonish and Greenidge, 2010) and the most important
dependent variable in industrial and organizational psychology (Kahya, 2007). The
construct is highly valued since it is an employee‘s great contribution to an
28
organization towards achieving its strategic goals (Arvey and Murphy, 1998; Zhang,
LePine, Buckman, and Wei, 2014; Schat and Frone, 2011). Researchers (Taris &
Schaufeli, 2014) argue that performance is a multidimensional concept, and it is very
important to explore how well an employee performs at his/her job and this cannot be
gauged merely with task performance which is mainly related with performing one‘s
core job tasks. Therefore, the present study explores task as well as contextual
performance. Moreover, the broader conceptualization of performance will help
understand the implications of those behaviors that contribute to the social and
psychological environment at work (Rotundo & Rotman, 2002). Contextual
performance encompasses activities or behaviors that help achieve organizational
goals, while not being part of the prescribed job description (Taris & Schaufeli, 2014).
This includes helping behaviors at work, going an extra mile to achieve one‘s goals,
and being respectful to each other etc., (Motowildo, Borman, & Schmit, 1997). The
two dimensions of job performance help provide holistic view of the outcomes of
individuals.
In organizational behaviors, turnover is one of the highly studied variables
(Price, 2001) and a matter of serious concern for organizations as it results in indirect
costs such as lower productivity due to replacement, and loss of experience. Direct
costs include cost of replacement and training of new employees (Silverthorne, 2004).
It is difficult to measure actual turnover as employee turnover data is often
inaccessible to researchers (Medina, 2012). Hence, measuring turnover intentions is
the next best method to gauge turnover (Lambert, Hogan & Barton, 2001). Moreover,
turnover intention is considered as an actual precursor to turnover (Griffeth, Hom, &
Gaertner, 2000) and is related to the subjective evaluation of an individual regarding
the possibility that he/she may leave the organization he/she works for in the near
future (Mobley, 1982a, 1982b; Carmeli & Weisberg; 2006). Based on our present
theorizing related to conflict types, it is expected that both task and relationship might
have differential impact on work behaviors of the employees.
Jehn and Jonsen (2010) argue that ―organizational conflict affects individual‘s
well-being by influencing social and psychological aspects of work, hence, interferes
with efficient processing of individuals as well as group work.‖ This implies that there
is a possibility of an explanatory mechanism between the direct relationship of task
and relationship conflict with task and contextual performance and turnover
intentions. This theorizing is analogous to the situational perspective for studying
29
individual performance as suggested by Sonnentag and Frese (2002) which assumes
that ―environmental factors i.e., work characteristics affect worker well-being, which
in turn would affect worker performance‖ (Taris & Schaufeli, 2014). In a similar vein,
we theorize that different psychological states may mediate this direct relationship.
Different indicators of workplace subjective well-being i.e., work engagement, job
satisfaction, and job burnout (Bakker & Oerlemans, 2011) have been proffered as
plausible mediators in the direct relationships.
The purpose is to understand and delineate a process that help us understand
how task conflict and relationship conflict distinctively translate their impact to three
most important individual outcomes i.e., task/contextual performance and turnover
intentions (Bakker, Demerouti, & Verbeke, 2004; Price, 2001; Zhang, LePine,
Buckman, & Wei, 2014). In doing so, the study has included three indicators of
workplace subjective well-being i.e., work engagement, job satisfaction and job
burnout (Bakker & Oerlemans, 2011). The choice of these indicators of wellbeing was
guided by three considerations. First, we wanted to include indicators of well-being
most relevant to the workplace settings, thereby including positive as well as negative
forms of well-being. Second, we wanted to ensure compatibility with existing
research on conflict. Third, we wanted to elucidate the complete spectrum of the
theorized COR processes, while including both positive (work engagement, job
satisfaction) as well as negative (job burnout) indicators of well-being. The study
follows the basic principle (resource investment/acquisition of resources) and related
corollary- gain spirals of the Conservation of Resources theory (Hobfoll, 1989, 1998)
to explain the mediation of work engagement/job satisfaction in the link between task
conflict and work behaviors. Moreover, it utilizes the primacy of resource loss
principle and corresponding corollary-loss spirals of the COR to explain the
mediation of job burnout as a mediator in the link between relationship conflict and
work behaviors.
Due to highly specialized jobs of telecom engineers (Anderson, Courter,
McGlamery, Nathans-Kelly, & Nicometo, 2010), task conflict and relationship
conflict may have different implications on their individual outcomes. For instance, as
for task conflict, Jehn (1995, 1997) argued that task conflict in non-routine complex
task enhances the individuals‘ creativity which leads to a better decision making.
Complementing this argument with the resource investment/acquisition principle of
the COR theory (Hobfoll, 2001), different perspectives, ideas, and information
30
exchange as a result of task conflict in technical jobs may lead to accumulation of
knowledge resources since it challenges existing assumptions on which the
individuals build their current arguments. This in turn may manifest in the shape of
positive outcomes in terms of individual‘s task, contextual performance and lowered
turnover intentions. Furthermore, we expect that there is an underlying mechanism
through which task conflict transmits its positive impact on individual outcomes. In
doing so, we have selected two positive indicators of workplace subjective well-being
such as work engagement and job satisfaction. Building further on COR, we argue
hereunder that work engagement and job satisfaction might be considered as conduits
with necessary motivational power that help explain the direct relationships between
task conflict and the chosen study outcomes.
Coming to relationship conflict, which has been equivocally reported as a
work stressor in extant literature (Jehn, 1995, 1997; De Dreu & Weingart, 2003;
Tjosvold, 2006; Gamero et al., 2008; Jehn & Jonsen, 2010; Huttermann & Boerner,
2011; Ismail, Richard & Taylor, 2012; De Wit, Greer, & Jehn, 2012), we expect an
underlying mechanism through which relationship conflict transmit its negative
impact on individual outcomes. The COR theory posits that work stressors initiate a
resource depletion process which leads to negative outcomes in individuals.
Furthermore, a corresponding corollary of the COR theory states that initial loss
begets further loss (Hobfoll, 2001). We expect that relationship conflict (a loss of
social ties) may lead to further loss of resources (job burnout) which in turn lead to
negative individual outcomes. In doing so, we test different dimensions of burnout
such as exhaustion, cynicism and interpersonal strain at work distinctively as
mediators in link between relationship conflict and individual outcomes.
Consistent with our theorizing based on theoretical and empirical support from
conflict researchers (De Drue et al., 1999; Jehn 1997; Simons & Peterson, 2000) that
task conflict and relationship conflict are two distinct phenomena with different
dynamics, following may be considered as the specific objectives of this study:-
Understanding of the distinct impact of task and relationship conflict
on task performance, contextual performance and turnover intentions
of employees.
31
To explore the linking mechanisms between task conflict and work
behaviors (task/contextual performance, turnover intentions) proposing
work engagement and job satisfaction as explanatory mechanisms
To explore the linking mechanisms between relationship conflict and
work behaviors (task/contextual performance, turnover intentions)
proposing exhaustion, cynicism and interpersonal strain at work-
(dimensions of burnout) as explanatory mechanisms
Understanding of the underlying psychological processes linking task
conflict and work behaviors guided by resource investment/acquisition
principle of the COR theory and its related corollary of gain spirals
Understanding of the underlying psychological processes linking
relationship conflict and work behaviors guided by primacy of loss
principle of the COR theory and its related corollary of loss spirals
Understanding of the indicators of workplace well-being such as work
engagement, job satisfaction and job burnout as explanatory
mechanisms
1.3 Problem Statement
To analyze and evaluate the effect of task conflict and relationship conflict on
different dimensions of well-being and work behaviors (task performance, contextual
performance, and turnover intentions) of employees using an individual level
approach. This also includes identification of factors which may serve as conduit to
transmit the positive impact of task conflict and negative effect of relationship conflict
on work behaviors.
1.4 Research Questions
Based on the research objectives as well as the gaps identified in the relevant
literature, following questions have been derived. The first two questions are related
to the direct relationships between the predictors and outcome variables followed by
questions related to mediation of different indicators of workplace well-being
between conflict types and work behaviors:-
32
1) What is the impact of task conflict on (a) task performance, (b)
contextual performance; and (c) turnover intentions?
2) What is the impact of relationship conflict on (a) task performance; (b)
contextual performance (c) turnover intentions?
3) Is the relationship between task conflict and task/contextual
performance and turnover intentions mediated by work
engagement and job satisfaction?
4) Is the relationship between relationship conflict and task/contextual
performance and turnover intentions mediated by exhaustion,
cynicism, and interpersonal strain at work?
1.5 Context of the Study
All of the literature pertaining to interpersonal conflict and work behaviors
leads to the belief that conflict and ensuing behaviors are major concerns in
organizations (Jehn, 1995; De Drue & Weingart, 2003; Tjosvold, 2008; Choi, 2010;
De Wit, Greer, & Jehn, 2012). In academic research, organizations come from a large
pool of different types of industries which are diversified in nature and size. The
findings of one industry cannot be generalized onto the other industry since there are
differences in national as well as organizational cultures, work environments, work
structures, policies and procedures, and profiles of individuals working in different
capacities.
There are remarkable cultural differences in Western context and Asian
context. Hofstede (1980, p. 25) defines national culture as ―the collective
programming of the mind which distinguishes the members of one human group from
another‖. Hofstede (1983) suggested four dimensions of a culture which are ―power
distance, uncertainty avoidance, individualism, and masculinity‖. Later Hofstede
(2010) added two additional dimensions in his model i.e., long/short term orientation
and indulgence/restraint. Power distance is defined as ―the problem of human
inequality and the translation of biological differences in strength and talents into
social differences in power and wealth‖. Uncertainty avoidance refers to ―the
inescapable uncertainty about tomorrow, and the ways in which societies nevertheless
try to enable their members to sleep in peace‖. Individualism refers to ―the problem of
the relationship of an individual to his or her fellows, from tightly to loosely
33
integrated primary groups‖. Masculinity is defined as ―the problem of the division of
mankind into two sexes, and what represents the appropriate role of men (who tend to
make their concept of their own role a model for society as a whole‖ (Hofstede,
1983). Long term versus short term orientation refers to the ―choice of focus for
people‘s efforts whether future, or the present or past. Indulgence versus restraint
refers to ―gratification versus control of basic human desires related to enjoying life‖
(Hofstede, 2010).
Most of the conflict research has been carried out in Western context (Jehn
1995, 1997; De Drue & Weingart, 2003; Jehn et al., 2010; Tjosvold, 2008) where
cultural dimensions are quite different from that of our South Asian region in which
Pakistan exists. Western culture is characterized by high individualism, and low
power distance and uncertainty avoidance whereas the Asian countries have been
characterized by collectivism, high power distance, uncertainty avoidance and
masculinity. Therefore, the findings of the studies conducted in Western context
cannot be generalized to the Eastern context. Moreover, it has been observed that
individuals from low context, individualistic cultures are more competing and
confrontational and less avoiding and obliging as compared to their counterparts from
high context, collectivistic cultures (Zhang & Zhang, 2012).
The interpersonal conflict in collectivist society may have different
implications for individuals and their organizations due to the fact that individuals in
collectivist culture are less confrontational and more cooperative (Jiang, Zhang, &
Tjosvold, 2013). An individual from collectivist culture may not consider task conflict
as threatening due to the concept of shared responsibility as compared to his/her
counterpart from an individualistic culture where self concern is more important.
Likewise, in collectivist societies, ―individuals perceive themselves as part of one or
more collectives and goals of the collectives are preferred over goals of self‖ (Oetzel
& Ting-Toomy, 2003). Due to their closely-knitted social networks, it is expected that
relationship conflict can be a serious threat for individuals as well as their
organizations since it may result in the loss of good employees as it serves to dissolve
their common ties. Moreover, the subordination of organizational goals over the
personal issues warrants deep level analysis of the phenomenon which may cause
severe setback for organizations. The impact of task conflict and relationship conflict
from individual‘s perspective may yield different scenarios which have remained
unexplored so far.
34
The findings of studies in a particular field vary on the basis of the selection of
industry as well. Manufacturing industries and nonmanufacturing industries also
referred to as service industries differ drastically in almost every aspect of their
working life. It is reasonable to assume that the individuals working in a purely
manufacturing concern, doing more routine jobs, non-specialized tasks, will have an
altogether different work environment and experience as compared to their
counterparts in a service-oriented industry doing non-routine, complex tasks. Put
differently, the same types of workplace issues exist in different organizations, yet do
not lead to similar outcomes in terms of type of organizational context. The
differences do exist!
The telecom sector of Pakistan is a service-oriented industry and is some of
the fastest growing segments of the economy. Telecom sector has been selected
because it is one of the promising sectors of Pakistan and this sector has shown an
unprecedented success in past few years (Imtiaz et al., 2015). It has a higher rate of
professional employability and has shown an unprecedented growth (Hussain & Asif,
2012). It is a major contributor of revenue to the government in terms of providing
employment, contribution to the national exchequer through taxes and attracting
foreign investment in the country and playing its active role in economic growth
(Pakistan Telecommunication Authority). In fact, the empirical findings have also
supported that telecom industry positively influenced economic development of the
country (Hashim, et al., 2009).
According to Pakistan Telecommunications Authority‘s annual report (2013-
2014), the telecom sector attracted foreign direct investment inflows of US$ 903
million thus making a significant contribution of 34.2% of the total FDI flow in
Pakistan during this period. During last three years, the sector contributed an average
of Rs. 124.8 billion to the national exchequer on account of its different portfolios. It
is expected that this growth will continue to rise with the introduction of next
generation services in the country. Currently there are five cellular service providing
companies in Pakistan namely Ufone, Warid, Telenor, Mobilink and Zong. These
companies are covering network coverage of almost 92% of land area of Pakistan
(Pakistan Telecommunication Authority). Owing to telecom sector‘s economic
significance since it is expected to contribute to employment growth from 1.6% to
2.4%, it becomes important to study factors that may contribute towards
understanding the behaviors of its employees because viability of an industry hinges
35
upon its happy, contented and productive workforce. A business remains prosperous
as long as its employees make coordinated efforts to sustain its success.
The population of the study has been selected from this sector based on
multiple reasons. Telecom engineers are the core workforce of telecom companies
who perform highly specialized jobs. Van Maanen and Barley (1982) argue that just
like nations and organizations, occupations have their distinct culture. Due to this
culture, engineers believe that the sustainability of the organizational success is
dependent on their engineering capabilities (McIlwee & Robinson, 1992), since
organizations hire engineers for specialized and highly skilled jobs (Ross, 2000).
Their mutual interactions may have very important implications for their work
behaviors and task conflict and relationship conflict are particularly relevant in this
context. This calls for a deep level study on the population which is so far under-
researched (Anwar and Ahmad, 2012). This implies that more research is needed that
may address the implications of task conflict and relationship conflict on their task
performance, contextual performance and turnover intentions at individual level.
Moreover, telecom engineers have non-routine jobs and are on the constant
treadmill of creating novel solutions. They work in a challenging environment since
they are assigned specialized tasks. Their work environment is characterized by less
hierarchical work structures and their reward systems are based on their individual
outcomes. Telecom engineers are considered the backbone of the telecom sectors as
the whole infrastructure of telecom services depends on their highly specialized
knowledge, expertise and experience. In daily working life, telecom engineers come
across different types of task-related conflicts which may emanate from their
discussions about the contents and nature of a task and different ways of doing it.
Similarly, it will be interesting to study the relationship conflict in non-routine jobs.
Another reason for the selection of sample from a single industry is to avoid the
potential confounding effect of other industries. Nonetheless, it is important to study a
population which is so vital for the sustainability of an industry and with the help of
this study we can put forward useful recommendations on the implications of their
interpersonal conflict, work behaviors, and subjective well-being.
36
1.6 Significance of the Study
The study is important for several reasons. First, it provides insight into the
role of interpersonal conflict in the telecom sector. Second, it focuses on work
behaviors and behavioral intentions that are crucial for organizations as well as their
employees. Lastly, it seeks to explore the underlying mechanism that connects
interpersonal conflict with work behaviors and behavioral intentions at individual
level.
Most of the research on interpersonal conflict revolves around intragroup
conflict (Tyastuti et al., 2014; Meng, Fulk, & Yuan, 2015; De Wit, Greer & Jehn,
2012; Aaldering & De Dreu, 2012; Huang, 2010; Greer, Jehn, & Mannix, 2008;
Radford, 2008; Medina et al., 2005; Jehn & Bendersky, 2003; Jehn & Mannix, 2001;
Jehn, 1995) and its impact on organizational outcomes, few studies have measured
conflict at individual level ( Lu et al., 2011; Choi, 2010), whereas researchers (De
Wit, Jehn, & Scheepers, 2013, Lu et al., 2011; Jehn et al., 2010) are of the view that
perceptions of conflict vary from person to person.
In fact Jehn et al., (2010) in their study on group as well as individual
perceptions of conflict argue that individuals vary in their attitudes, reactions and
behaviors due to their perception of more or less conflict than others in their group,
and the findings of the individuals‘ perceptions of conflict should not be aggregated to
teams level (Lu et al., 2011). De Wit, Jehn, and Scheepers (2013) argue that
individual-level consequences of interpersonal conflict must be taken into
consideration since ―individuals differ in their perception of one and the same
conflict.‖ More research will help understand the individual level processes that
account for differential impact of different types of conflicts. Hence, the present study
aims to explicate the interrelationships of study variables at individual level.
Moving forward with the concept, the mechanism linking perceptions of task
and relationship conflict and work behaviors at an individual level is an important
area of study which is so far under-researched (Maria et al., 2005; Medina et al.,
2005; Eatough, 2010; Meier, Gross, Spector, & Semmer, 2013; Meier, Semmer, and
Gross, 2014). More precisely, this study will answer how task conflict exerts its
positive influence on individual outcomes as well as the underlying mechanism
through which relationship conflict negatively impacts these outcomes. This study
will try to find the explanatory mechanism between these variables. The mediators of
37
the study will be explicated with philosophical underpinnings of the conservation of
resources theory. With the help of this theory, the study seeks to explore the different
mechanisms through which both types of conflict operate in organizational setting. In
this way it extends theoretical and empirical research on the COR theory.
Taken together, the study employs multiple mediator approach to answer the
questions about cause-effect relations between conflict types and work behaviors
since Preacher and Hayes (2008) assert that it is of paramount importance to explain
how or by what means a causal effect occurs. Thus it is a multiple mediator study that
seeks to explain the underlying mechanism between interpersonal conflict and work
behaviors. Preacher and Hayes (2008) recommend researchers to consider multiple
mediators in their model guided by the relevant theory since they argue that ―it is
unlikely that the effect of an independent variable on an outcome is transmitted by
only one means‖. Mediation analysis help find ‗fundamental processes underlying
human behavior that are relevant across behaviors and contexts‘ (MacKinnon &
Fairchild, 2009).
Furthermore, three individual outcomes i.e., task performance, contextual
performance and turnover intentions have been chosen to study the interrelationships
among the constructs. Moreover, the study recognizes the need for, and the benefits
associated with testing of the effects of task/relationship conflict on multiple work
behaviors since different perspectives on work behaviors will deepen our
understanding of differential effects of the two dimensions of conflict.
The study used supervisory ratings of the task and contextual performance
thus giving more objective perspective of performance. This also added to the
robustness of findings. Thus, the conceptual schema proposed in the theoretical
framework is validated with high explanatory power. Furthermore, the study used
structural equation modeling to test the hypothesized relationships.
Furthermore, conflict research is dominated by the studies conducted in
Western context whereas there is scarcity of research in Eastern context particularly in
Pakistan. Interpersonal conflict may have different implications in a collectivist
culture where concern for others is more important than concerns for self. Overall,
this study will serve as a platform for a better understanding of the interpersonal
conflicts between peers, its impact on individuals‘ workplace subjective well-being
(work engagement, job satisfaction, and burnout) and consequently on their task
performance, contextual performance and turnover intentions.
38
Last but not the least, the conflict research in Pakistan has mainly focused on
the role of interpersonal conflict mainly as a stressor (Ul-Haq, 2011; Riaz & Junaid,
2012). Less effort has been made to challenge the assumption of treating both types of
conflict as a stressor consistently. The present study takes a different stance where it
deviates from the conventional findings in Pakistani context, and tests the
assumptions theorizing on the basis of motivational process and resource depletion
process of COR. Furthermore, researchers (Lee, Om, Choi, Song, & Kim 2014) state
that there is scarcity of research on IT professionals or engineers as a unit of analysis.
Hence, this study collected data from telecom engineers.
1.7 Managerial Implications of the Study
This study has important implications for practicing managers. The study aims
to offer an insight on the differential effect of interpersonal conflict i.e., task conflict
and relationship conflict on individuals‘ outcomes such as task performance,
contextual performance and their turnover intentions through indicators of workplace
subjective well-being which are work engagement, job satisfaction, and job burnout.
This study will also guide managers how to help their employees during
conflicts (task conflicts, relationship conflicts) as the study proposes that task conflict
has positive impact on task performance and contextual performance and negative
impact on turnover over intentions through its positive impact on work engagement
and job satisfaction. The study will help identify which dimension among the
dimensions of workplace subjective well-being contributes more towards task
performance, contextual performance and turnover intentions. Likewise, the impact of
relationship conflict on different dimensions of burnout will help understand the
plausible effect on afore-mentioned work behaviors.
1.8 Thesis Structure
The thesis is divided into six chapters. The first chapter entails introduction of
the study in which various concepts and definitions of constructs and theoretical
background have been presented alongwith identification of the gaps in relevant
literature. Second chapter covers literature review of study constructs. The third
chapter explicates the interrelationships of the study constructs and delineates first
and second path of the theoretical framework. Fourth chapter is related to research
39
methodology which provides an insight into research design, sample design, data
collection and tools, and data analysis techniques etc. Fifth chapter is related to data
analysis and findings. Final chapter discusses results, recommendations, limitations
and future research prospects.
1.9 Summary
This chapter has outlined the overall research rationale of the present study as
per following details:-
Table: 1.4: Summary of Chapter
Section Details
1
The first section i.e., theoretical background presented the detailed
account of conflict research followed by the description of research gaps
identified in the previous conflict research. This also included key
definitions of the study constructs and related concepts, augmented by
highlights of the key account of previous conflict research presented in
tabular form. This section also discussed the Conservation of Resources
(COR) theory and its related corollaries that help explain the proposed
relationships between the study constructs. The relationship between
task conflict and work behaviors (task/contextual performance and
turnover intentions) were explained on the resources
investment/acquisition principle of the COR theory.
2
Furthermore, the links between relationship conflict and work behaviors
were explicated in the backdrop of resource depletion principle of the
COR theory.
3
The next section entailed the aims and objectives of the study and
subsequently the research questions derived from these aims and
objectives.
4
This was followed by the significance of the study, managerial
implications of the research and key research contributions alongwith
limitations of the study.
5 The chapter concluded with the overall thesis structure.
40
Chapter 2
Critical Review of Literature
41
Critical Review of Literature
The literature review consists of two chapters. The first chapter entails the
detail of the study constructs. It starts with theoretical overview of the conservation of
resources (COR) theory. This is followed by synthesis of previous literature on key
constructs of the study which include- interpersonal conflict, types of conflict- task
and relationship conflict, outcome variables- task/contextual performance, turnover
intentions, and mediators- work engagement, job satisfaction, and job burnout.
The second chapter introduces the framework for this study that comprises the
main focus of the research described in this thesis. It delineates the interrelationships
among study constructs on the basis of the COR theory. In doing so, the study
explains the outcomes of task conflict utilizing a resource investment/acquisition
approach and gain spirals and suggests work engagement and job satisfaction as the
plausible mediators in the link between task conflict and individual outcomes.
Moreover, the study explicates the outcomes of relationship conflict utilizing a
resource depletion approach based on the primacy of loss principle and loss spirals,
whereby it suggests the different dimensions of job burnout (exhaustion, cynicism and
interpersonal strain at work) as the putative mediators between the link of relationship
conflict and work behaviors. The chapter concludes with an overview of the complete
model.
2.1 The Conservation of Resources (COR Theory)
Contingency perspective propounded by Jehn and Bendersky (2003) has
dominated the literature on the relationship between interpersonal conflict and
employee outcomes. This perspective mainly highlighted the conditions under which
conflict can be productive or destructive. However, it could not delineate the linking
mechanisms between conflict and employees‘ work behaviors. The current study
introduces the Conservation of Resources (COR) theory as an alternative theoretical
lens through which the relationship between conflict types and work behaviors could
be explained. The COR theory also guides the underlying psychological process
between conflict types and work behaviors.
The Conservation of Resources theory was proposed by Stevan Hobfall (1989,
1998). This is a stress and motivational theory that has contributed tremendously to
42
both the theoretical and applied organizational literature (Dewe, O‘Driscoll, &
Cooper, 2012; Hobfoll, 2011). The theory was developed in response to integrate both
the objective and perceived environment in the process of coping with stress (Hobfoll
& Schumm, 2002). The COR theory goes beyond other competing theories of stress
as it delineates ―what individuals do when confronted with stress vis–a-vis when not
confronted with stress, and unlike previous theories, the COR theory help predict
psychological or behavioral action when individuals are not confronted with
stressors‖ (Hobfoll, 1989). It has become a fundamental theory in the field of stress
and positive psychology, especially in challenging work environments (Hobfoll,
2001)
The basic tenet of the COR theory is that ―individuals strive to obtain, retain,
protect, and foster those things that they value‖ (Hobfoll, 2001). A ―resource‖ is
anything that carries value for a person, contributes positively to his well-being and
enables him to adjust accordingly (Dewe et al., 2012). Moreover, ―framing individual
resource is only meaningful within an ecological context‖ (Hobfoll, 2011). Hobfoll
(2001) contends that ―the value of a resource originates from its being desired goal
object as well as instrumental in the acquisition or maintenance of desired resources‖.
Hobfoll (2002) simplified the definition of resources- as ―entities that either are
centrally valued in their own right or act as a means to obtain centrally valued ends‖.
Halbesleben, Neveu, Underdahl, and Westman (2014) have redefined resources as-
―anything perceived by the individual to help attain his or her goals‖. The value of the
resources varies according to the context that determines the relative significance of a
particular resource (Halbesleben et al., 2014). More precisely, ―the value of our
potential resources is culturally defined and hinges upon the social environment that
surrounds us‖ (Gorgievski & Hobfoll, 2008). This implies that people invest their key
resources to maintain their self, sustain their social relations, and to behave and adapt
in the broader context of organizations and the culture (Hobfoll, 2011).
Hobfoll (1989) identified four kinds of resources. Object resources are valued
because of their physical nature or socioeconomic status such as home or car.
Conditions are resources to the extent they are valued such as being married or living
with someone (Hobfoll, 1989). Personal characteristics are resources to the extent
they help reduce stress. Hobfoll indicated that research has so far identified 74
different types of resources which can be categorized as ―personal‖ resources whereas
others as features of the environment (external resources). Personal resources include
43
personal values (the significance of success), personality traits (e.g., internal locus of
control, hardiness, optimism and self-esteem) and positive affect. Environment factors
may include job autonomy, performance feedback, rewards against improved
performance, social support from peers and organizational support are also among key
environmental resources, which may reduce stress and burnout (Dewe et al., 2012).
The fourth category of resources i.e., energy resources include time, money, and
knowledge (Hobfoll, 1989).
The COR theory is built around two fundamental principles. The first principle
of the COR theory is that loss of resources is more pronounced than gain since loss
related events have strong effect on people‘s physiological, cognitive, affective, and
social responses. Hobfoll (2011) states that ―resource loss is disproportionate not only
in terms of degree, but also speed‖. This loss of resources is followed by
psychological distress (Hobfoll, 2001) since individuals have diminished coping
capabilities to counter future challenges (Hobfoll & Schumm, 2002). According to the
COR theory individuals may gain or lose from four major types of valued resources
which include object resources, condition resources, personal resources, and energy
resources. More precisely, human beings value food, shelter, positive self-evaluation
and primary social ties (Westman, Hobfoll, Chen, Davidson, & Laski, 2004).
The second principle is related to resource investment. It states that ―people
invest resources so as to immune against resource loss, to recuperate from losses, and
attain resources‖ (Westman et al., 2004; Halbesleben et al., 2014). The corresponding
corollary of this principle is that individuals who possess more resources are less
vulnerable to resource loss and are more likely to gain resources than their
counterparts with few resources. This enables them to substitute resources for those
lost or absorb the loss to invest in from available pool (Hobfoll, 2002). Conversely,
those who possess few resources are more vulnerable to resource loss (Westman et
al., 2004) .Individuals who begin with borderline resource reserves are more likely to
be in a precarious position (Hobfoll, 2002).
The other corollaries follow that trail and second corollary states that initial
resource loss leads to future resource loss (a resource loss spiral)because individuals
utilize their resources to offset loss, hence at each stage of an ongoing stress cycle,
there are fewer resources to employ for defense, thus giving rise to ―loss cycles‖
(Hobfoll, 2001, p. 354). ―These loss spirals move with greater strength and speed as
the individuals, groups, and organizations either lose the resources to meet challenges
44
or acquire resources so they could risk looking for new challenges‖ (Hobfoll, 2011).
The corresponding third corollary contends that initial resource gain leads to future
resource gain (a resource gain spiral). The gain spirals are critical for workplaces.
Moreover, ―individuals are motivated for gain as well as to prevent resource loss‖
(Hobfoll, 2011). Finally, fourth corollary states that lack of resources leads to
defensive attempts to conserve remaining stock of resources (Halbesleben et al.,
2014)
The concept of spiral is embedded in the belief that when individuals have few
resources to deal with stressful events, they become more vulnerable in that scenario
alongwith a trail of further resource losses thus initiating a ―loss begets loss‖ of
resources (Hobfoll, 2001).However, because loss is more salient than gain, loss
spirals will have more intensity and speed than gain cycles (Westman et al., 2005).
Similarly, there are resource gain spirals which attain their momentum when there is
reinforcement of resources. In addition to these gain/loss spirals, OR theory also
incorporates the concept of resource caravans. This view suggests that resources
accumulate and build upon each other, thus strengthening one another. The impact of
these resources tends to hold across time and different circumstances (Hobfoll,
2002).Individuals at work are capable of maintaining and developing their resource
caravans, or conversely fail to foster and maintain them either by their own skill or
effort, but much of the condition that surround social ecologies in organizations which
are beyond individual‘s control (Hobfoll, 2011).
The COR theory guides the theoretical framework of the study. Using the lens
of its key principles related to resource investment/acquisition and primacy of
resource loss (Hobfoll, 2001), the interrelationships between the study variables have
been delineated.
2.2 Conflict
The concept of conflict is as old as human civilization. Since organizations are
made up of human beings who each have their own thoughts, feelings and priorities,
hence their interactions may yield pleasant or unpleasant disputes or conflicts, thus
making conflicts an inherent part of the organizational life (Martínez-Corts et al.,
2011; Curseu et al., 2009; Gamero et al., 2008; Suliman and Al-Shaikh, 2007;
McGrane et al., 2005; Rahim et al., 1999; Putnam and Poole, 1987). Suliman and
45
Abdulla, (2005) argue that understanding organizational conflict and how it affects
employees‘ behavior and their performance has become much more important than it
was in the past. Ehie (2010) argues that ―organizations without conflict operate at
comfortable mediocrity and this may spell doom for these organizations.‖
Conflict has been defined differently by researchers. Rahim (2011) defines
conflict ―as an interactive process manifested in incompatibility, disagreement, or
difference within or between social entities (i.e., individual, group, organization,
etc.)‖. It can be viewed at the individual, group, or organizational level. Early conflict
literature depicted conflict as counterproductive and harmful for organizational
functioning (Pondy, 1967). Before 1990s, majority of conflict theorists presented a
negative view of the conflict and considered it counterproductive (Jehn & Bendersky,
2003), which prevailed for long time. The underlying premise of this research was
that conflict is bad and efforts must be made to eliminate as much conflict from the
workplace as was possible. This view was challenged by conflict theorists (Amason &
Schweiger, 1997; Jehn, 1995, 1997; Jehn & Bendersky, 2003; Tjosvold, 2008) and it
was suggested that under specific condition conflict can yield positive outcomes. This
body of research gave rise to the famous typology of conflict i.e., task conflict and
relationship conflict (De Drue & Weingart, 2003). This rationale changed the
direction of conflict research and more studies came up with the positive results of
task conflict (Chen et al., 2011; Lu, Zhou, & Leung, 2011; Matsuo, 2006; Parayitam
& Dooley, 2009). It was argued that task-related conflict can results in increased
satisfaction with group decisions as well as their intention to stay in the group.
However, results on the consequences of relationship conflict remained consistent (De
Drue & Weingart, 2003; De Wit et al., 2012)
The research on conflict bifurcates into two main streams of conflict; positive
conflict and negative conflict, whilst the emphasis has been more on negative
dimension of conflict (Huttermann & Boerner, 2011; Massey & Dawes, 2007; Ayoko
& Hartel, 2006; Baer, 2006; Medina et al., 2005; De Dreu & Weingart, 2003; Jehn,
1995; Amason, 1996). Halevy, Chou, and Galinsky (2012) contend that ―conflict is
often the process of testing and assessing oneself and at times may be highly
enjoyable as one experiences the pleasure of the full and active use of one‘s
capacities. Hence conflicts can sometimes produce taxing stress and other times
vitalizing arousal‖. Tillet and French (2006) argue that conflict can encourage
dialogue, foster personal and professional growth, provide opportunities for problems
46
to be discussed and solved, and prevents stagnation. The multidimensional nature of
conflict has made researchers to come up with divergent views about it. It has both
constructive (Tjosvold, 2008; DeDreu & Weingart, 2003; Jehn, 1995) as well as
destructive dimension (Ayoko & Hartel, 2006; Baer, 2006; Amason, 1996). Medina et
al., (2005) categorized conflicts as functional and dysfunctional conflicts. Benítez et
al., (2011) termed these dimensions as ―cognitive, functional or task component, and
an affective, dysfunctional or relational component.‖According to these researches,
task conflict has been termed as positive conflict and relationship conflict has been
termed as negative conflict. But still there is dearth of studies regarding the linking
mechanisms through which task conflict yields positive outcomes and relationship
conflict yield negative outcomes.
The present study explores the dynamics of conflict types at individual level in
context of technical jobs. Following section will discuss interpersonal conflict:-
2.2.1 Conceptualization of Interpersonal Conflict
Interpersonal conflict refers to a perception of different parties having
different views or conflicts due to their interpersonal incompatibilities (Jehn, 1995).
Interpersonal conflict has been divided into two main types by conflict researchers
(Jehn, 1995, 1997; Solansky et al., 2014) which are task conflict, and relationship
conflict. Barki and Hartwick, 2002, further elaborated that interpersonal conflict in
organizations is the result of task-related issues or task conflict and non-task related
issues such as relationship conflict. Task conflict has been also termed as affective
conflict and relationship conflict as emotional conflict (Bradford &Weitz, 2009).
Task conflict as defined by Jehn (1997) is ―group members‘ perception of the
disagreements about the actual tasks being performed even though the ultimate goal
and objective about task in the group may be shared.‖ In other words task conflict is
about differences of ideas and opinions about work (Ayoko and Pekerti, 2008).
Employees term this conflict as ―work conflict, work disagreements, and task
problems.‖ It may be inferred that task conflicts are focused on work per se and task
at hand (Jehn & Bendersky, 2003). Researchers argue that task conflict is good for
team creativity and innovation (De Drue, 2008), but empirical evidence is
inconclusive. Moreover, the underlying mechanisms linking task conflict with
47
performance and withdrawal behaviors have not been explored. This research will
address this vacuum in literature.
The other type of conflict i.e., relationship conflict relates to differences
arising out of personal and social issues that are not associated with work (Jehn &
Chatman, 2000). Relationship conflict may arise due to incompatibility among
individuals on the basis of personal liking or disliking, religion, sect, gender, and
political affiliation etc., hence the conflict pertains to people. Previous researchers
(Barki & Hartwick, 2004; De Drue & Weingart, 2003; Huang, 2010) have concluded
that relationship conflict is detrimental for the job performance of individuals. It will
be interesting to investigate how it is related to individual outcomes through
mediation of negative indicators of well-being i.e., job burnout.
Jehn and colleagues (1997, 1999) identified another type of conflict; process
conflict and it is related to differences over work allocation and especially who is
going to do what (Ayoko and Pekerti, 2008, Jehn, 1997; Kabanoff, 1991). This type
of conflict may induce feelings of unfair allocation of tasks/work assignment and
injustice in their procedures. But researchers such as Shaw et al., (2011), Huang
(2010) and Barki and Hartwick (2004) argued in their research that there are
conceptual and empirical problems with process conflict. In fact, it is part of the task
conflict and not a distinct type of conflict. Moreover, measures of process conflict
have not been found to be empirically different from those of task conflict (Behfar,
Mannix, Peterson, & Trochim, 2010). Therefore, this study focuses on task conflict
and relationship conflict and their relationship with different indicators of well-being
and individual outcomes.
2.2.2 Conflict with Coworkers
Workplace conflict operates at two levels in organizations- horizontal conflict
(conflict between peers) and vertical conflict (conflict between employees and their
supervisors). Both levels of conflict have different individual as well as organizational
outcomes as individuals relate differently to these two categories (Frone, 2000;
Hershcovis & Barling, 2010). Likewise, ―conflict structure may vary according to the
relative hierarchical positions of those involved in the conflict‖ (Xin and Pelled,
2003). Keeping in view the less hierarchical set-up of telecom engineers, and the
nature of their complex jobs, the present study considered horizontal conflict (conflict
48
between peers) as the relevant level since Frone (2000) suggests that professional
employees may have collective sharing relation with their supervisors because they
may be considered as peers and colleagues as both are engineers. Moreover,
relationships with co-workers are one of the most meaningful interpersonal
relationships individuals have at work (Mckenzie, 2015).
―Coworkers may possess social power to the extent that they are more likely
to affect the presence and quality of social relationships at work‖ (Hershcovis &
Barling, 2010). This is because coworkers are able to affect the interactive processes
in the form of relevant information and feedback, practical assistance, and emotional
support relevant to the stressful work conditions (Joiner & Bartram, 2004). Conflict
with peers may have more pronounced effect on individuals since they spend most of
their time with them and issues related to modus operandi of certain tasks are more
likely to be raised and discussed among peers due to their close proximity to the same
problems (Martínez-Corts, Boz, Medina, Benítez, & Munduate, 2011). Due to their
substantial interactions and interdependence, individuals may encounter task-related
or relationship-related conflicts.
Conflict with coworkers is considered critical to cognitive and socio-cognitive
development because discussions between colleagues manifest a unique form of
discourse that requires each participant to articulate and critically analyze multiple
perspectives (Laursen & Hafen, 2010). Moreover, differences between equals do not
involve power assertion but it requires negotiation (Laursen and Hafen, 2010).
Evidence suggests that coworkers can make a relatively clear distinction between task
conflict and relationship conflict (Amason, 1996; Jehn, 1995; Xin and Pelled, 2003).
It has been argued that conflict with co-workers leads to psychological outcomes
whereas conflict with supervisors leads to organizational outcomes (Frone, 2000). The
present study takes a step forward in that direction using the lens of the COR theory
where it explores the link between task conflict, relationship conflict, psychological
outcomes (different indicators of workplace subjective well-being), and
organizationally relevant outcomes. Throughout this thesis, terms like coworkers and
peers will be used interchangeably.
49
2.2.3 Consequences of Task Conflict
Task conflict entails disagreement ―about the content and outcomes of the task
being performed‖ (De Wit et al., 2012). It is the difference of ideas, viewpoints, and
perspectives related to tasks at hand (Jehn, 1995). Conflict of this nature might be
considered as work conflict, work disagreement, or task disagreement, which implies
that such type of conflict relates to work itself and issues related to work tasks (Jehn,
1997), hence also termed as intellectual opposition of ideas, approaches and
viewpoints. Task conflict exists when individuals have differing opinions related to
work such as goals to achieve, the ways to do it, distribution of the outcomes,
judgments, and interpretation of facts (Amason, 1996; De Drue and Weingart, 2003;
Jehn, 1997; Solansky et al., 2014). Research on task conflict is inconclusive and the
results are largely inconsistent as it has yielded positive (Amason, 1996; Behfar,
Mannix, Peterson, and Trochim, 2011, Jehn, 1995, 1997; Lu et al., 2011; Puck, and
Pregernig, 2014; Solansky et al., 2014), negative (Beldow et al., 2009; De Drue, 2006;
De Drue & Weingart, 2003; Medina et al., 2005), and insignificant results (De Wit et
al., 2012). Researchers (De Drue,2008; Tjosvold, 2008; Jehn, 1995) argue that task
conflict may enhance creativity and innovation in individuals because they exchange
ideas and their opposing viewpoints lead to a better decision during their discussion.
Jehn (1995) stated that task conflict in non-routine complex task results in divergent
thinking and creative solutions. Jehn and Bendersky (2003) suggest that task conflict
at individual level may increase effort, enhance task focus, and increase divergent
cognitive perspectives on the issue. Task conflict infuses new ideas and triggers new
discussion which results in multiple alternatives, creative solutions and innovations
(Ehie, 2010). It is important to mention here that ―task conflict tends to be a one-time
occurrence, which means that it can be resolved in a single episode‖ (Zhang & Zhang,
2012).
Matsuo (2006) argues that task conflict infuse creativity in individuals. When
employees are involved in open discussions, it results in cost effectiveness, improved
quality, innovative use of technology and effective restructuring (Tjosvold, 2008).
However, there is another stream of research which says that intense task conflict is
not good for performance such as meta-analysis by De Drue and Weingart (2003)
revealed that intense task conflict leads to relationship conflict and is detrimental for
team performance. Puck and Pregernig (2014) found a negative relationship between
50
task conflict and team‘s performance mediated by cooperation. Task conflict
negatively affected cooperation among team members which had a negative impact
on its performance. While most of this research has taken into account group-level
effects of task conflict, researchers (Lu et al., 2011; Jehn et al., 2010) argue that
findings obtained at one level do not apply to other level, an individual level approach
is more relevant to our line of inquiry.
Parayitam and Dooley (2009) found in their study that task conflict is
positively related to decision quality and decision commitment and it plays a pivotal
role in strategic decision- making as it facilitates the flow of information among team
members (Ehie, 2010). Conflict generated by paradoxical frames (contradictory
alternatives) enhances individual‘s creativity and tendency to think out of box. Similar
views have been expressed by Farh et al., (2010) that task conflict has a curvilinear
relationship with team creativity and creativity is at its peak at moderate level of
conflict. Experienced conflict results in multiple perspective-taking and novel insights
of problem at hand (Miron-Spektor, Gino, and Argote, 2011). It means that opposing
opinions of individuals lead to creative solutions.
Lu et al., (2011) studied impact of task and relationship conflicts on individual
work behaviors. The researchers found positive relationship between task conflict and
innovative behaviors and knowledge sharing behaviors. Relationship conflict was
found to be negatively related to both individual-directed organizational citizenship
and knowledge sharing behavior.
Bradley, Postlethwaite, Klotz, Hamdani, and Brown (2012) argued in their study that
task conflict has a positive effect on team performance in presence of team
psychological safety climate. Peterson et al., (2006) stressed upon the need of trust in
reaping the benefits of intragroup task conflict.
Meier, Gross, Spector, and Semmer (2013) investigated a within individual
effects of task conflict and relationship conflict on angry mood and somatic
complaints. The researchers found main effect of relationship conflict on angry mood
but not on somatic complaint. However, after controlling for relationship conflict, task
conflict was found to be unrelated to both angry mood and somatic complaints.
However, task conflict moderated the effect of relationship conflict. The researchers
termed task conflict as a ‗double-edged sword‘, containing seeds of creative solutions
but at the same time some individuals may consider it an attack on their viewpoint.
51
Zhang & Zhang (2012) explored the impact of task and relationship conflict
on relational satisfaction, suggesting culture as a mediator. The sample consisted of
university students from United States and China. The researchers found that task
conflict is more likely to be resolved and is associated with higher relational
satisfaction than relationship conflict in both cultures.
Jiang, Zhang, and Tjosvold (2013)suggest that task conflict in complex jobs
involves deliberate discussions about the task and enhances individual‘s ability to
concentrate on tasks more deeply, and can be beneficial to performance. This also
contributes to deliberate information processing among individuals which fosters
learning and creative insights, finally leading to innovative behaviors.
Solansky, Singh, & Huang, (2014) investigated the effect of task and
relationship conflict on individuals‘ perceptions of group efficacy and group mind.
Individual perceptions of group efficacy and group mind were significantly higher
when they perceived non-occurrence of conflict as compared to frequent conflict
episodes. When the conflict types were decoupled, the perceived efficacy and mind
score were found to be significantly higher in case of task conflict than when both
types of conflict co-occurred.
Review of the relevant literature shows that research has yet to reach a
consensus on the relationship between task conflict and performance at work, and
accounting for this inconsistency is crucial for theoretical and practical reasons. Since
most of research on task conflict deals with group level studies (Lu et al., 2011), this
study measures the conflict perceptions at individual level and its impact on task
performance, contextual performance and turnover intentions of employees.
Moreover, the findings of these studies suggest that task conflict and work behaviors
may have an explanatory mechanism through which task conflict leads to positive
outcomes. It is predicted that different indicators of workplace subjective well-being
i.e., work engagement, and job satisfaction may explain the intervening mechanism in
this relationship. In this way, the present study also tries to add something to existing
knowledge regarding the contribution of these different types of conflicts in
organizational setting in context of different forms of employees‘ subjective
wellbeing and work behaviors.
52
2.2.4 Consequences of Relationship Conflict
Human beings are social entities that are part of a larger social network of the
world we live in. Individuals value their relationships and derive information based on
the dynamics of these relationships (Festinger, 1954). Strong social networks protect
against stressful encounters. In fact, the presence of social entities who can be
confided in and whose relationships matter is the most salient type of support
(Hobfoll, 2002). Reich and Hershcovis (2010) define an ―interpersonal relationship
(being an inescapable reality in organizations) as an individual‘s subjective
experience of repeated interaction or connection with another individual‖.
Relationships among peers are can make an organization pleasant or miserable and
also determine the extent of their attachment or withdrawal. These relationships may
influence us in positive as well as negative ways (Berscheid & Reis, 1998). However,
the deleterious outcomes of damaged relationship may engender more harm than the
benefits of a positive relationship (Reich & Hershcovis, 2010). Therefore, the
importance of interpersonal relationships calls for a deeper analysis of the
phenomenon which may sabotage the smooth functioning of organizations‘ most
valuable asset. Moreover, a growing body of evidence suggests that relationship
conflicts at work are an important source of work stress and a suitable stressor to
focus on in an overall context of organizational functioning.
Relationship conflict also known as affective or emotional conflict (Pelled et
al., 1999) refers to interpersonal or socioemotional disagreements, disputes or
negative social interactions which include feelings of tension, aggression, frustration
and contempt among or between individuals on a personal level (Amason 1996; Jehn,
1995, 1996; Isaksen & Ekvall, 2010). Relationship conflict with co-workers is defined
as tension or disagreement within an employee-co-worker relationship. It occurs from
negative emotional interactions or personality clashes between two or more
individuals that are in a personal or work-related relationship. Unlike task conflict
which can be resolved in a single episode, relationship conflict can be serial and may
occur repeatedly in interpersonal interactions(Zhang & Zhang, 2012), thus difficult to
resolve (Bear, Weingart, and Todorova, 2014) and the resulting negative
psychological states have been said to be a major source of employee stress (Avgar et
al., 2014).
53
Relationship conflict entails negative emotionality (Jehn, 1997), ―personality
clashes which involve rude interpersonal exchanges, cynical comments, and disregard
for fellow colleagues‖ (Jehn, 1994; Solansky et al., 2014). It occurs when individuals
dislike and distrust each other (Amason, 1996). It affects individual and
organizational outcomes negatively (Lu et al., 2011; Choi, 2010; Lau & Cobb, 2010).
Relationship conflict has been found to be negatively related to job performance and
decision making, team effectiveness, productivity, job satisfaction, commitment and
is related positively to withdrawal behavior (De Dreu & Weingart, 2003;Passos &
Caetano, 2005; Tjosvold, 2006; Mooney et al., 2007; Gamero et al., 2008; De Jong et
al., 2008;Jehn & Jonsen,2010; Huttermann & Boerner, 2011; Martínez-Corts et al.,
2011; Wang & Nasr, 2011;McKenzie, 2012;Ismail, Richard & Taylor, 2012).
De Dreu and Weingart (2003) argued in their meta-analysis that relationship
conflict does more damage to team satisfaction as compared to task conflict.
Relationship conflict results in more negative consequences for individuals and
organizations e.g., anxiety, stress, frustration, tension, poor task performance, and
inability to concentrate and analyze the situation at hand (Kacmar, Bachrch, Harris, &
Noble, 2012; Wang & Nasr, 2011; Choi, 2010; Ren & Gray, 2009). Kacmar et al.,
state that relationship conflict entails an aggregation of behaviors and negative
interpersonal experiences that indicates frustration and interpersonal rifts and lead to a
wide array of negative emotions and affective outcomes. The negative repercussions
of relationship conflict not only affect individuals‘ core work activities but also result
in poor organizational performance (Kacmar et al., 2012).
Employees undergoing relationship conflict exert their cognitive attention on
interpersonal issues which limits the use of their cognitive resources for task related
issues and diverts their behavior, energy and time away from the job (Bouckenooghe,
De Clercq, & Deprez, 2014). Relationship conflict impedes receptivity of each other‘s
opinion and ideas thus hampering their information processing capability (Van der
Kam et al., 2014). It also limits infusion of novel ideas, cognitive flexibility and
creativity, and processing of useful information which in turn affects their
performance (Van der Kam et al., 2014; Lau & Cobb, 2010; Kacmar, Bachrach,
Harris & Noble; 2012).
Parayitam & Dooley (2009) found in their study that relationship conflict is
not negatively related to decision quality but negatively related to decision
commitment. Hen, Zhang, & Vogel (2011) argue that relationship conflict negatively
54
affects attitude and performance. Negative psychological responses resulting from
relationship conflict deteriorate satisfaction in individuals and they focus more on
interpersonal attacks rather than work per se which result in poor performance (Jehn,
1995). Individuals undergoing relationship conflict do not share useful information
among themselves since they dislike each other. Relationship conflict negatively
impacts individual directed citizenship and knowledge sharing behaviors (Lu et al.,
2011).
Meier et al., (2013) explored short-term within-individual effects of
relationship and task conflict on angry mood and somatic complaints. Through daily
diary study, the researchers found main effect of relationship conflict on angry mood,
but not on somatic complaints. Controlling for relationship conflict, task conflict was
found to be unrelated to both outcomes. Moreover, task conflict moderated the effect
of relationship conflict such that relationship conflict had a prospective effect on
angry mood and somatic complaints that lasted till the following day when the task
conflict was low.
Recently, Meier, Semmer, and Gross, (2014) have investigated the effect of
relationship conflict on psychological and physical well-being. Relationship conflict
had a negative effect on both forms of well-being and the effects were strong for
employees with high levels of depressive symptoms. Hence, depressive symptoms
moderated the effect of relationship conflict on psychological and physical well-
being. The researchers suggested that conflicts may cause depressive symptoms thus
making people even more prone to conflicts, initializing a vicious circle involving
serious psychological and economic setbacks for individuals as well as their
organizations.
Giebels and Janssen (2005) found a positive relationship between stress
caused by workplace conflict and negative indicators (emotional exhaustion,
absenteeism, and turnover intentions) of employees‘ well-being. It was further
revealed that controlling for relationship conflict, there was no negative relationship
between stress and task conflict. The researchers further argued that relationship
conflict owing to its detrimental effect on personal identity and self-esteem lead to
tension and stress in individuals.
Research is replete with studies on the consequences of relationship conflict
on group performance and outcomes (Jehn, 1995, 1997; De Drue & Weingart, 2003;
Huang, 2010) whereas there is dearth of studies at individual level. Since individuals
55
differ in their perceptions of conflict (Jehn, 2010), therefore, more studies are needed
to understand the effect of relationship conflict on individual level outcomes.
2.3 Conceptualization of Outcome Variables
2.3.1 Task and Contextual Performance
Job performance is the most considered and studied work-related criterion
among academics and practitioners (Devonish & Greenidge, 2010) and the most
important dependent variable in industrial and organizational psychology (Kahya,
2007). The construct is highly valued since it is considered to be the greatest
contribution an employee can make to an organization as it contributes to the
achievement of organization‘s strategic goals and competitive edge (Arvey and
Murphy, 1998;Zhang, LePine, Buckman, and Wei, 2014).In fact, ―it represent the
primary contribution of individuals to organizational effectiveness and the primary
reason individuals are employed by organizations‖ (Schat & Frone, 2011).It is a
behavior which is related to what people do at work (Motowildo, Borman, &
Schmit,1997). Job performance as defined by Wetzels et al. (2000) is ―the degree to
which employees execute tasks, responsibilities, and assignments.‖ Motowidlo (2003)
defined job performance as ―behaviors that can make a difference to organizational
goal accomplishment‖.
Although it is difficult to come up with a universally accepted definition of job
performance, Devonish and Greenidge (2010) argue that ―traditional definitions of job
performance have confined this construct to mere coverage of task-related behaviors;
nonetheless, this myopic view of job performance has been challenged by many
researchers (Dalal, 2005)‖. Furthermore, Demerouti, Bakker, & Leiter (2014) contend
that task performance per se is very important, but it does not entail the whole range
of human performance at work. Moreover, meta-analysis by Koopmans, Bernaards,
Hildebrandt, Schaufeli, de Vet Henrica, and Van der Beek, (2011) revealed that two
factors common to most of the models of work performance are: task performance
and contextual performance, however, they stated in their meta-analysis that task or
in-role performance is the central dimension of job performance. Hence, the present
study included two dimensions of job performance to provide a broader perspective
on the relationships among study constructs.
56
The theoretical distinction between task and contextual performance was made
by Borman and Motowidlo (1997). ―Task or in-role performance entails behaviors
that fulfill the prescribed duties of a certain job or in other words outcomes and
behaviors that directly serve the goals of an organization‖. Taris and Schaufeli (2014)
define it as ―proficiency (competency) with which workers perform their central job
tasks, or sometimes to the degree to which workers achieve the central goals of their
jobs‖. ―Contextual performance entails behaviors or actions on the part of the
employees that goes beyond the formal job descriptions and help maintain and
enhance the social-psychological work environment that supports task performance‖
(Schat & Frone, 2011; Borman & Motowidlo, 1993). These behaviors are
discretionary in nature that are not part of the formal duties, but contribute to the
effective functioning of organization (Athanasou & King, 2002). Organ (1997) states
that ―contextual performance does not have to extra-role but just extra-task‖; these
behaviors complement the facilitation of core tasks and managers give equal weight to
contextual performance as to task performance in evaluation of overall performance
(Borman & Motowidlo, 1997).
Contextual performance is beneficial and desirable from organization‘s
perspective since it contributes towards organizational effectiveness and shape the
organizational, social, and psychological context that facilitate task activities and
corresponding processes (Borman & Motowidlo, 1997). Contextual performance is
crucial since it is under motivational control of the individuals (Griffin, Neal, and
Neale, 2000). It includes activities such as helping and cooperating with each other;
showing respect to others (Taris & Schaufeli, 2014); following rules and regulations,
going an extra mile for achieving organizational objectives; enthusiastically
accomplishing one‘s own tasks and performing task activities that are not part of the
core duty (Motowildo et al., 1997). These activities result in improvement in co-
worker and managerial productivity, and freeing up more resources as a result of
coordination among individuals (Podsakoff & MacKenzie, 1997). Researchers
(Demerouti, Xanthopoulou, Tsaousis, & Bakker, 2014) argue that task performance
and contextual performance are considered as important performance dimensions
which are relevant for every kind of job. Moreover, behaviors aimed at facilitating
others in context of non-routine jobs become even more important. Additionally, task
performance and contextual performance have been identified as two distinct
57
dimensions of work behaviors that contribute independently to organizational
effectiveness (Griffin et al., 2000).
2.3.2 Turnover Intentions
Employee retention is one of the greatest challenges for organizations due to
ever increasing worth of knowledge workers (Lumley, Coetzee, Tladinyane, &
Ferreira, 2011) and has significant implications for human resource management.
Turnover intention refers to the subjective evaluation of an individual regarding the
possibility that he/she may leave the organization he/she works for in the near future
(Mobley, 1982a, 1982b; Carmeli & Weisberg ; 2006). It is important to study turnover
intention since it serves as forecasting tool for controlling negative factors associated
with individuals and their organizations (Kim & Park, 2014) and is said to be the
‗strongest cognitive predecessor of (actual) turnover with the great explanatory power
(Griffethet al., 2000) and last part of sequence in the withdrawal cognition process
(Mobley et al., 1982b). Moreover, it is valuable to study turnover intentions as ―it is
under more individual control than actual turnover which is more difficult to predict
than intentions since there are many external factors that affect turnover behavior‖
(Shore, 1989).
An employee with high turnover intentions is more prone to actual turnover
and even it does not translate into real action, it leads to low productivity, low
motivation and loss of efficiency for the assigned work, which in turn decreases
overall organizational effectiveness (Mobley, 1982). For instance, employees with
high turnover intentions are more likely to show indifferent attitude towards their
work (Biron and Boon, 2013). Turnover can lead to many setbacks for organizations
in case the ―individual who leaves the organization is a good performer or the
organization invested heavily in training the person‖ (Griffin &Moorhead,2011, p.
20). Meta-analysis by Steel and Ovalle (1984) showed a strong positive relationship
between intent to leave and actual turnover. Metal-analysis by Harrison, Newman and
Roth (2006) also provided an empirical support to the theoretical expectation that
turnover intentions reliably predict job behaviors such as turnover and it is expected
that intent to leave actually translates into employees‘ exit.
Mobley (1977) devised a withdrawal decision process to explain how people
decide to leave their organizations. According to his model, people first evaluate their
58
present jobs on the basis of their level of satisfaction or dissatisfaction with their jobs.
If they feel dissatisfied, they are more inclined to quit the job. Before going for the
alternatives, they compare the cost of leaving the present job with the utility that is
expected to accrue from the search. In case the utility is worth it, the search for
alternatives begin which are evaluated and compared with the prevailing conditions. If
the alternatives are deemed more attractive, intention to quit is formed which is
followed by actual turnover, hence turnover intentions has been considered a critical
factor in an individual‘s work-withdrawal process. The process chain suggested by
Mobley was later reaffirmed by Carmeli and Weisberg (2006). They also outlined
three elements in the withdrawal cognition process – thoughts of leaving, the intention
to search for alternative opportunities and intention to quit.
Turnover of employees threatens the overall functionality of the organization,
therefore, efforts must be made to eliminate or at least reduce the phenomenon so that
organizations may not lose their valuable human capital (Carmeli & Weisberg; 2006).
When employees leave their organizations, the loss is irreversible as it may result in
increasing recruitment and training cost, low employee morale and low job
satisfaction, collectively increasing inefficiencies in organizations (Cho, Johanson, &
Guchait, 2009). It may result in loss of intellectual capital since employees who leave
also take with them valuable knowledge (Korsakienė, Stankevičienė, Šimelytė, and
Talačkienė, 2015). Employees also have to pay the cost such as relocation cost,
financial stress and loss of social ties (Hom & Griffeth, 1995).
Research to-date has focused more on voluntary turnover as it is a critical
issue for employees as well as their organizations (Ghazali, 2010). According to Kim
and Park (2014) turnover of employees results in increase of cost in terms of
replacement/recruitment and training, decrease in productivity due to outflow of
skilled labor and structural damage to communication and trust among organizational
members. Korsakiene, Stankeviciene, Simelyte, and Talackiene (2015) argue that
turnover not only increases incompetence in organization but also relationship losses
among individuals. Furthermore, the employees who are about to leave the job stop
working as hard as before which may in turn affect their coworkers since they have to
burden the workload to compensate for the individual who is leaving.
Biron and Boon (2013) state that causes of turnover are still poorly understood
owing to different and complex factors associated with the phenomenon. Therefore,
more focused attention is warranted to identify on factors that may affect turnover
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intentions and actual turnover. Moreover, an understanding of the correlates of
turnover intention would be valuable and informative not only to organizational
theorists but also to practicing managers. Turnover has become one of most pressing
issues facing telecom sector of Pakistan, due to high job opportunity, ease of job
switching and huge demands of skilled professionals (Hussain & Asif, 2012). In the
current study, we include turnover intentions, or an individual‘s desire to leave an
organization, rather than actual turnover because once employees have left an
organization, it is difficult to track down the factors which accounted for that act.
Moreover, it serves as a symptom of the more serious issue. Organizations can treat
the underlying causes of these symptoms by taking into account the level of these
indicators.
2.4 Workplace Subjective Well-being
Well-being is a broad concept which has its ramifications in every field of life.
The phenomenon has plethora of definitions. Behavioral researchers, sociologist,
economists and psychologists have come up with different definitions relevant to their
own particular field. Warr (1987) defines it as the overall quality of an employee‘s
experience and functioning at work. DeDrue et al., (2004) define workplace well-
being as an individual‘s evaluation of his or her work environment. It refers to the
experience of meaning, behavior, social relationships and the individual‘s
interconnectedness with the environment (Kirsten et al., 2009). Researchers have put
forward different dimensions of employees‘ well-being. McAllister, F. (2005)
discusses in his report on well-being that there are two basic dimensions of well-
being, objective well-being and subjective well-being. Objective well-being is related
to broader perspective of well-being in a society, whereas subjective well-being is
related to the well-being of individuals.
In work settings, well-being has been measured in terms of job satisfaction
(Rothman, 2008), work engagement (Bakker and Leiter, 2010; Schaufeli and
Salanova, 2007), positive affect (Warr, 1990), and flow (Bakker, 2008). However,
impaired well-being has been measured in terms of negative affect and burnout. The
existence of multiple indicators of workplace subjective well-being is appropriate
owing to its prevalence in every sphere of life. Moreover, limiting well-being to only
one indicator could provide a myopic view of work-related well-being since it is a
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multi-dimensional concept. What seems to be lacking in conflict research is that how
conflict types affect different indicators of well-being and whether these indicators of
well-being help transmit the effect of conflict types. Given that well-being is indicated
as the most important factor, beyond material success (Diener, 2000), and because of
its associations with valued individual outcomes, it is imperative to understand its
antecedents.
In line to the study‘s theoretical model, we focus on three indicators of
workplace subjective well-being; work engagement, job satisfaction and job burnout-
which are key variables in occupational and organizational research on employee
health and well-being (Cropanzano and Wright, 2001). Bakker and Oerlemans (2011)
and Rothman (2008) have also identified them as dimensions of workplace subjective
well-being. By including these indicators, this study brings together recent research
that shows that these constructs add unique valuable information about the
individual‘s well-being at work (Rothman, 2008).
The following section will discuss afore-mentioned forms of workplace
subjective well-being. For the sake of brevity, the terms workplace subjective well-
being and well-being will be used interchangeably:-
2.4.1 Work Engagement
The concept of work engagement gained its popularity from growing
awareness of the worth of human capital and corresponding interest in positive
psychology since the dawn of this century (Schaufeli, 2013; Schaufeli & Salanova,
2014). It was primarily used in business settings by human-resources professionals
and consultants due to economic importance of the cognitive and emotional abilities
of its employees which is considered the source of competitive edge (Schaufeli &
Salanova, 2014). The concept became so popular that from 2001 to 2012, there were
1,100 scientific publications on the topic (Schaufeli & Salanova, 2014). Schaufeli
(2013) termed these changes towards the development of this phenomenon as a
―psychologization of the workplace.‖ This is due to the fact that employees‘ mental
health and cognitive abilities provide a competitive edge to their organizations
(Schaufeli & Salanova, 2014)
Kahn‘s (1990) presented a model of personal engagement that referred to
being immersed personally and engaged physically, cognitively and emotionally.
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According to this model, a dynamic analogy exists between an individual and his
work role that shapes how that person inhabits that role (Bakker, Demerouti, & Sanz-
Vergel, 2014). Kahn (1990) suggests that people need self-expression and self-
employment in their work lives.
Research on engagement progressed in yet another direction which stressed
that engagement is exactly antithesis of burnout (Maslach, Schaufeli, & Leiter, 2001).
Maslach et al., (2001) adopted the practitioner terminology and defined engagement
as ―a persistent, positive affective-motivational state of fulfillment in employees
characterized by high levels of activation and pleasure‖. They argued that engagement
and burnout are opposite ends of a continuum and individuals tread back and forth on
this spectrum daily. However, Schaufeli, Salanova, González-Romá, and Bakker,
(2002a) argued that engagement is an independent and distinct concept that is
negatively related to burnout.
Work engagement as defined by Schaufeli et al., (2002a) is ―a positive,
fulfilling, work-related state of mind that is characterized by a physical component (1)
vigor (i.e. state of being energetic and mentally resilient and persevere even in
difficult times); an emotional component (2) dedication (i.e. a sense of significance,
inspiration, pride and challenge); and a cognitive component (3) absorption (being
fully and happily engrossed in one‘s work).‖Schaufeli et al., (2002) developed this
definition within an organizational behavior context following the theoretical
foundation of the concept of engagement presented by Kahn (1990).
Saks (2006) mentioned that ―engagement is a distinct and unique construct
that comprises of cognitive, emotional, and behavioral components which are
associated with individual role performance.‖ He further argued that work
engagement is an individual-level construct, and individuals must first experience
individual-level outcomes in order for organizations to gain favorable results. It
entails the relationship of an employee with his or her work (Schaufeli, 2013) where
the individual brings his/her entire self into work role employing emotions, behaviors
and cognitions (Saks, 2006). Work engagement has also been termed as harmonious
passion, a passion in which the individual controls the activity, albeit the activity
carries a significant value but not overpowering place in his/her life (Valerian, 2008).
Schaufeli, Salanova, Gonzalez-Roma, and Bakker (2001) argue that engagement is a
―persistent and pervasive affective-cognitive state that is not focused on any particular
object, event, individual or behavior‖ (p. 74).
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Work engagement has been said to be positively related to important
individual outcomes such as commitment (Schaufeli et al, 2008), personal initiative
(Sonnentag, 2003), involvement, productivity and job performance since engaged
employees enjoy their work and take it as a fun whereby time passes quickly because
they like their work (Schaufeli & Bakker, 2004 ;Schaufeli, 2013; Bakker, Demerouti,
& Sanz-Vergel, 2014). Engaged employees are intrinsically motivated (Schaufeli,
2012). Researchers (Bakker et al., 2014) argue that ―work engagement is a desirable
state with positive consequences.‖Particularly, with respect to job performance, work
engagement has been documented to be related positively to in-role performance
(Halbeleben & Wheeler, 2008) as well as extra-role performance (Bakker &
Demerouti, 2008; Xanthopoulou, Bakker, Heuven, Demerouti, & Schaufeli, 2008).
Engaged employees are satisfied with their jobs and more committed to their
organizations because they value their work and usually do not intend to leave their
jobs. (Schaufeli & Bakker, 2004). They experience job resources as well as job
demands and work conditions that give rise to creativity and learning. They love to
work in challenging work environment. They enjoy their work and this fun element
motivates them to go beyond their prescribed duties and they perform work activities
that are beneficial for their organizations. Hence, this indicates that engagement may
contribute towards contextual performance. These factors lead to their better
performance (Van Beek et al., 2014). Gorgievski and Bakker (2010) term work
engagement as ‗harmonious passion‘. According to these researchers, engaged
employees take pride in performing their jobs, enjoy their activities and have control
over events that affect their lives. The positivity inherent in work engagement makes
them more outgoing, cooperative, self-assured and optimistic. Christian, Garza, &
Slaughter (2011) conducted a meta-analysis which showed that work engagement was
positively related to job performance.
Work engagement has beneficial effects on organization as well. It results in
retention of valued employees due to emotional attachment of employees to their
organizations, more positive corporate image, and a sustainable competitive and
effective organization (Schaufeli & Salanova, 2007).
In conflict research, researchers (Tjosvold, 2008; Amason 1996; Jehn, 1995)
are of the view that task conflict in individuals leads to creativity and better decision
making. When employees engage in task conflict, they exchange ideas and
information, which in turn contribute positively towards their performance in a way
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that they become more clear about what to do and how to do it. Kahn (1990) opined in
his research paper on engagement that people need self-expression so when they
express their views, this may lead to their work engagement. The antecedents of work
engagement include job resources such as job control, social support, task variety,
performance feedback and challenging demands such as workload, time urgency,
mental demands and responsibility. Outcomes are organizational commitment,
personal initiative, low turnover intention, low sickness absence, and job/task
performance etc. (Schaufeli & Salanova, 2014).
Chen, Zhang, and Vogel, (2011) investigated the impact of task and
relationship conflict on work engagement and knowledge sharing behavior through
three psychological states (experienced meaningfulness, experienced safety,
experienced availability). The researchers found that task conflict had a positive
relationship with work engagement and knowledge sharing behavior through its
positive impact on two psychological states (experienced safety and experienced
availability). Relationship conflict had a negative relationship with work engagement
and knowledge sharing through its negative impact on all three psychological states.
Task conflict may have a positive impact on job performance through its
positive effect on work engagement since researchers (Gorgievski & Bakker, 2010)
argue that engaged employees create positive organizational outcomes, both at
individual level as well as team level (Schaufeli, 2012, 2013). Work engagement has
been said to be positively related to (task & contextual) job performance since
employees experience positive emotions and fun element of their jobs, which lead to
better performance (Gorgievski & Bakker, 2010; Schaufeli, 2012). Similar views have
been expressed by Gruman and Saks (2011) that engaged employees are energetically
and psychologically connected to their work and they are capable and willing ―to go
the extra mile‖ (Schaufeli, 2012). They put all their energies into their work, hence
perform better (Innanen, Tolvanen, & Salmela-Aro, 2014). In a similar vein, Schaufeli
and Salanova (2014) contend that work engagement may also contribute towards
improving extra-role performance since being engaged means being capable of doing
beyond the prescribed formal duties.
Engaged employees are capable and willing to invest in their work with their
mind and soul (Schaufeli, 2013). According to the COR theory, the resources have
intrinsic motivational power, thereby creating more resource gain (Hobfoll, 2001).
Resources mobilize employees, sustain their resilience, and make them more
64
concerted in their efforts which means that resources foster work engagement which
in turn leads to positive outcomes such as job performance (Schaufeli, 2013). In fact,
Schaufeli and Bakker (2010) proposed a model in their study that considered work
engagement as a mediator between job resources, personal resources and
organizational outcomes. Based on this tenet of the COR theory, ―work engagement
mediates the relationship between job and personal resources on the one hand and
positive outcomes on the other hand, thus generating a motivational process
(Schaufeli, 2013)‖. In the present study, based on our conceptualization of task
conflict as a resource, work engagement is expected to mediate the relationship
between task conflict and task performance, contextual performance and turnover
intentions.
2.4.2 Job Satisfaction
Job satisfaction has been a central point for several theories explicating
individual attitudes and behaviors. Moreover, research related to job satisfaction has
practical implications for the improvement of individual lives as well as
organizational effectiveness (Judge & Klinger, 2008; Ikyanyon & Ucho, 2013).
Therefore, it is considered as an important indicator of employee well-being and is
related to key organizational outcomes such as performance, turnover, absenteeism,
and organizational citizenship behavior (Boz, Martinez, and Munduate, 2009). Owing
to these implications, the concept shares its importance equally in the organizational
sciences as well as in the subjective well-being research (Judge & Klinger, 2008).
There are several definitions of job satisfaction in the scholarly literature,
however, the definition by Locke (1976, p. 1304) has been considered classical who
defined job satisfaction as ―a pleasurable or positive emotional state resulting from the
appraisal of one‘s job or job experiences, satisfaction with the task involved and
feelings of accomplishment from doing that job‖ (Ikyanyon & Ucho, 2013; Judge et
al., 2001). This definition entails the significance of both affect (feeling) and
cognition (thinking), and both processes are intertwined closely (Saari & Judge,
2004). Job satisfaction has also been defined as ―one‘s emotional attachment with
his/her job (Tett & Meyer, 1993). Bakker and Oerlemans (2011) have considered job
satisfaction as one of the positive forms of workplace subjective well-being as it
65
relates to improvement of individual lives, we need to look into the effect of task
conflict on job satisfaction from the well-being perspective.‖
Schneider and Snyder (1975) describe job satisfaction ―as an individual‘s
personal assessment of conditions prevalent in the job. This evaluation is based on the
factors important for them.‖ These aspects may include high pay package, congenial
working relationships, supportive working environment and several other factors
which may be based upon subjective evaluation of that particular factor and the
importance it carries for that person. In other words, job satisfaction deals with how
employees feel about their jobs and its related aspects (Spector, 1997). An employee‘s
well-being can be affected by how he/she feels about the job. Smith, Kendall, and
Hulin (1969) argued that striving for ways to make employees‘ jobs more satisfying
was of humanitarian value, and job satisfaction per se is a legitimate goal. According
to Robbins (1996) mentally challenging work is one of the primary factors that lead to
increased job satisfaction. It is expected that in context of technical jobs, task conflict,
may lead to job satisfaction since it may serve as a platform to voice different
concerns of employees about tasks that may provide alternative ways of doing work.
Research on job satisfaction has generally followed two approaches (Spector,
1997). The first approach examines job satisfaction from a global perspective,
concerned with overall satisfaction with the job, whereas the other approach gauges
job satisfaction with respect to the different facets of the job such as inner rewards,
coworkers, and compensation etc. However, keeping in view the nature of the
constructs of present study, global perspective has been considered more relevant
since Vandenabeele (2013) suggests that the facet-specific view makes the
differentiation between the determinants of job satisfaction and the concept per se
more cumbersome.
Job satisfaction is a concept that has covered enormous space in literature with
unclear boundaries (Yang, 2010). This growing interest is based on three perspectives
on this domain. The first perspective considers job satisfaction as antecedent of
organizational outcomes such as business performance (Schyns & Croon, 2006),
employee turnover (Griffeth et al., 2000; Silva, 2006), and organizational
commitment (Taris et al., 2005; Li, 2006). The second perspective views job
satisfaction as an outcome of organizational conditions such as leadership, social
support, and task characteristics (Schyns & Croon, 2006). The third gauges job
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satisfaction in terms of temperament of individuals, which is largely affected by
individual traits (Judge & Bono, 2001).
Spector (1997) underscored three important features of job satisfaction. First,
organizations should be guided by human values because such organizations tend to
treat workers fairly and considerately. In that case the assessment of job satisfaction
would serve as a good indicator of employee effectiveness such as their performance.
Second, the behavior of employees resulting from the level of job satisfaction of
employees will affect the functioning of organization which implies that job
satisfaction may result in positive behavior. Third, job satisfaction may serve as
indicator of organizational activities which is related to turnover, absenteeism,
organizational citizenship behavior, and job performance. These aspects of job
satisfaction make it an important construct that warrants further investigation.
Antecedents of job satisfaction can be demarcated into two main categories
(Spector 1997). The job environment and the factors associated with job are two
major determinants of job satisfaction. Evidence shows that mentally challenging jobs
lead to job satisfaction (Huang & Van De Vliert, 2004). Researchers (Saari & Judge,
2004) argue that job satisfaction is significantly influenced by the nature of work
itself. This does not imply that other factors are irrelevant, rather, several measures
can be ensured in order to make job more interesting and challenging. Saari and Judge
(2004) further contend that among the factors relevant to the nature of work per se-
job challenge, autonomy, variety and scope are the best predictors of the overall job
satisfaction. This stream of research support our assumption in the present study that
task conflict in non-routine jobs may lead to positive psychological states.
De Drue and Weingart (2003) argued in their meta-analysis that both task
conflict and relationship lead to decrease in job satisfaction among team members.
However, recently Todorova, Bear, & Weingart (2014) explored the impact of task
conflict on positive emotions and job satisfaction at individual level. The researchers
concluded that moderate level of task conflict generates knowledge exchange but
intense task conflict obstructs the knowledge sharing. Knowledge acquisition as a
result of moderate task conflict results in positive emotions which in turn lead to job
satisfaction.
Based on the findings of the Todorova et al., (2014) study, it can be assumed
that when employees debate about their tasks, its modus operandi, they feel more
freedom about their work, hence this may induce a feeling of satisfaction and
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contentment. Employees who engage in task conflict are more aware of their jobs,
how to do them and when to do them, so they feel more satisfied the way they do it.
Evidence shows that satisfied employees tend to be more productive, creative and
committed towards their organizations (Syptak, Marsland, and Ulmer, 1999).
Satisfaction at workplace is valuable to study owing to multiple reasons; job
satisfaction is positively related to firm‘s value (Edmans, 2012), increased
organizational citizenship behavior (Organ & Ryan, 1995), and decreased withdrawal
and work deviant behaviors (Dalal, 2005; Morrison, 2008). The relationship between
job satisfaction and job performance has been a main theme in
industrial/organizational psychology (Judge, Thoresen, Bono, & Patton, 2001). Landy
(1989) termed this relationship as the ―Holy Grail‖ of organizational behavior.
However, this research has been inconclusive and controversial as meta-analysis by
Iaffaldano and Muchinsky (1985) reported a very low value (r = .17) as the best
estimate of the correlation between satisfaction and performance. Later on Judge et
al., (2001) challenged the results of meta-analysis conducted by Iaffaldano and
Muchinsky (1985) as the reported correlation in their study was the average of the
correlation between different facets of job satisfaction and job performance. However,
the results of Iaffaldano and Muchinsky (1985) were so influential that they continued
to haunt management thinking for rest of the millennium (Edmans, 2012).
Judge et al., (2001) suggested that ―facet satisfaction correlation will always
be lower than overall satisfaction correlation, as aggregating those facets decreases
the effect size‖. Hence, the method used to get the information from facet measures
could not be considered an accurate estimate of the relationship between overall job
satisfaction and job performance. However, their meta-analysis of 301 studies came
up with the mean correlation value of 0.30 between overall job satisfaction and job
performance which was considered modest. Further, it was revealed that the
relationship between job satisfaction and job performance was stronger in complex
(professional) jobs than for less complex routine jobs. Later in 2006, Harrison et al.,
found job satisfaction to be positively related to task performance, and contextual
performance and negatively related to turnover intentions. Relevant to theorizing of
the present study, Saari and Judge (2004) reported that association between job
satisfaction and job performance is stronger for complex professional jobs as
compared to routine jobs. This finding supports our assumption that task conflict in
non-routine jobs may lead to job satisfaction.
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Research reveals that dissatisfied employees are more inclined to leave their
jobs than their satisfied counterparts (Saari & Judge, 2004). Job satisfaction was
found to be negatively related to turnover intentions (Muchinsky & Tuttle, 1979).
Yang (2010) also found a negative relationship between job satisfaction and turnover
intentions. Allen, Bryant, and Vardaman‘s (2010) study showed negative relationship
between job satisfaction and turnover, thus indicating retention benefits of satisfaction
at workplace. Medina (2012) found a strong negative relationship between job
satisfaction and turnover intentions mediated by satisfaction in workplace culture.
Westlund and Hannon (2008) found a positive relationship between satisfaction with
the nature of work and employee‘s intention to stay with their organization.
2.5 Burnout
Burnout research progressed along two lines: ―an interventionist approach
introduced by a clinician Freudenberger that focused on assessment, prevention and
treatment of burnout, and an academic research approach introduced by Christina
Maslach that emphasized on finding its antecedents and consequences from a
scientific point of view‖ (Schaufeli & Buunk, 2003; Schaufeli & Salanova, 2014).
The concept became so popular that around 6,600 articles have been published so far
as reported by Schaufeli and Salanova (2014).
The concept of burnout was introduced by Freudenberger (1974) who was a
psychiatrist working on the rehabilitation of the drug addicts in New York (Bakker,
Demerouti, & Sanz-Vergel, 2014). He started observing exhaustion in volunteers after
he worked with them almost a year or so. He defined burnout as a psychological
condition including exhaustion (depletion of one‘s mental resources), physical
symptoms (headaches, stomach aches, insomnia etc.,), frustration, drug use, and
depression among other factors (Freudenberger, 1980). However, measurement of this
model was quite complicated, but his studies provided a fundamental
conceptualization of burnout. Around the same time, Christina Maslach (1976) used
the term while working with health care workers in California. On the basis of their
observations, Maslach and Jackson (1981) defined burnout as ―a state of mental
fatigue that refers to a drain of mental/emotional resources caused by chronic job
stress and is a work-related indicator of psychological health‖ (Schaufeli & Enzmann,
1998).
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Burnout was originally considered to be common in employees performing
people‘s jobs (Maslach, 1981) because in these professions, employees are supposed
to serve other people and soon they find themselves mentally drained and stressed out
due to demanding nature of these jobs. Maslach, Schaufeli, and Leiter (2001) termed
this process as the erosion of psychological resources of individuals as a result of
prolonged stress at work. Later on, in the 1990s, the concept was broadened and
redefined ―as a general crisis in the relationship with one‘s own work rather than a
crisis in one‘s relationship with people at work‖ in order to extend the phenomenon
across different professions other than service context (Schaufeli, Leiter, Maslach, &
Jackson, 1996; Schaufeli & Taris, 2005; Borgogini et al. 2012; Schaufeli & Salanova,
2014). Cherniss (1980) terms burnout as a socio-psychological state of withdrawal
from work or decreased motivation. Maslach (1982) identified certain conditions that
could lead to burnout and one of these conditions was negative peer relations.
Maslach and Jackson (1981) initially developed the Maslach Burnout
Inventory (MBI) to assess burnout among people in social service jobs. Later, they
expanded the measure to include other fields as burnout was observed in professions
other than service careers. It is a chronic state and burnout scores through MBI
(Maslach Burnout Inventory) are stable across time (Schaufeli & Buunk, 2003).
More specifically burnout was defined as a multi-dimensional stress syndrome
consisting of three basic dimensions which are: - 1) exhaustion (i.e., depletion of
mental resources), (2) cynicism or depersonalization (indifferent attitude towards
one‘s job or in other words distancing oneself from his/her work (Bakker, Demerouti,
& Sanz-Vergel, 2014) or towards people; and (3) and lack of professional efficacy or
reduced personal accomplishment (i.e., tends to underestimate one‘s job performance)
(Maslach, 1993). On a more generic note, Gorgievski and Hobfoll, (2008) term
burnout as ―the end state of a long term process of resource loss that gradually
develops over time depleting energetic resources‖. Later on, Schaufeli et al., (2009)
argued that the third dimension is not part of the burnout construct and by excluding
this dimension, there is possibly no loss of information. The claim was further
augmented by Hakanen and Schaufeli (2012) who cited Lee and Ashforth (1996) and
Kalliath (2000) that as compared to other two dimensions, reduced professional
efficacy plays a divergent role.
Borgogni, Consiglio, Alessandri, and Schaufeli, (2012) argue that during the
extension of burnout phenomenon to other job contexts, depersonalization, the second
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component of burnout, had been replaced by ―a more general and nonsocial
dimension, called cynicism.‖ In doing so, the interpersonal feature was lost. In order
to fill the void and keep intact the social essence of burnout, they introduced the third
dimension as interpersonal strain at work; a psychological distress resulting from
interpersonal interactions. The researchers recommended integrating interpersonal
strain which results from deterioration of social networks at work, with other two core
burnout dimensions; exhaustion (chronic energy depletion) and cynicism
(disengagement from one‘s work). Hence in the present study, the construct of
burnout will be measured with the afore-mentioned dimensions.
Antecedents of burnout are ‗high quantitative (excessive work, urgency, long
working hours and jobs involving frequent contact with clients or customers) and
qualitative job demands (discrepant work roles, insufficient information to perform
tasks, emotionally demanding events, work family conflicts) as well as poor job
resources(Schaufeli & Salanova, 2014). However, job demands are more strongly
related to burnout than lack of resources (Bakker, Demerouti, & Sanz-Vergel, 2014).
Maslach (2003) state that exhaustion and cynicism are likely to emerge from work
overload and social conflict. In afore-said study Maslach analyzed the three-
dimensional model comprising of exhaustion, cynicism and inefficacy. Schaufeli and
Salanova (2014) contend that burnout is more likely to occur when individuals
experience lack of interpersonal resources (social support from peers and supervisors)
that is crucial in accomplishing one‘s job responsibilities. Lack of social support from
supervisors as well as from co-workers is one of the antecedents of burnout. In a
similar vein, interpersonal conflict with peers and superiors are one of the work
stressors that cause burnout (Schaufeli & Buunk, 2003).
Burnout has negative repercussions for the individuals as well as for their
organizations and is considered as a serious burden for working class (Bianchi,
Schonfeld, & Laurent, 2015). Consequences of burnout at individual level include
negative impact on individual‘s mental as well as physical health, debilitating
performance (Taris, 2006b), low morale, sickness absence, and job
turnover‘(Freudenberger, 1974; Schaufeli & Bakker, 2004; Schaufeli & Salanova,
2014). Burnt-out employees are more likely to neglect important aspects of their jobs
(Freudenberger, 1974). Singh et al., (1994) argue that burnout entangles employees in
a vicious spiral, in which the employees cease to put in more effort in their work, and
continue to perform ineffectively. They are less satisfied with their jobs, perform
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poorer than their counterparts, and indulge more frequently in planning to leave their
organization (Maslach, Schaufeli, & Leiter, 2001). Furthermore, burnt-out person
becomes intolerant, irritable, oversensitive, skeptical, and behaves rudely towards
peers and supervisors (Freudenberger, 1980). Schaufeli and Buunk (2003) contend
that ―burnt-out individuals feel helpless, hopeless and powerless‖. Work becomes
worthless having lost its meaning and cognitive abilities such as memory and focus
might be impaired and thinking becomes inflexible, mechanized and detached.
Burned out employees may disrupt the normal functioning of their colleagues
as the phenomenon is contagious and may demotivate the coworkers as well
(Rakovec-Felser, 2011). Negative consequences for organizations include mental
withdrawal (poor commitment and attachment) or physical withdrawal that
encompasses intention to quit, impaired performance, lower productivity and
efficiency, poor quality of service (Schaufeli & Buunk, 2003), turnover (Kim &
Stoner, 2008) and sickness absence (Schaufeli & Salanova, 2014). Employees are no
more concerned for their organizations and become overcritical of the management,
co-workers and superiors (Schaufeli & Buunk, 2003; Schaufeli & Enzmann, 1998)
which relates more specifically to low contextual performance and increased turnover
intentions (Bakker, Demerouti, & Verbeke, 2004). In fact, Bakker et al., found job
burnout to be negatively related to in-role and extra-role performance. The present
study will measure burnout with exhaustion, cynicism and interpersonal strain at
work.
2.5.1 Exhaustion
Exhaustion is considered a core component of burnout (Hakanen & Schaufeli,
2012; Schaufeli & Taris, 2005). It refers to depletion of one‘s emotional, cognitive
and physical resources thus exhausting energy back-up of individuals (Bakker et al.,
2004; Maslach, Schaufeli, & Leiter, 2001). When individuals face high stressors they
may undergo exhaustion since researchers (Sonnentag, Arbeus, Mahn, & Fritz, 2014)
contend that exhausted employees believe that their energetic resources are not
sufficient to meet their job demands. Exhausted employees feel cognitive fatigue and
have problems related to perception, memory retention and failure to perform task at
hand and it has been linked with poor job performance (Sonnentag et al., 2014).
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Singh, Goolsby, and Rhoads (1994) explicate the relationship of burnout and
job performance. They state that exhaustion depletes the available energy of
employees and they cease to put in more effort into their work. Furthermore, burnout
entangles employees in a detrimental, vicious spiral in which they do not seek social
support or strive for improvement in their work conditions, hence, they continue to
perform ineffectively.
Bakker and Heuven (2006) explored the relationship of exhaustion and
cynicism with in-role performance. Both exhaustion and cynicism were found to be
negatively related to in-role performance. Bakker, Demerouti, and Verbeke, (2004)
studied burnout and job performance in a sample of employees from a variety of
sectors and positions, and found that emotional exhaustion was significantly
negatively related to in-role and extra-role performance. Demerouti et al., (2014)
found a negative relationship between exhaustion and task performance.
2.5.2 Cynicism
Another core dimension of burnout is cynicism (Schaufeli & Taris, 2005)
which refers to ―an indifferent or distant attitude toward work (Schaufeli and
Salanova, 2014). To put it more concisely; exhaustion refers to inability to expend
effort and cynicism refers to unwillingness to expend effort since work has lost it
meaning (Schaufeli & Salanova, 2014). Cynicism is characterized by de-motivation,
unconcern and withdrawal from the work‖ (Bianchi, Schonfeld, & Laurent, 2015).
According to Bakker, Demerouti and Verbeke (2004), cynicism ―represents an
extensive and intensive reaction in terms of an emotional, cognitive, and behavioral
abandonment of the work‖. It also implies that an employee is no longer interested to
perform duties owing to low level of tolerance (Mostert & Joubert, 2005).
Taris, Schreurs, and Van-Silfhout (2001) found that stress stemming from
relationship tensions among coworkers was associated with psychological withdrawal
such as cynicism, loss of commitment and turnover. Researchers (Amason, 1996;
Jehn 1995) are of the view that people who experience relationship conflict show
symptoms of cynicism, withdraw themselves physically or psychologically from
workplace and undermine the effort of others (Van der Kam et al., 2014). In doing so,
their work performance further plummets (Schaufeli & Salanova, 2014).
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2.5.3 Interpersonal Strain at Work
Interpersonal strain refers to ―a specific disengagement reaction from all
relevant interpersonal relationships at work‖ (Consiglio, 2014). Individuals tend to
isolate themselves from others and develop an impersonal attitude, thus dehumanizing
the relationships with people around them. Fernet, Gagné, and Austin (2010) stress
upon the need of high quality relationships in organizations to decrease the effect of
burnout. However, social isolation, loose and non-supportive social fabric (Schaufeli
& Buunk, 2003), poor or deteriorating workplace relationships or ‗lack of community
(refers to breakdown in relationships with other people at someone‘s immediate
workplace‘) are also one of the antecedents of burnout and they have been found to be
related to negative organizational outcomes such as absenteeism, turnover and low
self-esteem (Rakovec-Felser, 2011). Fernet et al., (2010) argued in their study that
high quality interpersonal relationships are crucial in organizational setup to mitigate
the effects of burnout. Rakovec-Felser (2011) argues that when employees do not
experience reciprocity in their relationship at interpersonal level, they may undergo
the three dimensions of burnout owing to the fact that energy depleting demands of
relationship conflict may increase an employee‘s vulnerability to psychological stress
(Bouckenooghe et al., 2014).
Schaufeli and Salanova (2014) state that burnout is more likely to occur when
the employees face lack of interpersonal resources i.e., the needed support from peers
and supervisors. Particularly, the symptoms of burnout are embedded in the context of
interpersonal relationships at work. When there is strain in relationships at workplace
which is marked with indifferent, harsh and reserved behavior towards other people,
this leads to burnout (Borgogni et al., 2012). Consequences of burnout include
turnover intentions, poor performance and sickness absence.
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2.6 Summary
This chapter provided a detailed review of relevant literature on key constructs
of this study as per following details:-
Table: 2.1: Summary of Chapter
Section Details
1 It included the overview of overarching theory i.e., Conservation of
Resources (COR) theory, its basic tenets and related corollaries.
2
The chapter further elaborated on key study constructs i.e., task conflict,
relationship conflict, outcome variables (task/contextual performance,
turnover intentions) and mediators (work engagement, job satisfaction,
and job burnout.
3
The review included the definition and conceptualization of these
constructs, their theoretical background, the chronological account of
relevant research in their respective areas and their relevance to the
present study.
75
Chapter 3
Theoretical Framework
76
Theoretical Framework
The second chapter delineates the interrelationships among the study
constructs on the basis of the Conservation of Resources (COR) theory. This chapter
provides an overview of direct relationships, indirect relationships (the two different
underlying mechanisms through which task/relationship conflict affect work
behaviors, and discusses the tenets of the COR theory that help explain the direct as
well as indirect relationships. It concludes with the theoretical framework.
3.1 Task Conflict and Task/Contextual Performance
Research has shown inconsistent results of task conflict with job performance
of employees. Studies have shown a positive relationship (Amason & Schweiger,
1997; Jehn, 1995, 1997; Jehn, Northcraft, & Neale, 1999; Lu et al., 2011), negative
relationship (De Dreu & Weingart, 2003; Jehn et al., 2008; Langfred, 2007), and no
significant relationship (De Wit et al., 2012; Pelled, Eisenhardt, & Xin, 1999). Jehn
(1995) argues that task conflict has positive relationship with job performance of
employees in non-routine jobs since these jobs are complex and they require idea
sharing and knowledge exchange among individuals. In case of routine jobs, the
relationship between task conflict and job performance was found to be negative.
Researchers (Amason, 1996; Olson et al., 2007) found a positive relationship
between task conflict and job performance of employees. Weingart and De Drue
(2003) found in their meta-analysis of 30 studies that both task conflict and
relationship conflict are negatively related to job performance of employees. It should
be noted that De Drue and Weingart (2003) used a rather strict criteria for effect size,
in which they selected only objective team performance measures or manager‘s
ratings of performance, hence they ended up with negative conclusions about the
relationship. Later De Dreu (2006) challenged his meta-analysis results and argued
that task conflict does have positive results because differences arising over task
related issues can enhance cognitive processing of these issues thus increasing
satisfaction with decisions and final outcomes (Lau & Cobb, 2010). De Wit et al.,
(2012) also conducted a meta-analysis of 116 studies, but unlike findings reported by
De Drue and Weingart (2003), De Wit et al., did not find a strong and negative
relationship between task conflict and group performance. Task conflict was found to
77
be positively related to group performance in studies conducted in top management
teams, in studies where association between task conflict and relationship conflict was
rather weak. The major problem with meta-analyses is that these can only draw
inferences at the study level, not at the group or individual level, and likewise meta-
analyses could not test the hypothesis directly, nor the underlying processes that link
the direct relationships (De Wit, Jehn, and Scheepers, 2013), hence an individual level
approach was considered more appropriate.
Few individual level studies were also conducted. Lu, Zhou, and Leung (2011)
studied the impact of task and relationship conflict on innovative behaviors,
organizational citizenship behavior and knowledge-sharing behaviors. Task conflict
was found to be positively related to both innovative behaviors and knowledge
sharing behaviors. Choi (2010) investigated the antecedents and consequences of
interpersonal conflict and its effects on job performance (Contextual performance and
work deviant behavior). Relationship conflict had a negative effect on job
performance whereas task conflict had no negative impact on organization related
outcomes and a weak negative relationship with individual outcomes.
Mannes (2009) explored the relationship of latent task conflict, perceived task
conflict and relationship conflict against team performance and satisfaction. The
researcher concluded that latent task conflict increases team‘s performance whereas
perceived task conflict coupled with relationship conflict had negative effect on
satisfaction, but by controlling relationship conflict, perceived task conflict had no
effect on teams‘ satisfaction. These studies call for a need to investigate and challenge
the previous findings that task conflict contribute towards negative organizational
outcomes. Moreover, it will be interesting to explore the impact of task conflict on job
performance in non-routine technical jobs. This study will investigate the two
dimensions of job performance so as to provide a broader perspective on performance
of employees
3.2 Task Conflict and Turnover Intentions
3.2.1 Studies Linking Task Conflict and Turnover Intentions
There are two main stream themes in research on task conflict. One stream of
research states that presence of task conflict highlights member differences, which
threatens positive team identity and their attachment to the core values of the group
78
(Avgar, Kyung Lee, & Chung, 2014, 2014). Cognitive dissonance as a result of task
conflict prevents employees from developing emotional attachment with their
workplace which more likely leads to withdrawal behaviors such as turnover (Jehn,
1995). Individuals no longer feel themselves as part of the clan and their bonding with
their workplace diminishes subsequently. Consequently, this may lead to a stronger
desire to leave the group. These findings are largely based on the studies carried out in
western individualist cultures. Later, De Wit et al., (2012) stated in their meta-analysis
that task conflicts are less negatively related to turnover intentions as compared to
relationship conflict. We argue that implications of task conflict will be different in
collectivist societies due to differences in value system.
The other stream of conflict research terms conflict as energetic force that
enhances group cohesion (Todorova et al., 2014). Conflict researchers(Jehn,1997,
Matsuo, 2006; Tjosvold, 2008; Parayitam & Dooley, 2009; Bradley et al., 2012) state
that task conflict results in creative solutions which lead to creative behaviors and
knowledge sharing behaviors among individuals. Task conflict involves idea sharing
and knowledge sharing, which in turn lead to innovative behaviors in individuals and
it has been termed as energizing force that makes employees more satisfied with their
jobs (Todorova et al., 2014). Task conflict is related to the nature and contents of the
task per se (Matsuo, 2006), the creative discussions should enhance a person‘s
emotional attachment with his/her job, hence, it may be assumed that task conflict
may have a negative impact on the turnover intentions of employees.
3.2.2 Substantiating Evidences from the Literature
The literature review reveals that the research on task conflict has yielded
mixed results (Puck, & Pregernig, 2014; Beldow et al., 2009; De Drue & Weingart,
2003), and majority of the studies have been conducted at team level (Lu et al.,
2011;Tyastuti et al., 2014; Meng, Fulk, & Yuan, 2015; De Wit, Greer & Jehn, 2012;
Aaldering & De Dreu, 2012; Greer, Jehn & Mannix, 2008; Radford, 2008; Medina et
al., 2005; Jehn & Bendersky, 2003; Jehn & Mannix, 2001; Jehn, 1995). Researches
which have been conducted on the relationship of task conflict and work behaviors
focused more on the direct relationships (De Wit, Greer, & Jehn, 2012; Haq, 2011;
Choi, 2010; De Drue & Weingart, 2003) whereby the explanatory mechanisms
linking these relationships have not been explored. Conflict affects different people
79
differently, as task conflict may serve as an opportunity for some people as means of
self-expression leading to positive subjective well-being in individuals and still we are
in search of those factors which may enhance the positivity of conflict.
Cronin and Weingart (2007) state that task conflict represents a process
through which different ideas and perspectives surface and diverse information is
accumulated, elaborated, and shared among individuals. Taking a lead from this idea
sharing and information accumulation process entailed through task conflict, we
expect that there are certain psychological processes through which task conflict
exerts its effect on individual outcomes. Indicators of workplace well-being such as
work engagement and job satisfaction (Bakker & Oerlemans, 2011) may mediate the
relationship between task conflict and work behaviors. Researchers (Bakker, 2010;
Page & Vella-Brodrick, 2009) emphasize the need of identification of factors required
to manage conflict effectively and enhance positive well-being of individuals which
leads to their better outcomes.
Task conflict has been termed as a double-edged sword (Meier et al., 2013),
sometimes yielding positive results and sometimes negative results at individual as
well as organizational levels (De Drue & Weingart, 2003). Therefore, the quest to
search for factors which may contribute towards better understanding of underlying
processes must continue. Building its theoretical foundation on the resource
acquisition/investment principle of the COR theory, this study investigates whether
task conflict is a resource and how it impacts different forms of workplace subjective
well-being and finally task performance, contextual performance, and turnover
intentions of employees. The present study will help broaden our vision and deepen
our understanding about how task conflict transmits its effect on work behaviors
through indicators of workplace subjective well-being-work engagement and job
satisfaction.
3.3 First Route of Theoretical Framework: Resource
Investment/acquisition Principle of the COR Theory; Task
Conflict, Work Engagement/Job Satisfaction, Job Performance
and Turnover Intentions
The first route of theoretical framework of the study explicates relationship
between task conflict, and work behaviors such as task performance, contextual
80
performance, and turnover intentions. Further, it explains the mediation of two
indicators of well-being -work engagement and job satisfaction between task conflict
and work behaviors relationship on the basis of the resource investment/acquisition
principle and gain spirals of the Conservation of Resources (COR) theory (Hobfoll,
1988, 1998, 2001).
3.3.1 Resource Investment/acquisition Principle of the COR
theory and Gain Spirals
The COR theory delineates the basic instinct of individuals that they always
strive to maintain, foster and retain valuable resources (Hobfoll, 1989). Based on the
basic premise of the COR theory that individuals invest resources in order to protect
existing resources, to recover from losses, or gain further resources (Hobfoll, 2001a),
we explain the relationship of task conflict and work behaviors. The COR theory
predicts that when investment of resources results in good return, and consequently
goals are achieved, people experience this as a gain that increases the existing pool of
resources, thereby generating a positive gain spiral of resources. The underlying
intention in this tenet is to gain new or additional resources, beyond the protection of
existing pool of resources. This signifies a general tendency of individuals to enrich
their existing reservoir of resources (Hobfoll, 2002). Halbesleben et al., (2014) state
that resource investment is a complex process that entails several psychological
factors. The related corollary of this principle articulates that individuals with more
resources are in a better position to invest and gain additional resources (a resource
gain spiral), (Hobfoll, 2001a).
Resources are defined as ―anything perceived by the individual to help attain
his or her goals‖ (Halbesleben et al., 2014). They further state that resources hold
their value to the extent that they are instrumental in the achievement of goals. The
value of these resources depends upon the context in which resources operate.
Individuals strive to acquire resources and may likely to invest some of their existing
resources to achieve resource acquisition (Hobfoll, 2001a).
Task conflict in the context of technical jobs may yield different results as we
expect that task related discussions that entail contrasting ideas, viewpoints and
perspectives may lead to better outcomes. Employees who come across different
approaches, perspectives and viewpoints, and deliberate on them are more likely to
81
expand their own reservoir of approaches, ideas and perspective or more precisely
their cognitive resources. Employees strive to create novel solutions out of their task
conflicts (Jehn, 1995; Tjosvold, 2008; De Drue, 2008) which may contribute towards
positive outcomes. According to the COR theory, resources are positively related to
important job outcomes. Although research has identified a positive relationship
between task conflict and work behaviors (Jehn, 1995; Lu et al., 2011; Solansky et al.,
2014), little is known about the psychological processes that translate the impact of
task conflict on individual‘s outcomes.
3.3.2 Direct Relationship among Task Conflict and Work Behaviors
Research on the relationship of task conflict and work behaviors has yielded
mixed results (De Drue & Weingart, 2003; De Wit, Greer, & Jehn, 2012; Tjosvold,
2008). In fact, the precise nature of the link between task conflict and job performance
has been elusive (Solansky et al., 2014) because the researchers have found evidence
for positive, negative, and curvilinear relationships between the two constructs (Jehn,
1995; Medina et al., 2005; Shaw et al., 2011). Researchers are still in search of the
factors which can contribute towards the positivity of the task conflict as it has been
termed as a double-edged sword as it may help or hurt performance (Bradley et al.,
2012; Meier et al., 2013).
Researchers (Amason, 1996; Olson et al., 2007) found a positive relationship
between task conflict and job performance of employees. Jehn (1995; 1997) argues
that task conflict in non-routine tasks yields positive results. Task conflict results in
positive performance because difference in opinion may allow individuals to analyze
contrasting perspectives of an issue, challenge validity of long-held beliefs (Bradley et
al., 2012), and promote creative thinking (Amason and Schweiger, 1994). Jehn and
Bendersky (2003) suggest that task conflict facilitates certain outcomes at both the
individual level and group level. At the individual level, having one‘s ideas
challenged can result in an increase in effort, enhance task focus, and divergent
cognitive perspectives. De Dreu (2006) states that during task related discussions,
employees engage in deep and deliberate processing of task-related information,
leading them to become more effective and productive. This could result in better
understanding of the tasks at hand which may improve their performance. Moreover,
task conflict has been described as ―one of the core processes through which deep
82
level discussion and use of diverse information takes place‖ (Cronin & Weingart,
2007; Jehn et al., 1999).
Task performance refers to ―officially required outcomes and behaviors that
directly serve the goals of the organization‖ (Bakker, 2010). ―Basic tenet of COR
theory is that individuals are motivated to protect their current resources and acquire
new resources‖ (Halbesleben et al., 2014). Using the lens of the COR theory, task
conflict, an exchange of cognitive resources may have a potential to impact task
performance positively. We posit that sharing of cognitive resources among
coworkers becomes even more important in technical tasks, and may improve their
task performance. Task conflict may help remove certain ambiguities related to tasks
at hand, thus improving their performance. Hence it is hypothesized:
H1a: Task conflict is positively related to employees’ task performance.
The relationship between task conflict and contextual performance is not well
documented in literature except few studies such as Lu et al., (2011), and Chen et al.,
(2011). Contextual performance includes activities such as helping and cooperating
with each other; showing respect to others (Taris and Schaufeli, 2014); going an extra
mile for achieving organizational objectives; enthusiastically accomplishing one‘s
own tasks and performing task activities that are not part of the core duty (Motowildo
et al., 1997). Task conflict fosters cognitive cooperation among coworkers as they
share their expertise and knowledge and build on each other‘s ideas. Task related
discussions provide employees with sufficient informational resources (Chen et al.,
2011) and can stimulate richer interactions among individuals and improve
performance (Bradley et al., 2012). Conflict may increase interpersonal collaboration
skills (Laursen and Hafen, 2010). It has been theorized to facilitate mutual
understanding and openness among employees, as a result of sharing of different
insights and ideas, thus integrating viewpoints from dissimilar frames-of-reference
(Pinkley, 1990). It also increases communication and information-sharing among
individuals (Jehn & Bendersky, 2003). Pelz and Andrews, 1966, state that intellectual
tension and vigorous critical interactions among peers which focus on core tasks
improve performance.
Hobfoll (2011) argues that sharing of resources becomes critical in
organizations as individuals in organizations are often held accountable for others
83
(Hobfoll, 2011). From a COR theory perspective, task conflict may contribute
towards improvement in contextual performance because task related discussions
among employees may foster their healthy functional interactions (Solansky et al.,
2014), and helping behavior whereby employees may gain from each other‘s
perspectives and learn to coordinate the effort to integrate informational resources.
Bradley et al., (2012) contend that task conflict has the potential to stimulate richer
interactions among individuals which can improve performance. Moreover, task
conflict may serve as an opportunity for employees to come together to exchange,
discuss, and discern useful information among them. Thus, we hypothesize that;
H1b: Task conflict is positively related to contextual performance of
employees.
Task conflict contributes positively towards organizationally valued outcomes
such as task performance, innovative behaviors and knowledge sharing behaviors (Lu
et al., 2011). The findings of these studies corroborate our assumption that task
conflict owing to its contribution towards fostering cognitive cooperation among
employees and making them more committed with their jobs may lessen their
intentions to leave their jobs. Moreover, the constructive discussions in complex tasks
make employees more clear about their jobs and increase their satisfaction with work
(Todorova et al., 2014), hence it is more likely that they would tend to stay at their
workplace. Therefore, it is expected that task conflict will have negative impact on
turnover intentions. Therefore, we formulate:
Hypothesis 1c: Task conflict is negatively related to turnover intentions
3.3.3 Mediation of Work Engagement/ Job Satisfaction in the
Relationship between Task Conflict and Work Behaviors
The COR theory suggests that resources have inherent motivational power
(Hobfoll, 2011). Moreover, a corresponding corollary of the COR theory states that
individuals who possess more resources are likely to gain further resources than
individuals who have few resources (Hobfoll, 2001). We explain our assumptions
84
related to mediation of work engagement and job satisfaction on the basis of this
corollary.
Conflict researchers (Jehn, 1995; Medina et al., 2005; Miron-Spector et al.,
2011; Tjosvold, 2008; Solansky, Singh, & Huang, 2014) argue that task conflict leads
to divergent thinking, deep processing of task-related information, exploration of new
ideas, creative solutions and improves decision quality. Individuals who come across
different ideas, approaches, and perspectives and capitalize on them are more likely to
expand their own systems of approaches, cognitive attention and perspectives
(Todorova, 2014). Researchers suggest that conflict enhance well-being as
disagreements can improve mental health and social flexibility as far as it provides
platform for self-expression and cooperation (Laursen and Hafen, 2010). These
findings suggest the possibility of presence of an explanatory mechanism linking the
direct relationship of task conflict and work behaviors. Different indicators of
workplace subjective well-being such as work engagement and job satisfaction may
mediate this relationship due to the reason that exchange of cognitive resources may
lead to positive outcomes and this relationship may have some underlying mechanism
which connects resources to individual outcomes. On the basis of the resource
investment/acquisition principle of the COR theory, the motivational process initiated
by positively-valued resources mobilize employees, energize their potential and
makes them more engrossed in their work (Schaufeli, 2013).
We expect a positive relationship between task conflict and work engagement
because when employees engage in task conflict, they come up with new ideas and
new concepts about their work and have better understanding of issues at hand (Wang
& Nasr, 2011). At the individual level, having one‘s viewpoints challenged may result
in an increase in effort, enhance task focus, and divergent ideas (Jehn & Bendersky,
2003). Researchers (Chen et al., 2011) contend that task-related involvement
behaviors entail discussion, exchange of ideas, and sharing of task-related
information. De Wit et al., (2012) state that task conflict involves critical reevaluation
of the different perspectives as it is more specifically related to the task at hand.
Tjosvold (1991) argued that conflict can be a manifestation of the right to
voice individual dissent and self-expression, thus enabling them to identify the
problem areas, and devising more solutions through critical thinking. Contrasting
views in task conflict enhances employees‘ ability to analyze task problems deeply,
which fosters learning and growth (Chen et al., 2011). Task conflict is argued to
85
enhance performance through deep understanding of various viewpoints, ideas and
multiple perspectives (Jehn & Bendersky, 2003). Kahn (1990) explains that work
engagement is related to self-expression and self-employment in tasks that promote
individuals‘ connection to their work and others at workplace. Hence, this ideas
exchange technique may help them to be more engrossed in their jobs, help solve
work related problem, and they may feel more connected to their work. Using the lens
of the COR theory, we argue that employees exchange different ideas, perspectives
and opinions during task conflicts which may help them become more absorbed in
their work, thus building more resources and triggering a gain spiral where initial
resource gain leads to further accumulation of resources which manifest as work
engagement. Hence, our next hypothesis is:
Hypothesis 2: Task conflict is positively related to work engagement
Task conflict is a means of integration of different perspectives that
materializes from the exchange of information and coordination of individuals
(Amason, 1996). Research has shown that work engagement mediates the link
between work demands and organizationally valued job outcomes (Karatepe et al.,
2014). Task conflict has been said to be related to better understanding of the task
(Jehn, 1995). When employees engage in task conflict, they exchange ideas and
information, which in turn may contribute positively towards their performance in a
way that they become more clear about what to do and how to do it.
Kahn (1990) argued that people need self-expression and when they express
their views, this may lead to their work engagement. In fact, engaged employees feel
an energetic and effective association with their work which enables them to cope up
well with the demanding jobs (Del Libano et al., 2012). Engaged employees love to
work in challenging work environment (Van Beek et al., 2014) and they feel ―a
psychological connection with their work and exert their cognitive, physical and
emotional energies to tasks at hand‖ (Christian et al., 2011). Their energy and focus
motivate them to put in extra effort (Yalabik, Popaitoon, Chowne, & Rayton, 2013).
Deep discussions and discourse over different ideas and perspectives may energize
employees because the information they engender may help them improve their
performance (Todorova, Bear, and Weingart, 2014).
86
Task conflict increases an individual‘s capacity to process task related
information deeply and deliberately (De Drue and West, 2001) and triggers mental
stimulation (Xin and Pelled, 2003).It may be inferred that task conflict-an exchange of
cognitive resources, may foster work engagement through self-expression and
exchange of diverse ideas and unique relevant information in technical jobs that are
thought provoking and mentally invigorating. It may also enable individuals to review
and reexamine their own ideas and perspectives in greater depth, which would
increase an individual‘s engagement with their work. Hence, it may be implied that
task conflict may allow individuals to engage in deep thinking to combine the
perspectives and benefit from the new insights that contribute to improved
performance. From a COR theory perspective and consistent with our theorizing that
individuals who invest resources are likely to gain further resources, it may be
assumed that task conflict may be instrumental in acquiring additional resources that
may translate to positive outcomes by making employees more engaged through deep
cognitive understanding of the task, hence indirectly contributing to enhanced
performance. This leads to the following hypotheses of the study:-
H 2a: Work engagement mediates the relationship between task conflict and
task performance.
Task conflict stimulates intellectual discourse among employees through
increased understanding of the task-related differences (Jehn and Bendersky, 2003;
Farh et al., 2010), thereby facilitating integration of diverse perspectives, and may
foster collaborative activities among employees. This may in turn lead to
accumulation of informational resources manifesting as work engagement. Engaged
employees enjoy their work and this fun element motivates them to go beyond their
prescribed duties and they perform work activities that are beneficial for their
organizations. These factors contribute to their extra-role performance (Van Beek et
al., 2014). Kahn (1990) also suggested that engaged employees put their personal
selves into their work that go beyond the formal boundaries of their jobs to facilitate
the organization and its people. As we expect in this study that task conflicts help
employees come together to solve their task-related problems and gain creative
knowledge from each other as result of their social cognitive interactions, this may
lead to prosocial behaviors which can benefit organization as a whole. Furthermore,
87
as a result of gain spirals initiated through task conflict through engagement (Hobfoll,
2001) the individuals are expected to have sufficient pool of resources to meet their
job demands as well as to facilitate people around them by extending interactive
support. Hence we hypothesize that;
H2b: Work engagement mediates the relationship between task conflict and
contextual performance.
To the extent that task conflict provides an opportunity to employees to
become more engrossed in their work and develop a psychological connection with
their job, it is more likely to result in decreased intention to quit their workplace.
Schaufeli and Bakker (2004) suggest that engaged employees are psychologically
attached to their organizations since they highly invest in their jobs and strongly
identify with their work and therefore exhibit lower propensity to leave their jobs.
Engaged employees are satisfied with their jobs because they value their work and are
less likely to leave their jobs since they derive a sense of attachment with their work
(Van Beek et al., 2014). We expect in this study that task conflict will negatively
affect turnover intentions of employees because task related discussions will make
employees more involved in their work and enhance their identification with the work
and organization and result in more psychological attachment with their jobs which in
turn will lessen their propensity to leave their jobs. Hence, we formulate that;
H2c: Work engagement mediates the relationship between task conflict and
turnover intentions.
Task conflict has been termed as energizing force that makes employees more
satisfied with their jobs (Todorova et al., 2014) since task conflict serves as a means
to participate in discussions and voice one‘s concerns (Loughry and Amason, 2014).
Huang and Van De Vliert(2004) argue that mentally challenging tasks are one of the
antecedents of job satisfaction. Bruce and Blackburn (1992) state that ―satisfied
employees are more likely to experience high internal work motivation, to give high
quality work performance, and to have low absenteeism and turnover‖ (p. 6). Task
conflict may lead to more thorough deliberation of ideas, allowing individuals to
evaluate and consider unique perspectives in addition to being able to express their
88
own personal views (Tjosvold, 2008). It has been found to be associated with
affective responses such as enhanced satisfaction and commitment (Amason, 1996;
Behfar et al., 2011). Consistent with our present theorizing that exchange of cognitive
resources may lead to positive outcomes, we expect that task conflict in technical jobs
is the means to voice differing ideas, opinions, and viewpoints, hence may lead to
personal gratification or in other words satisfaction with their work. In light of the
preceding discussion, we advance the following hypothesis:
Hypothesis 3: Task conflict is positively related to job satisfaction
Task conflict may impact task performance positively through its impact on
job satisfaction as job satisfaction has been found to be related to positive job
behaviors such as job performance (Judge & Klinger, 2008). Self-expression of
different concerns related to a task may instill a feeling of being satisfied which may
contribute toward their task performance as task related discussions may help remove
certain misconceptions and ambiguities about work to be done. Task conflict goes
beyond merely participating in work related discussions to include making one‘s own
ideas and opinions known to others (Jehn, 1995), which may add to their being more
satisfied where it may serve as an opportunity for individuals to raise their task related
issues, and have their viewpoints deliberated, thus making them more satisfied. Hence
its purpose is to help individuals identify task related problems which may get
overlooked otherwise, and may contribute towards improved performance. Consistent
with the tenets of the COR theory, we expect task conflict to lead to increased
satisfaction as a result of gain spirals initiated through task conflict discussions among
individuals, which in turn leads to enhanced task performance. Hence, our next
hypothesis is:
Hypothesis 3a: Job satisfaction mediates the link between task conflict and
task performance
Task conflict may serve as a means to be heard as individuals are motivated to
seek further cognitive cues from their coworkers that may lead to better solutions or
better ways of doing work, thereby instilling a feeling of being satisfied. Hence, we
expect task conflict to enable employees to engage in mutually satisfying interactions
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and perform well beyond their core job duties since they gain sufficient resources in
the form of multiple perspectives, ideas and viewpoints. Satisfied employees express
their sense of satisfaction by engaging in prosocial behaviors such as cooperative
relationships and social facilitation with others that are beyond their prescribed job
assignments (Podsakoff et al., 1996). This implies that satisfied employees may
become good performers by engaging in in-role (task performance) as well as extra-
role behaviors (contextual performance).
Based on the resource investment/acquisition principle of the COR theory, we
argue that employees accumulate more cognitive resources during task conflicts
entailing content-related discussions with their coworkers to make meaningful
connections between such large numbers of differing perspectives, which enhance
their level of satisfaction with their job. This in turn positively affects their social
functioning through freeing up more mental resources and increases their likelihood
to engage in more coordinated efforts for the accomplishment of work tasks. It is
through these gain spirals that they have more resources to facilitate other employees,
thus creating an overall positive environment. On the basis of this discussion, we
advance the following hypotheses:
Hypothesis 3b: Job satisfaction mediates the link between task conflict and
contextual performance
Conflict researchers (Tjosvold, 2008;Miron-Spektor et al., 2011; Bradley et
al., 2012) argue that task conflict results in multiple perspective-taking and novel
solutions through constructive discussions (Jehn, 1995). We advance the argument
that task-related discussions provide a platform to individuals to work closely, voice
their own perspectives and concerns (Behfar et al., 2011) and share ideas, and know
each other viewpoints thus creating an overall satisfying environment and cultivating
a sense of belongingness. All these activities contribute towards creating a community
of employees which may strengthen their bonding with their organization as well.
When individuals feel satisfied as result of expressing their own opinions and
reflecting on other‘s perspectives, they tend to feel an attachment with their work,
thus likely to exhibit weaker turnover intentions and a stronger desire to stay with the
organization (Amason, 1996). According to the COR theory perspective, cognitive
exchanges triggered by task conflict enhance the resource reservoir of individual in
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the form of job satisfaction that leads to increased attachment to the workplace.
Research shows that satisfied employees are less likely to leave their jobs (Lu et al.,
2002; Tett & Meyer, 1993), therefore, it is expected that task conflict will have
negative impact on turnover intentions through it positive impact on job satisfaction.
This leads us to the following hypothesis;
Hypothesis 3c: Job satisfaction mediates the link between task conflict and
turnover intentions
The relationship between task conflict and different facets of subjective well-
being at work and their impact on task performance, contextual performance and
turnover intentions has been shown in Figure 3.1.
Route –I- Resource Investment/Acquisition
Figure: 3.1: Task Conflict, Well-being and Work Behaviors Model
Source: Compiled by Researcher
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3.4 Relationship Conflict and Job Performance
Review of the relevant literature reveals that there appears to be consistent
evidence that relationship conflict is associated with debilitating performance.
Conflict researchers (Amason, 1996; De Drue & Weingart; De Wit, Greer, & Jehn,
2012; Jehn, 1995, 1997; Lau & Cobb, 2010; Simons& Peterson, 2000) have
unequivocally documented that relationship conflicts are detrimental to individual as
well as group performance. De Drue and Weingart (2003) found in their meta-
analysis that both task conflict and relationship conflict are negatively related to job
performance of employees. Relationship conflict not only results in poor performance
(De Dreu, 2008; Jehn et al., 1999; Kacmar et al., 2012), but also contributes
negatively towards contextual performance (Choi, 2010), thus undermining overall
performance.
De Wit, Jehn, and Scheepers (2013) proved in their studies that presence or
absence of relationship conflict determines the efficacy of task conflict in decision
making in groups. In case of relationship conflict, task conflict will result in poor
decisions due to biased information processing by the group members.
This study investigates the two dimensions (task and contextual) of job
performance so as to provide a broader perspective on performance of employees.
Conflict might have a direct relationship with job performance or we might expect a
relationship between conflict and job performance mediated by job burnout (an
indicator of impaired subjective well-being) due to the fact that if task conflict or
relationship conflict is affecting the well-being in a positive or negative way, it may in
turn influence their performance.
3.5 Relationship Conflict and Turnover Intentions
The problem of turnover is generic part of every organization (Kim & Chang,
2014). Nonetheless, success of an organization hinges upon the retention of a highly
skilled human capital (Korsakienė et al., 2015), hence, the phenomenon of turnover of
skilled employees becomes the nightmare for organizations. Turnover intentions not
only harm the organizations in terms of economic costs such as hiring and training of
the new replacement, but it also involves costs at individual level such as loss of
relationships and productivity (Kim & Park, 2014)
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Turnover intention is ―a conscious and deliberate willingness to leave the
organization‖ (Tett & Meyer, 1993). According to researchers (Ajzen & Fishbein,
1980) intentions are the immediate determinants of actual behavior, and the final step
in the turnover process before actual departure. It is also important from research
perspective since employees who leave are hard to trace and it becomes impossible to
determine what actually caused them to leave (Firth, Mellor, Moore, & Loquet, 2004).
Moreover, researchers (Griffeth at al., 2000, Carmeli & Weisberg; 2006;
Rahman, 2012; Kim & Park, 2014) believe that turnover intention is the strongest
surrogate precursor of actual turnover. Korsakienė et al., (2014) found in their study
that the most important factors required for the retention of employees are the
relationships among peers, and between employees and their managers.
Evidence shows that work stressors have negative effect on the individuals
and detrimental impact on their organization (Cropanzano, Kacmar, & Bozeman,
1995). Conflict researchers (De Dreu and Weingart, 2003; Passos & Caetano, 2005;
Tjosvold, 2006; Mooney et al., 2007; Gamero et al., 2008; Jehn & Jonsen, 2010;
Huttermann & Boerner 2011; Martínez-Corts et al., 2011; Wang & Nasr, 2011;
McKenzie, 2012; Ismail, Richard & Taylor, 2012; Bouckenooghe et al., 2014) argue
that relationship conflict is related negatively to positive personal and organizational
consequences and positively to withdrawal behaviors and other negative outcomes
such as turnover intentions (Avgar et al., 2014; Medina et al., 2005).
According to COR theory, individuals may undergo stress when invested
resources do not result in favorable returns (Harris et al., 2009). Relationship conflict
with employees may undermine their association with their organizations as they no
longer want to remain a part of the work unit due to negative work experience and
hostile attributions towards each other (Jehn et al., 1999; Jungst & Blumberg, 2016).
Social stressors reduce employees‘ overall resilience as they drain their valued
resources (Harris et al., 2009). This may cause a decrease in emotional attachment to
his/her organization since due to stressful and hostile environment, employee may
think about alternative job opportunities.
3.6 Substantiating Evidences from the Literature
The literature review reveals that the research mostly conducted at group level
on effects of relationship conflict unanimously proven its negative impact on
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important individual as well as organizational outcomes such as job performance, job
satisfaction, commitment, productivity and found to be positively related to stress,
withdrawal behaviors and psychosomatic complaints (De Drue & Weingart, 2003; De
Drue & Beersma, 2005; De Drue, 2008; Lu et al., 2011; Meier, Gross, Spector, &
Semmer,2013; Meier, Semmer, & Gross; 2014). In conflict research, studies on
relationship conflict and work behaviors (Kacmar et al., 2012, De Wit, Greer, & Jehn,
2012; De Drue & Weingart, 2003) have unfortunately not emphasized on the
explanatory mechanisms linking these direct relationships. Researchers (De Drue,
2008; Benitez et al., 2011; Meier, Semmer, & Gross, 2014) suggest the need of more
studies on conflict, well-being and work behaviors of individuals since the success of
the organizations hinges upon the quality of interpersonal relationships among
individuals.
Research on interpersonal conflict also ignored the impact of the association
of relationship conflict and different dimensions of job burnout (an indicator of
impaired well-being) on important work behaviors such as task performance,
contextual performance and turnover intentions of employees. The study of these
constructs will provide us with a clear understanding of the implications of the
underlying relationships and their effects on individuals and organizations. The
present study is an effort to understand this relationship with the help of different
dimensions of job burnout i.e., exhaustion, cynicism, and interpersonal strain at work.
In the backdrop of the conservation of resources (COR) theory, this study investigates
the impact of relationship conflict on different dimensions of job burnout and finally
the impact of this relationship on work behaviors of employees.
3.7 Route Two of Theoretical Framework: Resource Depletion
Process: Conservation of Resource Theory; Relationship
Conflict, Burnout, Job Performance, and Turnover Intentions
The second route of theoretical framework of the study explicates connection
between relationship conflict, work behaviors such as task performance, contextual
performance, turnover intentions, and job burnout on the basis of the Conservation of
Resources (COR) theory (Hobfoll, 1988, 1998, 2001).
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3.7.1 The Conservation of Resources Theory (Primacy of Loss
Principle and Loss Spirals)
The basic premise of COR theory is that stressful environment lead to resource
loss. When resources are threatened or lost, individuals may experience negative
consequences and loss of resources is the ―principal ingredient in the stress process‖
(Hobfoll, 2001). Although COR theory emphasizes resource losses (due to stressful
circumstances) and resource gains (from favorable events or conditions), the major
focus is on losses (Dewe et al., 2012). Hobfoll (2001) argues that since resources
losses pose a serious threat to survival, they have primacy over resource gains when
an individual is facing adverse stressful conditions. He further elaborates that
individuals tend to attach more significance to resources losses than gains, because
losses may undermine a person‘s resilience and resolve to survive and sustain their
existence. ―It is psychologically more damaging for individuals to lose resources that
it is helpful for them to gain the resources that they lost‖ (Halbesleben et al., 2014).
However, resource gains per se are important for the person to grow and to improve
their overall psycho-social well-being (Dewe et al., 2012).In case of loss of resources,
further investment of resources becomes more difficult (Halbesleben et al., 2014).
―Losses at work at work are expected to have more impact than similarly
value gains‖ (Halbesleben et al., 2014). COR theory contends that stress may occur
due to one or more of three conditions; ―when resources are threatened, actually lost
or when there is almost no resource gain after significant resource investment‖
(Westman et al., 2005). Gorgievski and Hobfoll (2008) argue that ―when primary
resources get threatened, individuals may tend to focus on their losses and weaknesses
rather than their strengths‖.
Workplace stressors not only disrupt the organizational functioning but also
hurt employees by reducing their effectiveness (Fox, Spector, and Miles, 2001). Prior
research has proven that stressors arising from the social environment at workplace
have significant impact on emotional and psychological well-being of employees
(Halbesleben et al., 2014), as well as direct relationship with organizationally relevant
outcomes (Lee, 2007). Hobfoll (1989, page 342) argued that interpersonal
relationships with coworkers are resources (Schat & Frone, 2011), to the extent that
they help provide or facilitate the achievement of other valuable resources. Workplace
interpersonal conflict represents an important work stressor that leads to several
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deleterious outcomes for both employees and their organizations (Frone, 2000). The
researcher (Frone, 2000) further argues that interpersonal conflict with coworkers is
related to psychological outcomes. Dewe et al., (2012) state that conflict with other
people at work wears out the energy back-up of individuals, takes time to deal with,
diverts their attention from the focal tasks, all of which contributes to resource losses.
Social interaction or relationships at workplace provide individuals with the
requisite help and feeling of attachment (Hobfoll & Stokes, 1988, p.499). One of the
primary resources is having meaningful relationships and belonging to resourceful
social entities (Gorgievski & Hobfoll, 2008). The depletion of these resources
jeopardizes an individual‘s resilience to cope up with stressful events, eventually
leading to negative repercussions. Empirical evidence indicates that employees who
lose resources at work are more prone to undergo strain in the form of burnout
(Halbesleben et al., 2014). The present study theorizes in this direction that
relationship conflict with co-workers may lead to burnout. Most important, we argue
that relationship conflicts are capable of triggering negative emotional responses
which may have detrimental consequences for individual behaviors. This negative
impact of relationship conflict on workplace subjective well-being may have negative
effect on work behaviors of employees.
Keeping in view the implications of the COR theory (Harris, Harvey, &
Kacmar, 2009), it can be assumed that social stressors such as relationship conflict
may have positive impact on negative indicators of subjective well-being such as job
burnout because loss of social capital as a result of relationship conflict will cause
stress in individuals. Relationship conflict produces negative feelings in individuals
and they tend to expend less effort in completion of their task work (Amason, 1996).
These negative emotional responses reduce opportunities to facilitate coordination
among individuals which ultimately affects their performance and satisfaction (Jehnet
al., 1997). According to the COR theory, employees invest a significant effort in
terms of time and energy in developing and maintaining social ties at work (Harris et
al., 2009). Positive interactions yield fruitful return on their investment, whilst
negative interpersonal interactions as a result of relationship conflict may undermine
these resources. Presence of relationship conflict may sabotage the reinforcement and
personal investment in social relationships and they may lose social support of their
colleagues which is strongly desirable in work context since it contributes to
maintenance of a strong resource reservoir (Hobfoll, 2001).
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Relationship conflict is considered detrimental for organizational effectiveness
and individuals‘ performance (Jehn, 1995; De-Drue & Weingart, 2003; Choi, 2010,
Huang, 2010). Social stressor such as interpersonal conflicts (Hobfoll, 2001) and their
impact on employees‘ work behaviors can also be understood in the backdrop of the
COR theory.
3.7.2 The Direct association of Relationship Conflict and Work
Behaviors
Empirical research has documented that relationship conflict negatively affects
job performance and has positive impact on withdrawal behaviors (Amason, 1996;
Jehn, 1995; De-Drue and Beersma, 2005; Choi, 2010). Employees undergoing
relationship conflict exert their cognitive attention on interpersonal issues thus being
preoccupied with relational tensions which limits the use of their cognitive resources
for task related issues and diverts their behavior, energy and time away from the job
(Bouckenooghe, De Clercq, & Deprez, 2014). Employees spend most of their time in
ignoring or resolving relational tensions which makes them unproductive and
inefficient (Jehn, 1995). Consistent with previous findings and primacy of loss
principle of the COR theory, we argue that due to loss of social associations at work,
employees may lose their concentration and focus as they pay more attention to
interpersonal incompatibilities (Bouckenooghe et al., 2014). Relational tensions cloud
the task-related efforts (Parayitam and Dooley, 2009). They tend to spend
disproportionate amount of time and cognitive resources to deal with relational issues
and less time on productive activities which causes them to work less effectively and
consequently distracts them from the tasks at hand (Shaw et al., 2011). Relationship
conflicts with coworkers are socially damaging and negatively impact their work
experience (Kacmar, Bachrach, Harris & Noble; 2012). This social loss may dampen
their resolve to perform since they lose their interest in works their thoughts revolve
around loss and deprivation. Hence we formulate that;
H4a. Relationship conflict is negatively related to employees’ task
performance
Contextual performance relates to ―maintenance and enhancement of the
social and psychological context that support task performance‖ (Organ, 1997, p.91).
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Examples of the contextual performance behaviors are supportive coworkers`,
performing tasks in addition to core activities and spreading goodwill of the
organization (Borman and Motowidlo, 1993). Negative psychological responses
resulting from relationship conflict deteriorate satisfaction in individuals and harm
interactions among employees (Huang, 2012), and they focus more on interpersonal
attacks rather than work per se which result in overall poor performance (Jehn, 1995).
It also destabilizes interpersonal associations among employees thus leaving them
isolated and alienated (Laursen & Hafen, 2010). Individuals undergoing relationship
conflict do not share useful information among themselves since they dislike each
other and their associations with each other destabilize due to their interpersonal rifts
(Jehn, 1995, 1997). Relationship conflict negatively impacts individual directed
citizenship and knowledge sharing behaviors (Lu et al., 2011) as it tends to generate a
destructive climate which often engenders negative feelings, misattribution and non-
cooperative behavior among individuals which may inhibit rational interaction among
individuals, thereby reducing productive information processing among coworker (De
Drue & Weingart, 2003; De Wit et al., 2012; Lau & Cobb, 2010). When individual
experience stressful interactions as a result of relationship conflict, they develop
mutual enmity and intense personal differences, they avoid each other and may be less
likely to cooperate which has detrimental effect on their sharing behaviors and carries
serious implications for social processes at work (Jehn, 1995).
Salience of loss principle (Hobfoll, 2001) articulates that the loss per se affects
individuals‘ physiological, cognitive, emotional and social responses. ―Relationship
conflict at work impedes social processes at work whereby individuals tend to engage
in antagonistic attributions for others‘ social behaviors at work‖ (Kacmar et al., 2012).
When individuals experience relationship conflict, they tend to exhibit withdrawal
behaviors pertaining to cooperative activities such as useful informative exchanges
related to their work (Jehn et al., 1997). Interpersonal disagreements and tensions are
usually expressed with negative communication and lack of cooperativeness as well
as disregard for coworkers (Jehn, 1995).
We argue that once employees lose positive relationships with their coworkers
as a result of relationship conflict, their cooperation and support for each other and
discretionary behaviors for the overall benefit of the organization may diminish which
is crucial for maintaining a facilitating work environment. They may feel deprived of
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instrumental resources such as work-related help and advice due to their interpersonal
issues. Thus, we formulate that;
Hypothesis 4b: Relationship conflict is negatively related to contextual
performance of employees.
Turnover intention is a subjective evaluation of an individual regarding the
probability that he/she may leave the organization he/she works for in near future
(Mobley, 1982a, 1982b). Relationship conflicts with peers are socially damaging and
stressful events. These events have negative impact on employees‘ ―work experience‖
and turn the overall environment to unpleasant (Kacmar et al., 2012). Relationship
conflict has the potential to undermine their sense of self and similarity with others
(Giebels and Janssen, 2005), hence threatens their sense of membership. Hershcovis
and Barling (2010) state that when individuals experience negative encounters with
their colleagues at work, they no longer feel them part of the workgroup due to these
unpleasant incidents. They attribute this negativity to their organization which leads to
diminished organizational attachment. These negative work experiences may cause
employees to leave their organizations since they undergo intense mental suffering,
frustration and agonistic feelings which may make their working environment hostile
and unpleasant.
Researchers (Maertz & Griffeth, 2004; Reichers, 1985) state that individuals
experience multiple commitments to multiple constituencies in their organizations and
commitment with coworkers is one such example. It determines the motivational
mechanism for attachment or withdrawal behavior in the organization. A large body
of literature suggests that ―a critical part of an individual‘s sense of self is their need
to belong and coworkers have the capacity to influence employee feelings of
belongingness‖ (Hershcovis & Barling, 2010). Meier et al., (2013) contend that
relationship conflict threatens the sense of belonging to significant others. When
employees lose this attachment or lose feeling of being connected as a result of
relationship conflict, it may undermine their association with their organizations since
they no longer feel the social bonding which is an essential requirement for the
smooth functioning of organizational processes. Morrell and Arnold (2007) state in
their study of retrospective self-reports of ―leavers‖ that clashes with colleagues
constitute one of the major factors that contributes to actual turnover. Social stressors
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reduce employees‘ overall resilience as they drain their valued resources (Harris,
Harvey & Kacmar, 2009). Hence, we propose that relationship conflict with
coworkers set the stage for intention to quit. Once employees lose the social
commitment towards their coworkers, they may tend to focus more on other favorable
working environments, thus more likely to switch to other organizations. Hence, we
formulate that;
Hypothesis 4c: Relationship conflict is positively related to turnover
intentions
3.7.3 The Mediation of Job Burnout in the link between Relationship
Conflict and Work Behaviors
Employees generally want to be liked by their peers since it helps them to
maintain a positive social identity as they are underpinned by a desire to have
meaningful social relationships. Negative social interactions are said to be more
impactful than non-negative interactions since negative interactions are more
devastating and therefore, are more salient than non-negative interactions (Taylor,
1991). Reactions to relationship conflict typically include an inclination to withdraw
physically or psychologically from the unpleasant situation (Ross, 1989). Relationship
conflict is said to be related to anger, tension and negative emotional states (Cursue,
Boros, & Oerelemans, 2012). Moreover, negative interactions generate intense
affective, behavioral, and physiological responses than positive interactions (Taylor,
1991). Karasek (1979, p. 287) states that work stressors such as conflicts induce stress
in individuals, when unreleased, this negative energy manifests itself internally,
resulting in distress reactions and decreased well-being. The psychological distress
caused by relationship conflict can severely disrupt an individual‘s ability to perform
effectively for the organization, and can influence performance negatively. These
relational rifts among coworkers can have dramatic effect on individual well-being
and major implications for the success of the organization. This implies that the direct
link of relationship conflict and individual behaviors entails an underlying
mechanism.
We expect that burnout that captures the depletion of resources is the
mediating mechanism in the link between relationship conflict and individual
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outcomes through which loss spirals begin since researchers believe that individuals
who work in stressful conditions experience poor psychological well-being and more
likely to develop burnout (Sonnentag & Fritz, 2007). Moreover, Schaufeli and
Salanova (2014) state that the concept of burnout is embedded in context of
interpersonal relationships, and is more a social phenomenon(Maslach, 1981). People
with relational tensions are therefore probably more susceptible to burnout.
Specifically, we assume that each dimension of burnout has a unique mediating effect
on relationship conflict-specific form of individual outcome link. The mediation of
different dimensions of burnout in the link between relationship conflict and
task/contextual performance and turnover intentions has been explained on the basis
of conservation of resources theory (Hobfoll, 1988, 1998a). It has been argued that
negative life events have disproportionately profound effect than positive events
(Taylor, 1991). COR theory further contends that stress occurs in three situations, first
when resources are threatened, second when resources are actually lost and finally
when individuals don‘t get the return on their resource investment.
When employees undergo relationship conflict with their co-workers, this is
actually the loss of their primary resources i.e., their social ties (Hobfoll, 2001). This
loss leads to negative psychological states in individuals, which, in turn, may
exacerbate the negative effects of stress. Walton and Dutton (1969) stated that
individuals generally experience a negative state of psychological arousal ensuing
relationship conflict, which leads to frustration, uneasiness, and dislike of individuals
with whom they are in conflict. Interpersonally hostile environment and unfavorable
work conditions are related to impaired psychological well-being such as burnout
which serves to further deplete individuals‘ resources (Sonnentag & Fritz, 2007),
hence it is expected that the direct link between relationship conflict and individuals‘
outcomes entails an underlying mechanism which links it to work behaviors.
Hobfoll and Freedy (1993) termed COR theory as an ―overarching
framework‖ (p.115) to explicate human stress and burnout. Consistent with the
principles of the primacy of loss, they stated that ―workers are more sensitive to
workplace phenomena that translate to losses for them‖ (p.118). In order to counter
the loss effects, people employ coping efforts, thus, eventually investing more
resources. In this process, if there is no resource replenishment to offset resource
deterioration, resource depletion gains more momentum and intensity. The theory
delineates that individuals who have few resources are more vulnerable to further
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resource loss or loss spirals (Halbesleben et al., 2014), which can be cumulative as
losses pile up (Hobfoll, 2001), we explain the mediation of different dimensions of
burnout. With the onset of resource loss process, individuals are left with few
resources to cope up with stressors, which make them less resilient and more
vulnerable to stressors (Hobfoll, 2001). Based on this corollary of the COR theory, it
is argued that relationship conflict is the erosion of social ties at workplace.
Individuals experiencing relationship conflict are more vulnerable to more resource
loss which manifest as a strain (burnout). Consequently, those employees with
relationship conflict are expected to experience an internal deficit leading to greater
tendency to develop burnout, face difficulty in coping with job demands, and allow
this resource depletion process to exert stronger detrimental effects on employee
outcomes. This loss begets loss trail has serious implications for individual outcomes.
Research has documented a positive association between relationship conflict
and emotional exhaustion (Bear et al., 2014; Giebels and Janssen, 2005; Dijkstra, De
Dreu, Evers, van Dierendonck, 2009). Evidence suggests that when employees are in
relationship conflict, they lose their ability to concentrate on their tasks since
relationship conflict diverts their cognitive attention to interpersonal incompatibilities
rather than core responsibilities (Bouckenooghe et al.,2014). In other words, they are
blindsided by relationship rifts. This result in loss of time and energy accompanied
with physical and psychological withdrawal from the stressful environment (Jehn &
Bendersky, 2003). Researchers (Halevy et al., 2012) state that conflicts that
jeopardize social relationships are more depleting and exhausting. Consistent with the
COR theory, resource loss leads to stress in individuals. Although curtailing one‘s
work involvement in response to relationship conflict should reduce job performance,
it may also result in a more intense psychological and physical withdrawal from one‘s
job, thus resulting in successive depletion of resources. To the extent that relationship
conflicts tend to consume an individual‘s energy and other related resources, and
prevent resource acquisition that may be necessary to ward off current and future
resource needs, individuals are prone to experience work exhaustion. Hence, it is
hypothesized that relationship conflict will have positive relationship with exhaustion
which will in turn have negative impact on work behaviors.
Hypothesis 5: Relationship conflict is positively related to exhaustion.
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When individuals come across workplace stressors such as relationship
conflicts, they consume their energy and time to cope with that stressor, hence
utilizing more resources (Gilboa, Shirom, Fried, & Cooper, 2008). Stressful
conditions require individuals to draw from their energy reserves to maintain positive
functioning. Indeed, individuals use what resources they have to limit resource loss
and the adverse effects thereof. This further depletes their energy resources and
reduces their ability to perform by diverting effort and attention away from
performing job functions and they feel drained and overextended as a result of
expending efforts and energy on avoiding or managing interpersonal conflicts (Jehn,
1995). It follows that motivation to exert high level of effort will likely decrease in
response to relationship conflict as individuals tend to focus their time and energy on
interpersonal problems rather than tasks (Huang, 2012; Simons and Peterson, 2000).
Exhausted employees have problems related to perception and cognitive retention as a
result of cognitive fatigue which in turn contribute to undermining their ability to
perform tasks effectively (Sonnentag et al., 2014). Research has documented a
negative relationship between exhaustion and objective rating of in-role or task
performance, and organizational citizenship behavior (Taris, 2006).
We argue that relationship conflict initiates resource depletion process
whereby individuals lose their cognitive and energy resources required to perform
their core tasks in the form of exhaustion and may not have sufficient resources to
meet their job demands as relationship conflict interferes with their ability to
adequately perform their job. Owing to this lack of resources and energy and reduced
investment of effort, indicative of a loss spiral, ―they distance themselves from their
work to prevent further depletion of mental resources‖ (Van Beek, Hu, Schaufeli,
Taris, & Schreurs, 2012). In other words, the employees no longer have the capacity
to utilize available resources effectively as result of expending more attention and
energy on stressful interpersonal relations that could otherwise be used to perform
tasks, perhaps with the fear of losing further resources, and eventually exert
insufficient effort. Thus, we hypothesize that;
Hypothesis 5a: Exhaustion mediates the link between relationship conflict
and task performance
Relational rifts may consume an individual‘s energy and attention on solving
interpersonal problems, which in turn may reduce their ability to extend support to
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their coworkers, or in other words their contextual performance may suffer. The loss
process initiated by relationship conflict coupled with the drain of mental, physical
and emotional resources may leave the employees overextended and fatigued, thus
hampering their involvement in activities for the benefit of their coworkers. Loss of
relationship ties may increase the perceived severity of threats in the environment
such as feelings of helplessness and reduce the availability of the coping options,
hence increasing the likelihood of rapid resource loss in the form of exhaustion
(Campbell, Perry, Maertz, Allen, and Griffeth, 2013). They ultimately feel inadequate
in their ability to successfully go beyond their formal duties as they might be already
struggling with meeting their job demands. Hence, we hypothesize that;
Hypothesis 5b: Exhaustion mediates the link between relationship conflict
and contextual performance
Relationship conflict with coworkers might eventually wear employees down
with a steady onslaught of withdrawal behaviors and consequently they develop
negative perception of their organizations as well as of the work activities being
performed in it and are no more concerned for their organizations (Boz et al., 2009) as
relationship conflict makes the work environment more threatening. They become
overcritical of the management, co-workers and superiors (Schaufeli and Buunk,
2003; Schaufeli and Enzmann, 1998) which relates more specifically to low
contextual performance and increased turnover intentions (Bakker, Demerouti, and
Verbeke, 2004). This may result in withdrawal behaviors where the individuals may
think of alternative opportunities as their loyalty towards their organization may
diminish. Campbell et al, (2013) contend that psychological withdrawal (i.e.,
decreased commitment to the organization) is one of coping mechanism to preserve
remaining resources and to protect from further damage. Consistent with the COR
theory, relationship conflict may spiral into serious losses in the form of exhaustion
such as loss of energy and capacity to perform as well as stronger desire to leave the
organization in an attempt to preserve their existing resources. Thus, we hypothesize
that;
Hypothesis 5c: Exhaustion mediates the link between relationship conflict and
turnover intentions
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Employees are more likely to undergo tension, stress and irritability when they
face relationship tensions at workplace and they lose their interest in work (Kacmar et
al., 2012; Van der Kam et al., 2014), which indicates that relational rifts may lead to
cynicism which is related to unwillingness to expend effort (Schaufeli & Salanova,
2014). Burned-out employees can no longer conserve appropriate or required
threshold of resources required to perform job tasks. Relationship conflict with peers
tend to be psychologically and physically draining, hindering or preventing an
individual‘s ability to cope with work demands and leading to the feeling of being
overwhelmed.
Hypothesis 6: Relationship conflict is positively related to cynicism.
Relationship rifts divert focus from core tasks (Kacmar et al., 2012) hence
individuals may experience disengaged attitude towards work or in other words
exhibit cynicism. Cynicism is characterized by de-motivation and withdrawal from
the work (Bianchi, Schonfeld, and Laurent, 2015). According to Bakker et al., (2004),
cynicism ―represents an extensive and intensive reaction in terms of an emotional,
cognitive, and behavioral abandonment of the work‖. Researchers are of the view that
people who experience relationship conflict show symptoms of cynicism, withdraw
themselves physically or psychologically from workplace and undermine the effort of
others (Van der Kam et al., 2014; Jehn 1995). In doing so, their work performance
further plummets (Schaufeli and Salanova, 2014). Evidence shows that
disengagement from work leads to poor task performance (Demerouti et al., 2014).
Work becomes worthless having lost its meaning and cognitive abilities such as
memory and focus might be impaired and thinking becomes inflexible, mechanized
and detached (Schaufeli and Buunk, 2003). Employees may reduce personal
involvement in work activities due to lack of interest, hence, relationship conflict is
predicted to have more negative impact on task performance through its impact on
cynicism.
Hypothesis 6a: Cynicism mediates the link between relationship conflict and
task performance
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Employees encountering relational tensions may disrupt the normal
functioning of their colleagues as the phenomenon is contagious and may demotivate
the coworkers as well (Rakovec-Felser, 2011). Relationship conflict may crop up as
unconcern for others to complicate individuals‘ interactions at workplace, leading
them to feel lack of psychological coping resources needed to sustain social demands
other than core duties at workplace. This may lead to withholding of social support
resources as they are less likely to interact more productively which may in turn affect
their contextual performance as employees are no longer concerned about their own
work and that of the people around them.
Hypothesis 6b: Cynicism mediates the link between relationship conflict and
contextual performance.
Cynical employees exhibit negative attitude coupled with lack of concern for
their organization and tend to become less loyal to their organization (Campbell et al.,
2013), and tend to withdraw from aversive work environments (Schaufeli, Bakker,
and Van Rhenen et al., 2009). Taris, Schreurs, and Van-Silfhout (2001) found that
relationship tensions among coworkers were associated with psychological
withdrawal such as cynicism, loss of commitment and turnover. Hence, relationship
conflict may lead to erosion of resources in the form of cynicism as it erodes their
dedication and involvement towards work, and owing to inadequate resources to cope
with the stressful social environment, they are more likely to evade the aversive
workplace in order to prevent successive depletion of resources-that is, making up
their mind to quit. This may encourage them to seek workplaces they feel more suited
to as the overall negative environment may reduce their attachment to their
organization.
Hypothesis 6c: Cynicism mediates the link between relationship conflict and
turnover intentions
Interpersonal strain refers to ―a specific disengagement reaction from all
relevant interpersonal relationships at work.‖ This strain in relationships is marked
with indifferent, harsh and reserved behavior towards other people (Borgogni et al.,
2012). Relationship conflict may lead to interpersonal strain at work as it may evoke
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feelings of unconnectedness since individuals develop negative perceptions of the
people with whom they are in conflict with (adversaries), which add to their fears of
being socially excluded. Interpersonal strain at work arising from relationship conflict
creates tension and frustration in individuals. They become interpersonally estranged,
isolated and alienated from other people (Consiglio, 2014; Laursen and Hafen, 2010).
Relationship conflict induces strain among individuals whereby they start
avoiding each other, leading to an increased tendency towards social isolation or
interpersonal strain at work. Hence, it is hypothesized that;
Hypothesis 7: Relationship conflict is positively related to interpersonal
strain at work.
Rakovec-Felser (2011) argues that when employees do not experience
reciprocity in their relationships at interpersonal level, they may undergo
interpersonal strain owing to the fact that as a result of relationship conflict, they may
not be in a position to be more supportive towards their colleagues which may ensue
as an attempt to avoid negative social interactions. Avoiding the difficult coworker
may make it challenging to effectively cope with the work demands, as limited social
contact may lead to fewer opportunities to interact in a more effective way, thus
contributing to poor performance. Avoiding the difficult coworker may make it
challenging to effectively cope with the work demands, as limited social contact may
lead to fewer opportunities to interact in a more effective way. Hence we formulate
that:-
Hypothesis 7a: Interpersonal strain at work mediates the link between
relationship conflict and task performance.
Fernet et al., (2010) argued in their study that high quality interpersonal
relationships are crucial in organizational setup to mitigate the effects of burnout. The
psychological discomfort, tension and isolation produced by relationship conflict
prevent individuals to engage in coordinated activities (Jehn, 1995). This may lead to
behaviors such as seeking to distance oneself from the others and pulling back from
coworkers, thus avoiding potentially harmful social contexts and stressful situations
as a distraction from negative events and to protect oneself against negative feelings.
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This may result in impoverished social support thereby limiting their access to
resources such as knowledge and support of their coworkers and the benefits that
might otherwise be gained. This may in turn affect their contextual performance. This
may become counterproductive since positive relationships at workplace are of
paramount importance for smooth functioning (Consiglio, 2014). Taken together, we
expect that contextual performance of the employees is likely to suffer as a result of
relationship conflict and ensuing strain at work. Hence we formulate that;
Hypothesis 7b: Interpersonal strain at work mediates the link between
relationship conflict and contextual performance
This contributes to an increase in threat level in the environment and escape
may seem more appropriate so as to avoid the loss and further depletion of valued
resources. Moreover, due to breakdown in social connectedness as a result of
relationship rifts, the workplace does not remain supportive since loss of social ties
transforms into detached behavior at work that adds to the overall negative image of
the working environment, thus making loss spirals where initial loss of relationships
leads to social seclusion (interpersonal strain at work), consequently threatening the
belongingness to the workplace. This in turn makes their working environment more
stressful and somber and may lead to desire to disengage and exit their organization
altogether. Harris, Harvey, and Kacmar (2011) state that relationship conflicts among
coworkers is a potent source of stress and frustration in the workplace, and owing to
their unpleasant nature, employees tend to engage in behaviors that may reduce the
presence of such events. Thus, we formulate that;
Hypothesis 7c: Interpersonal strain at work mediates the link between
relationship conflict and turnover intentions
The relationships between relationship conflict and different facets of
workplace subjective well-being and their impact on task performance, contextual
performance and turnover intentions have been shown in Figure 3.2.
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Route –II- Resource Depletion Process
Figure: 3.2: Relationship Conflict, Burnout and Job Performance Model
(Source: Compiled by Researcher)
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3.8 Complete Model
The COR theory (Hobfoll, 1989, 2001) guides the theoretical model of this
study. We expect task conflict and relationship conflict behave differently in difficult
non-routine jobs such as telecom engineering in our case. This is based on the
theoretical justification presented by Solansky et al., (2014) in which they state,
―focus of a task conflict is the actual problem at hand, whereas the focus of a
relationship conflict is on the actual people and who they simply are.‖ More
precisely, the resource investment/acquisition principle of the COR theory explicates
the relationships between task conflict, workplace subjective well-being (work
engagement and job satisfaction) and task/contextual performance and turnover
intentions of employees. The primacy of loss principle of the COR theory explains the
link between relationship conflict, different dimensions of job burnout and
task/contextual performance and turnover intentions.
The first path of the theoretical model has been developed on the basis of
resource investment/acquisition principal of the COR theory. The basic tenet of the
COR theory is that individuals are motivated to invest and acquire resources (Hobfoll,
2001). Conflict researchers (Lu et al., 2011; De Drue, 2008; Tjosvold, 2008; Jehn,
1995) argue that task conflict leads to creativity and innovation in individuals as a
result of ideas exchange process. As discussed above, resources foster personal
growth and learning and some of the consequences of task conflict are creativity and
innovation (Kurtzberg & Mueller, 2005), we can assume that task conflict may
become a resource.
Task conflict entails exchange of cognitive resources and is said to be related
to positive psychological states thereby leading to work engagement (Chen et al.,
2011). Laursen and Hafen (2010) suggest that constructive conflict leads to improved
well-being of individuals since it provides a platform for self-expression and
collaboration. In line with the corollary of the COR theory which states that
individuals who possess more resources are less vulnerable to resource loss and are
more likely to gain resources than their counterparts with few resources (Westman et
al., 2004), the linking mechanism between task conflict and individual outcomes can
be understood as it is hypothesized that employees invest their cognitive resources in
order to gain more resources which in turn may lead to positive outcomes in
individuals. On the basis of these arguments, it may be assumed that task conflict may
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lead to work engagement or job satisfaction since task conflict provides an
opportunity to employees to discuss their task-related issues, express their concerns
and find a better solution (Jehn, 1995, 1997).
Work engagement has been found to be positively related to job performance
(Shimazu et al., 2012; Reijseger et al., 2012, cited Hakanen et al., 2008; Halbesleben
& Wheeler, 2008; Demerouti & Schaufeli, 2009). Since engaged employees enjoy
their jobs (Demerouti & Schaufeli, 2009), hence, under the assumption that task
conflict leads to work engagement of employees, this relationship will have positive
impact on task performance and contextual performance and negative impact on
turnover intentions of employees.
Similar relationship may be observed between task conflict and task
performance, contextual performance and turnover intentions of employees through
mediation of job satisfaction. In the backdrop of the COR theory, resources motivate
employees to perform better and that satisfied employees reciprocate their sense of
satisfaction by engaging in prosocial behaviours that are beyond their prescribed job
responsibilities (Podsakoff et al., 1996). This can be inferred that task conflict can
have more pronounced effect on job performance (task and contextual) and turnover
intentions through its positive impact on job satisfaction.
The second route of the theoretical frame work has been developed on the
basis of the resource depletion process of the COR theory. The COR theory assumes
that individuals strive to obtain and sustain the resources they value (Hobfoll,
2001).However, resource loss has primacy over resource gain. Stress is likely to occur
when valued resources are threatened or lost, are insufficient and when return on
resource investment does not yield anticipated results. It is theorized in the present
study that relationship conflict is a loss of social ties at workplace. This loss may have
negative impact on individual outcomes. Moreover, based on the ―loss begets loss‖
paradigm of the COR theory, it is hypothesized that loss of social ties as a result of
relationship conflict leads to further loss of resources in the form of job burnout which
in turn negatively impacts individual‘s job performance and positively impacts
turnover intentions.
Relationship conflict may have negative repercussions for employees since it
disrupts individuals‘ ability to concentrate on work (Lu at al., 2011), induces stress,
frustration and tension (Rakovec-Felser, 2011). On the basis of previous research and
COR theory, it is expected that relationship conflict may give rise to job burnout
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which may impact task performance and contextual performance negatively and
turnover intentions positively since relationship conflict has been said to be related to
stress and withdrawal behaviors in employees (De Drue, 2008; Jehn, 1995). The
present study considers different dimensions of burnout which are exhaustion,
cynicism and interpersonal strain at work in order to gauge the differential impact of
these dimensions.
The relationships between task conflict, relationship conflict, different facets
of workplace subjective well-being and work behaviors have been shown as follows:-
Figure: 3.3: Conflict, Well-being and Job Performance Model
(Source; Compiled by Researcher)
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3.9 Summary
This chapter explicated the interrelationships among the study variables with
the help of relevant literature as per following details:-
Table: 3.1: Summary of Chapter
Section Details
1
The chapter first focused on the direct relationships between predictor
variable- task conflict and outcome variable-task/contextual
performance and turnover intentions.
2
Further, it proposed two mediators i.e., work engagement and job
satisfaction as two plausible mediators between the link of task conflict
and outcome variables.
3
The relationships have been explained in the backdrop of resource
investment/acquisition principle of the Conservation of Resources
(COR) theory. This has been depicted by first model of the study
(Figure 3.1).
4
In the second model, the chapter elaborated the direct links between
relationship conflict and outcome variables-task/contextual performance
and turnover intentions. The study proposed job burnout as a mediator
in the link between relationship conflict and outcomes. The three
dimensions of job burnout-exhaustion, cynicism and interpersonal strain
at work were proposed to distinctively mediate the link between
relationship conflict and outcomes. These relationships were explained
in the backdrop of resource depletion (primacy of loss) principle of the
COR theory, shown by the second model of the study (Figure 3.2)
5 The concluding section presented the complete model of the study, thus
combining the afore-mentioned paths (Figure 3.3).
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Chapter 4
Research Methodology
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Research Methodology
This chapter outlines the overall design of the research. It includes the
underlying research philosophy, research approach, research design/strategy, sample
design, data collection and tools and statistical design of the study. This chapter also
includes variables, their operationalisation as well as scaling schemes of the measures.
This chapter concludes with the data analysis techniques used in this research.
The methodology of the present research is based on ‗onion‘ process
suggested by Saunders, Lewis, and Thornhill (2012, p.126). The layers of onion are-
research philosophy, research approach, methodological choice (research design),
strategy, time horizon, data collection techniques and analysis procedure.
Figure: 4.1: Layers of Onion
(Source: Saunders, Lewis, and Thornhill, 2012, p.128)
4.1 Research Philosophy
Research philosophy encompasses development of knowledge and the nature
of that knowledge (Saunders, Lewis, and Thornhill, 2012, p.127). Research
philosophy underpins important assumptions about the way we perceive things. On
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the basis of these assumptions we choose out research strategy and methods. Hence, it
becomes imperative for a researcher to know the philosophical underpinnings of the
research strategy and process he/she is going to adopt. In this regard, ontology and
epistemology are two components of research philosophy that guide the choice of
research process to be undertaken (Saunders et al., 2012, p.129).
Ontology is related to nature of reality, means what constitute reality, and
inquires ‗what is‘, whereas epistemology refers to ―how knowledge can be created,
acquired and communicated‖, in other words ‗what it means to know‘ (Scotland,
2012). There are two dimensions of ontology; objectivism and subjectivism.
Objectivism or realism holds that phenomena/object exist in the real world
independently of the social actors concerned with their existence (Saunders et al.,
2012, p. 131; Wahyuni, 2012) and their meaning reside in the object, not in the mind
of the researcher and it is the objective of the researcher to derive that meaning
(Scotland, 2012). ―Subjectivism states that social phenomena are created from the
perceptions and consequent actions of the social actors (Saunders et al., 2012, p.
131).‖ It varies from person to person (Scotland, 2012).
Epistemology is concerned with the nature of knowledge and is further
subdivided into three viewpoints, namely positivism, realism, and interpretivism
(Wang & Nasr, 2010). Positivist view is derived from natural science and is related to
testing of hypothesis developed from existing theory (deductive approach) through
measurement of observable social realities. Positivists assume that social world exists
objectively and externally, and knowledge is authentic if it is derived from the
observation of this external reality and the end product is a law-like generalization
(Saunders et al., 2012, p. 134). Positivist paradigm employs quantitative methods such
as surveys, experiments and statistical analysis. Realism is similar to positivism in the
sense that it also presumes a scientific approach to the development of knowledge.
Realism holds that what we sense is reality which is quite independent of mind
(Bryman & Bell, 2011).
Interpretivism undertakes a different stance and it requires social scientists to
understand the subjective meaning of the social actions. According to this view, such
research strategy should be employed that respects the difference between individuals
and social entities and the objects of the natural sciences. Interpretivism paradigm
employs qualitative methods such as case studies, interviews, focus group discussion
and naturalistic observation (Tuli, 2011; Scotland, 2012). Qualitative methodologies
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follow inductive approach since these are oriented toward discovery and
understanding of a social phenomenon and rely on personal contact between the
researcher and the group under study over a period of time (Tuli, 2011).
Pragmatism is another branch of research paradigm that unlike positivist and
interpretivist philosophies, view research philosophy as a continuum, rather than two
opposite poles (Wahyuni, 2012). According to pragmatists, objectivism and
subjectivism are not mutually exclusive; since no single point of view can provide the
entire picture and that there may be multiple realities. Pragmatism holds that the most
important determinant of ontology and epistemology is the research question (Bryman
& Bell, 2011; Wahyuni, 2012).
Following self-explanatory figure cited from (Tuli, 2011) explains building
pillar of a research on the basis of which a study is developed;
Figure: 4.2: Foundation of Research
(Source: Tuli, 2011)
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Insights from different research paradigms have helped to choose the
ontological and epistemological basis of the current study. Since the researcher
believes in this study that reality is external and objective and remains same for every
individual, and most of the realities can be measured through objective methods such
as surveys and questionnaires, hence, ontological stance of this study is objectivism.
Corresponding to objectivist ontology, the epistemological stance of the study is
positivism since positivist epistemology advocates scientific investigation based on
quantifiable data extracted from a sample of a large population. Likewise, the aim of
the study is to measure the effect of task conflict and relationship conflict on work
behaviors such as task performance, contextual performance and turnover intentions.
Different indicators of workplace subjective well-being have been proposed as
mediators between direct relationships.
4.2 Research Approach
Objectivism ontology and positivism epistemology further guided the research
approach and strategy of the study. There are two approaches to research namely
deductive approach and inductive approach. Deductive approach follows an existing
theory on the basis of which hypotheses are developed whereas inductive approach
explores the data and theory is developed on the basis of data analysis (Saunders et
al., 2012, p. 144). In deductive research, data is often collected through surveys,
questionnaires, and interviews etc, whereas in inductive research, data is generally
collected through interviews, observations, case studies and focus group discussions
(Babbie, 2012).
Deductive research is objective in nature and can be replicated whereas
inductive research owing to its subjective nature is very difficult to replicate. The
study aims to seek plausible truth that carries real existence and can be studied
independently of the researcher (Robson, 2011). The present study follows the
deductive approach due to the fact that in this approach hypotheses are developed on
the basis of existing theory i.e., the Conservation of Resources theory (Hobfoll, 1988,
1989), and the research aims to provide an explanation for the association between
interpersonal conflict, employees well-being and their job performance. The COR
theory takes the form of a deductive argument that lays the foundation of
development of different research hypotheses.
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4.3 Research Design and Corresponding Strategy
The research design is a master plan to accomplish a research (Greener, 2008).
It translates ontological and epistemological principles into guidelines that provide a
roadmap to research (Tuli, 2011). There are different research designs that can be
used to carry out a research such as mono methods such as quantitative design or
qualitative design, and multiple methods research design (Saunders et al., 2012, p.
161). ―Quantitative research examines relationships between variables, which are
measured numerically and analysed using a range of statistical techniques‖ (Saunders
et al., 2012, p. 162). This design is associated with experimental and survey research
strategies. Survey research is carried out through questionnaires, structured interviews
or observations (Saunders et al., 2012, p.163).
Qualitative research considers participants‘ meanings and their
interrelationships using multiple data collection techniques and analytical procedures.
Data collection is non-standardised in order to allow flexibility in questions or
procedures. Qualitative research is associated with variety of strategies such as action
research, case study, ethnography, grounded theory and narrative research (Saunders
et al., 2012, p. 163). ―Multiple methods research design may use either a deductive or
inductive approach or likely to combine both‖ (Saunders et al., 2012). Hence, this
design may include a combination of quantitative research design as well as
qualitative research design.
Objective ontology and positivist epistemology advocate a quantitative
research design, therefore, survey strategy has been selected for the study. It is
associated with deductive approach and is a popular and common strategy in business
and management research due to the fact that surveys allow the collection of a large
amount of data from a sizeable population that is too large to study directly in a cost
effective manner. Moreover, it provides the opportunity to conduct a quantitative
analysis using descriptive and inferential statistics (Mouton 1996:p. 232; Saunders et
al., 2012: p.176).
A descriptive survey is a source to obtain information from a sample of
population through self-report. The obtained results can be used to explore and
understand relationship among the study variables and thus help produce models that
can be generalized to the population. Survey research is conducted as a part of non-
experimental fixed designs and can be used for descriptive, explanatory, or
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exploratory purposes (Robson, 2011). This study is explanatory in nature, whereby
the emphasis is on studying a situation or problem in order to explain the relationships
between the study variables relying on the numerical evidence to draw conclusions.
The quantitative approach will enable this study to test task conflict, relationship
conflict, different facets of employee subjective well-being at work and their work
behaviors (task and contextual performance and turnover intentions) in an effective
manner and infer generalization about the effect of task conflict and relationship
conflict. Furthermore, the purpose of this explanatory research is to understand the
underlying mechanisms linking conflict types and work behaviors. Therefore, survey
strategy was considered more appropriate as it helps provide insight into perceptions,
attitudes, and behaviors of individuals in addition to organizational practices and
policies (Baruch and Holtom, 2008). Moreover, a standardized survey can be very
objective and has fewer biases due to high validity and reliability.
The study is cross-sectional in nature. Cross-sectional study enables a
researcher to collect data from various segments of a population at a single point in
time (Saunders et al., 2009: p.155). The cross-sectional design is recommended in
studies where there is no time ordering among the variable. The problem with cross-
sectional design is that the causality among variables cannot be established since it is
devoid of features of experimental design such as internal validity (Bryman & Bell,
2011). In contrast to cross-sectional studies, longitudinal design is a correlational
design which measures responses over a period of time repeatedly. It allows the
analysis of responses to change over time (Zikmund, Babin, Carr, & Griffin, 2009,
p.197). As the purpose of longitudinal design is to explore continuity of response and
observe the change over a period of time, the more suitable design for the present
study is cross-sectional since it provides a snapshot of relationships among constructs
of interest.
4.4 Sample Design
This study followed Zikmund et al (2009) sampling approach for a
quantitative study which allows for findings to be generalized to the population. The
sampling process involves various steps starting from defining the target population to
the selection of sampling frame (Zikmund et al., 2009, p. 390). It also involves
decisions about selection of either probability or non-probability sampling technique.
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Then the sample size is determined and sample units are selected. Following is the
detail of each step.
4.4.1 Target Population
The target population refers to the group of elements (households, housing
units, parts of an organization) to which the researcher wants to make
inference. Target population of the study includes telecom sector of Pakistan. This
sector includes five companies namely Ufone, Telenor, Mobilink, Warid, and Zong.
Telecom sector has been selected because it is one of the rapidly growing sectors of
Pakistan and since this sector provides a challenging environment to the employees,
any phenomenon which can contribute to the well-being and performance of
employees is crucial to study (Shahzad et al., 2011). Moreover, the study aimed to
research on individuals‘ attitude or behaviors and their perceptions of task and
relationship conflict in technical jobs, hence, telecom sector seemed to be an
appropriate choice for investigating these phenomena.
4.4.2 Sampling Frame
Sampling frame refers to a list of representative individuals within a target
population from which the sample can be drawn (Zikmund et al., 2009, p. 391). The
sampling frame for this study includes telecom engineers of Ufone, Telenor,
Mobilink, Warid, and Zong. Unit of Analysis are employees (Telecom engineers) of
Telecom sector. Telecom engineers have been chosen for the purpose of study
because they have non-routine complex jobs as their main domain is service design
and analysis and they perform highly specialized tasks. For reference, a detailed job
description of telecom engineers has been placed at Appendix L. The intended sample
of this study was 650 individuals/employees of the cellular service providing
companies.
4.4.3 Sampling Technique and Methods
There are different techniques for the selection of a sample. The two most
common techniques are probability and non-probability sampling techniques
(Robson, 2011). Non-probability sampling allows the researcher to select the sample
based on his/her subjective judgement. It is also used in studies where the researcher
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cannot specify the sampling frame and the issue of sample size is fuzzy.
Generalizations are made to the theory instead of to the population (Saunders et al.,
2012, p. 262). However, in probability sampling, every individual has an equal chance
of being selected (Zikmund et al., 2009, p. 395) and this sampling is generally
associated with survey-based research design where the researcher is supposed to
make inferences from the sample about a population to answer research questions and
meet objectives of the study (Saunders et al., 2012, p.261). A probability sampling
technique has been considered as the most appropriate sampling method for this
research.
The sampling technique employed in this study is proportionate stratified
random sampling because this study involves telecom engineers from different
telecom companies namely Ufone, Telenor, Mobilink, Warid, and Zong; therefore,
stratified sample design was used where each cellular service provider company was a
strata. Robson (1993) argues that the sampling theory supports stratified random
sampling because the means of the stratified samples are likely to be closer to the
mean of the population, hence the sample results will more precisely depict the
characteristics of the overall population (Leary, 1995). Consequently, the sample in
this study has been disaggregated by Telecom Company to address the fact that there
is a wide variance in the number of telecom engineers within each cellular service
providing company.
4.4.4 Sample Size
Sample size is an important determinant of the statistical strength of a study‘s
findings. The sample size of the study has been estimated from the table for sample
size determination (Krejcie & Morgan, 1970). The sample size of the current study is
370 individuals calculated from the table since the population size is approximately
10,000 telecom engineers in five cellular service providing companies, hence the
corresponding sample size mentioned in table is 370. However, Saunders et al., (2012,
p.265) suggest that sample size is always a matter of judgement as well as calculation,
therefore, a sample size of over a few hundred respondents was considered
appropriate. Hence, following Saunders et al.‘s recommendation, the questionnaires
were hand delivered to 650 telecom engineers in order to have better response rate
and in response 528 filled questionnaires were obtained.
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Table: 4.1: Sample Size
Company N %Age n Responses
Warid Telecom 1259 13 85 68
Zong 2065 20 130 118
Mobilink 2277 23 149 119
Ufone 2790 28 182 125
Telenor 1620 16 104 98
Total 10011 100 650 528
Note: N is total number of telecom Engineers in telecom sector of Pakistan.
n is stratified sample of population.
4.4.5 Data Collection
Primary data has been collected through a self-administered questionnaire
because the questionnaire can be administered to a large number of individuals
simultaneously in a lesser time and it provides a comprehensive view of the attitudes,
beliefs, and values of the large population with a smaller sampling-range error
(Cargan, 2007).
Questionnaire is a very flexible tool of data collection and generally there are
two ways of delivering questionnaire, one is personally and another is by mail
(Nicholas & Bousmaha, 2001). In this study, paper questionnaires have been
administered personally so as to increase the response rate. Questionnaires were
administered in English language as the sample of the study comprised of telecom
engineers and they expressed their ease with English language (Appendices D to G).
Personally administered questionnaires have their merits and demerits. On the
positive side, they help respondents in understanding the context and content of the
questionnaire and clear any ambiguity. Response rate is better as compared to other
data collection tools. Demerits of the questionnaire are social desirability issue and
researcher‘s bias. Social desirability refers to ‗tendency of respondents to answer
questions in a manner that would be viewed favorably by others (Fisher, 1993). These
issues have been handled in such a way that after distributing the questionnaires to
respondents, the researcher collected the questionnaires later on so that individuals
would not feel any social pressure and provide bias free responses. Moreover, task
and contextual performance of the sample was rated by their immediate supervisors.
The study used all standard questionnaires from relevant research.
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The cover page of the questionnaire was related to obtaining the informed
consent of the respondents and to ensure their privacy and confidentiality as the
respondents were not required to reveal their identities. Participation in the study was
voluntary. The cover page also explained the purpose of the study. The respondents
were given instructions for completing the survey. Demographic information was
sought at the end of the survey. The paper questionnaires were hand-delivered to 650
telecom engineers and 35 immediate supervisors. Approximately, 2 weeks after the
initial survey distribution a first reminder with another copy of the survey was sent to
those participants who had not yet submitted their responses. After one week from the
first reminder, a second reminder was sent, and as a result 528 filled questionnaires
were returned by the telecom engineers. The response rate was 81% approximately.
However, out of these 528 questionnaires, 20 were discarded due to incomplete data
and similarity of responses across questionnaires. Consequently, 508 usable
questionnaires were retained for further analysis, thus reducing the response rate
to78% approx. Supervisor-rated task and contextual performance measures were
obtained from the respective supervisors. The two dimensions of job performance
help provide holistic view of the outcomes of individuals. Reilly and Aronson (2009)
contend that ―contextual performance explains a unique variance in supervisors
ratings of employee overall performance, beyond that explained by task
performance‖. All supervisors provided the data on task/contextual performance of
their employees. A master list of the respondents was prepared containing the
identification code and this code was placed on each questionnaire. The supervisor‘s
questionnaire also had the corresponding identification code. The managers‘ and
supervisors‘ questionnaires were matched using these identification codes.
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Table: 4.2: Various Phases of Data Collection
Sr No Data Collection Phase Date
1 Questionnaires alongwith consent form
delivered to 650 telecom engineers and 35
supervisors
5th
January, 2015
2 528 telecom engineers responded 10th February, 2015
3 35 supervisor responded 5th
February, 2015
4 20 incomplete questionnaires were
discarded
15th
February, 2015
5 Data of respondents and supervisors
matched
78% Approx
4.5 Survey Design
Survey questionnaire serves as a cost effective and efficient tool for data
collection. In this study, the questionnaires were distributed with a covering letter
which explained the purpose of the study and ensured the confidentiality of the
responses and anonymity of the participants. It also ensured the respondents that their
participation was voluntary and that they can withdraw their participation at any time
during study. The respondents were explained that the questionnaire was intended to
measure their perceptions of the workplace conflict and their attitudes and behaviors.
Moreover, the participants were provided with the contact information of the
researcher so that they may contact in case of any relevant inquiry and clarification.
The respondents‘ questionnaire consisted of four sections related to the
constructs of study. The survey totaled 48 questions; nine demographic questions and
39 scaled items. Basic instructions were incorporated at the beginning of each section
to make it more convenient for the respondents. The sequence of the different
measures was deliberately randomized so as to keep intact the interest of the
participants and to avoid potential bias due to response consistency. Demographic
information such as name (optional), age, department, level of education, gender and
marital status was requested at the end of the questionnaire. Supervisors rated the
task/contextual performance of the respondents and this questionnaire consisted of 13
items, 5 items for task performance and 8 items for contextual performance.
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All the questions were measured on a 5-point Likert scale because this scale
offers the flexibility to the respondents to make a decision on their level of agreement
with the given statement. Likert scales are highly preferred in social science research
since they provide statistically significant results (Cooper & Schindler, 2006).
4.6 Tools / Questionnaires
Self-rated (i.e., Task conflict, relationship conflict, work engagement, job
satisfaction, job burnout, and turnover intentions), and supervisor-rated (i.e., task
performance and contextual performance), scales have been used to measure these ten
constructs.
4.6.1 Interpersonal Conflict
Task conflict and relationship conflict have been measured by scale adapted
from Jehn‘s (1995) as this scale has been widely used in conflict research. (Martínez-
Corts, 2011; Curseu , 2009; Ayoko & Pekerti, 2008; Gamero et al., 2008; Langfred,
2007; Ayoko, 2007; Medina et al., 2005; Passos & Caetano, 2005; Jehn et al., 1999)
4.6.2 Task Conflict
Jehn‘s (1995) four items scale has been adapted to measure task conflict.
Examples item is; ―How frequently are there conflicts about ideas between you and
your coworkers?‖ The self-report items are anchored on a 5-point Likert scale ranging
from 1 = ―None‖ and 5 = ―A lot‖. The Cronbach‘s α for task conflict is .81.
Participant responses have been averaged to form single scores for task conflicts.
4.6.3 Relationship Conflict
Jehn‘s (1995) four items scale has been adapted to measure relationship
conflict. Example item is; ―How much friction is there among you and your
coworkers?‖ The Cronbach‘s α for relationship conflict is 0.91. Participant responses
have been averaged to form single scores for relationship conflicts.
4.6.4 Workplace Subjective Well-being
Three indicators of workplace subjective well-being - work engagement, job
satisfaction, and job burnout have been used.
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4.6.4.1 Work Engagement
Work engagement has been measured through shortened version of the
Utrecht Work Engagement Scale (UWES; Schaufeli & Bakker, 2010;Schaufeli et al.,
2006; Schaufeli et al., 2002, Schaufeli et al., 2008) that includes a subscale for each of
the three engagement dimensions: vigor, dedication and absorption and this
instrument has been validated in several countries (Airila et al., 2014; Bakker et al.,
2014; Mäkikangas et al., 2013Shimazu et al., 2012; Bakkar, 2010; Balducci et al.,
2010; Seppälä, 2009; Xanthopoulou et al, 2009;Shimazu et al., 2008; Schaufeli,
2008;Bakker & Demerouti, 2008). Schaufeli et al., (2006) shortened the original 17
items scale to a 9 item scale to measure work engagement and reported its reliability
coefficient greater than 0.8. All items of the measure are scored on a 5-point
frequency rating scale which ranges from 1(never) to 5(always). Example items are:
―At my job, I feel strong and vigorous‖ (vigor); ―I am enthusiastic about my job‖
(dedication); ―When I am working, I forget everything else around me‖ (absorption).
However, the exploratory factor analysis emerged with one-factor in current study.
Sonnentag (2003) also reported one-factor structure of work engagement and used an
overall scale with a high reliability (Cronbach‘s α = 0.86). Later on, Hallberg and
Schaufeli, (2006) reported in their study the equivalence of one-factor model and
three-factor model and also suggested that composite measure can be used.
Participants‘ responses of the subscales have been averaged to form the total score for
work engagement. This cumulative scoring has been done on the recommendation of
Schaufeli (2012) who suggests that ―the three underlying dimensions are moderately
strong and positively related so that a total score can also be used as an overall
indicator of work engagement.‖
4.6.4.2 Job Satisfaction
Job satisfaction has been measured through a 3-items scale developed by
Cammann, Fichman, Jenkins, and Klesh's (1983). This scale has been used in several
studies (Way et al., 2010; Valentine & Fleischman, 2008; Bowling & Hammond,
2008; Ashforth et al., 2007; Saks, 2006; Gruman et al., 2006; Barak, 2001; Duffy et
al., 2000). One of the items was reverse scored (‗‗In general, I don‘t like my job‘‘)
with the other two items being scored normally (‗‗All in all, I am satisfied with my
job‘‘; ‗‗In general, I like working here‘‘). The measure has been assessed on a five-
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point scale (ranging from 1 = strongly disagree, to 5 = strongly agree). The
Cronbach‘s α for this scale is 0.83. Participants‘ scores were averaged to form single
score.
4.6.5 Job Burnout
The two dimensions (exhaustion, cynicism) of job burnout were measured
through the Maslach Burnout Inventory-General Survey (MBI-GS; Schaufeli,
Maslach, Leiter, & Jackson, 1996; Borgogni et al., 2012). The third dimension i.e.,
interpersonal strain at work was measured by 6-items scale developed by Borgogni
et al., 2012. MBI-GS scale has been widely used in research(Consiglio et al., 2013;
Leiter et al., 2013;Maslach et al., 2012; Chirkowska-Smolak, & Kleka, 2011;
Mäkikangas, 2011; Schaufeli et al., 2009; Myendeki, 2008; Langballe et al., 2006;
Kitaoka-Higashiguchi et al., 2004; Bakker et al.,2002;. Schutte et al., 2000; Taris et
al.,1999). The MBI scale is the first standardized instrument designed to measure
burnout. It has been reported that the MBI was used in more than 90% of burnout
studies by the end of 1990s (Bianchi et al.,2015). All items of each dimension are
scored on a 5-point frequency rating scale ranging from 1 (―never‖) to 5 (―always‖).
High scores are indicative of burnout. Participants‘ responses of the subscales were
averaged to form their respective single scores.
4.6.5.1 Exhaustion
Exhaustion was measured by five items (α = 0.80). Example item is: ―I feel
emotionally drained from my work‖.
4.6.5.2 Cynicism
Cynicism was measured by five items (α = 0.83). Example item is: ―I have
become more cynical about whether my work contributes anything‖.
4.6.5.3 Interpersonal Strain at Work
Interpersonal strain at work was measured with six items (α = 0.86),
(Consiglio et al., 2013; Borgogni et al., 2012; Ahola et al., 2006). Example item is:
―At work, I feel more comfortable keeping distance from others‖.
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4.6.6 Task Performance
Supervisor rated in-role or task performance has been measured with 5 items
from Williams and Anderson (1991) scale. Cronbach‘s α is 0.81. A sample item is,
‗This subordinate adequately complete(s) assigned duties.‘ The measure uses a 5-
point scale that ranges from 1 (‗do not agree at all‘) to 5 (‗strongly agree‘). The
reliability and validity of this scale has been demonstrated in several previous studies
(e.g. Podsakoff et al., 1995, 1996; Williams & Anderson, 1991). Individuals‘ score
were averaged to form their single scores.
4.6.7 Contextual Performance
Supervisor rated contextual performance was measured with scale developed
by Eisenberger et al., (2010). This is an 8 items scale and a 5-point likert type
response format has been used that ranges from 1 (strongly disagree) to5 (strongly
agree). A sample item is, ―This employee looks for ways to make (name of the
organization) more successful‖. Cronbach‘s α is 0.87. Participants‘ scores were
averaged to form single score.
4.6.8 Organizational Turnover Intentions
Organizational turnover intention has been measured from Meyer et al.‘s
(1993) three-item scale (e.g., I often think of quitting the organization). The measure
has been validated in several studies (Chang, Chi, & Miao, 2007; Paré & Tremblay,
2007; Hussain & Asif, 2012; Mauno et al., 2014; Thanacoody, Newman, & Fuchs,
2014). Cronbach‘s α for the scale was 0.77. The measure uses a 5-point scale
(1=strongly disagree to 5=strongly agree).
4.7 Common Method Variance
The self-report measures are plagued with common method bias or common
method variance. This variance is caused when the selected measurement technique or
source creates systematic or random error which can lead to superfluous relationships
among the study constructs (Podsakoff, MacKenzie, Lee, and Podsakoff, 2003). Other
problems include consistency artifacts and social desirability issues. Possible remedial
actions suggested by Posakoff and Organ (1986) are collecting data from different
sources, reordering of scale items to avoid consistency motif and Harman‘s one-factor
129
test (1976) to detect common method variance. These techniques have been used to
detect common method bias. Harman‘s one-factor test involves conducting an
exploratory factor analysis on all the study constructs and then unrotated solution is
examined to determine the number of factors that account for the variance in study
variables. If one factor emerges from the analysis or one factor accounts for most of
the covariance among construct, common method bias is an issue.
4.8 Survey Pre-Testing
The questionnaire was pre-tested in two steps with a representative group of
respondents to check for any ambiguities regarding the content, wording or layout of
the questionnaire. In the first step, 30 participants approached through convenience
sampling were requested to complete the survey and indicate any potential problem
with the survey design. The respondents provided feedback regarding overall layout
of questions, clarity of instructions and wording and the expected time to complete the
survey. In the light of their feedback, some modifications were incorporated to further
improve the survey.
In the second step of pre-testing, a pilot study was conducted to assess the
psychometric properties of the measure, and detect any weakness in the design of the
survey instrument as researchers (Cohen et al., 2005, p: 129,260) recommend to
conduct a pilot study to check the appropriateness, clarity and concreteness of the
measure. The survey was distributed among 60 telecom engineers selected through
convenience sampling with some explanation about the purpose of the study. After
two weeks from date of distribution, 45 filled questionnaires were returned. Owing to
the unrepresentative nature of the sample, results obtained from pre-testing were only
used to test content validity.
4.9 Data Analysis
The objective of data analysis is to convert data into useful information and
examine relationships among study variables and their underlying explanatory
mechanisms (Saunders et al., 2009, p. 414). For this purpose, the study used two
softwares for statistical analysis; Statistical Package for Social Sciences (SPSS) for
preliminary data analysis and AMOS (Analysis of moment structures) version 18 for
Structural Equation Modeling (SEM) to test the hypothesized model of the study.
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4.9.1 Preliminary Data Analysis
Statistical Package for Social Sciences (SPSS), version 20.0, was used to
perform preliminary data analysis. SPSS was used for data screening, data coding,
detection and treatment of missing values, detection of outliers and ascertain the
normality of the data. Moreover, descriptive statistics such as mean, frequencies,
percentages and standard deviations were also calculated through SPSS. The survey
consisted of nominal and ordinal scales. After preliminary data analysis, AMOS
software was used to test the measurement model through confirmatory factor
analysis (CFA) and structural model to test the hypothesized relationships.
4.9.1.1 Data Screening
Data is screened and cleaned to ensure that the data is ready for further
statistical analysis. Data screening involves determination of missing values, outliers,
normality, linearity and homoscedasticity, homogeneity of variance, and
multicollearity. Data screening is crucial to ensure that all assumptions are fulfilled.
(Van den Broeck et al., 2005).
4.9.1.1.1 Missing Values
Missing data is one of the most common problems in a survey research. There
are multiple reasons of missing data such as long questionnaires and lack of clarity
about questions. Tabachnik and Fidell (2007) suggest that percentage of missing data
greater than 5% should be considered troublesome. Missing data reduces statistical
power and can lead to biased estimation of the parameters (Schlomer, Bauman, &
Card, 2010). Sekaran and Bougie (2010) suggest that if the substantial numbers of
questions have not been answered (approximately 25% of the items in the
questionnaire), it is better not to include these questionnaires in dataset for analysis.
There are different techniques for handling missing data depending upon the
pattern of missingness, which are list wise deletion, pair wise deletion, imputation
techniques and model based approaches such as multiple imputation and maximum
likelihood (Graham, 2009).
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4.9.1.1.2 Outliers
Outlier is an observation that deviates so much from other observations so as
to arouse suspicion that it was generated by a different mechanism (Hawkins, 1980).
Outliers can be either univariate or multivariate. Univariate outliers are cases or data
points that have an unusual or extreme value for a single variable whereas
multivariate outliers are cases that have an unusual combination of values for a
number of variables (Kline, 2005). Multivariate outliers can be detected by computing
the squared Mahalanobis distance (D2) for each case. It measures the distance in
standard deviation units between a set of scores and the sample means for all
variables. An outlier will have a D2 value that stands different from all other D
2 values
(Byrne, 2001). Cohen et al., (2003) recommend that ―if outliers are few (less than 1%
or 2% of n) and not very extreme, they should be better left alone‖ (p.128). On the
other hand, if outliers are many in number, then Yuen (1974) recommends trimmed
means (outliers are simply omitted) and Winsorized variances (outliers are pulled
towards the center of the distribution, depending upon the sample size.
4.9.1.1.3 Normality
The individual measured items were checked for normality since it is the most
important assumption in multivariate analysis (Hair et al., 2010). Normality can be
assessed by determining skewness and kurtosis statistics. Skewness is related to the
symmetry of the distribution. A skewed variable is a variable whose mean value does
not fall in the centre of the distribution. If bunching of cases is to the left and a long
tail to the right, the distribution is positively skewed, and for the converse, the
distribution is negatively skewed (Saunders et al., 2009, p. 436)
―Kurtosis is the pointedness or flatness of the distribution compared with the
normal distribution‖ (Saunders et al., 2009, p. 436). When a distribution is more
peaked, the kurtosis value is positive. The kurtosis value is negative in case of a flatter
distribution. Tabachnick and Fidell (2007) suggest that the values of skewness and
kurtosis should be within the range of ±2.
Multicollinearity among independent variables was also tested. Tabachnick
and Fidell (2007) suggest that the correlation coefficient values should not be above
0.85. The correlation matrix for task conflict and relationship conflict was checked
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and the inter-correlation value was -0.58, which means that multicollinearity does not
exist.
4.9.2 Reliability and Validity of Scales
Reliability refers to the ―consistency of the measurement or more simply, the
degree to which an instrument measures the same way each time it is used under the
same conditions with the same subjects‖ (Adams, Khan, Raeside, & White, 2014, p.
235). A measure is considered reliable if it produces the same results every time it is
repeated, but at the same time it may not be inferred that the scale is valid. Adams et
al., (2014) suggest that ―reliability is a necessary condition for validity but not a
sufficient condition on its own‖. There are three approaches to assess reliability of the
scale: test re-test method (repeatability), internal consistency, and equivalent form
(Mitchell, 1996; Adams et al., 2014, p.236). In the present study, reliability of the
scales was checked by applying internal consistency approach using Cronbach‘s
Alpha.
Cronbach‘s alpha measures internal consistency of the scale. Its value ranges
from 0 to 1. A scale is considered to be reliable if the values of Cronbach‘s alpha are
on a higher side (Sekaran, 2006). Nunally (1978) suggests that the value of
Cronbach‘s alpha above 0.70 should be considered as acceptable whereas Sekaran
(2006) suggests that value of Cronbach‘s alpha below 0.5 is poor, value of 0.6 is
acceptable and value above 0.7 is good.
Validity refers to the degree to which an instrument measures what it intends
to measure (Polit & Hungler 1993, 448). Since all the standard scales are being used
in this study, therefore, external validity is already established. Internal validity is the
extent to which effect found in a study can be considered to be real and caused by the
identified independent variable (Coolican, 1994). Internal validity can be established
by using high power statistical tests capable of detecting differences in the observed
phenomenon (Coolican, 1994).
There are three types of internal validity: content validity, criterion-related
validity, and construct validity (Saunders et al., 2012, p. 193). Content validity refers
to the ―extent to which measurement questions adequately reflect their conceptual
definition‖ (Saunders et al., 2012, p. 429). Content validity is usually established
through a panel of experts (Hair et al., 2010). The content validity of the scales has
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been assessed through a focus group (faculty staff) who examined whether the scale
items cover the full domain of the constructs being measured. Criterion validity or
predictive validity is related to the ability of a measure to make accurate predictions
(Saunders et al. 2012, p.429).
Construct validity refers to ―the extent to which measurement questions
actually represent the constructs being studied‖ (Saunders et al., 2012, p. 430). There
are different techniques for checking construct validity such as factor analysis and
item response theory (Greener, 2008). Factor analysis has been used to measure
construct validity of the scales.
4.9.3 Exploratory Factor Analysis
Exploratory factor analysis is used to reduce a number of variables into a
smaller number of higher order factors. In factor analysis, factors need to be identified
which specify the relationship between variables and the factor and this relationship is
referred to as factor loading (Hair et al., 2010). The basic difference between
exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) is that
exploratory factor analysis takes what the data provides it whereas confirmatory
factor analysis is used for grouping and analysis of variables associated with a factor.
However, the underlying purpose of both is to cut down data and present it in more
simplified form.
There are some pre-requisites for conducting exploratory factor analysis such
as assessment of the suitability of data for factor analysis. Bartlett‘s test of sphericity
and Kaiser-Meyer-Olkin test of sampling adequacy are used for this purpose. Bartlett
test of sphericity should be significant and the Kaiser-Meyer-Olkin index should be
0.6 or greater for the factor analysis to be performed (Tabachnick and Fidell, 2007).
Williams, Brown, and Onsman, (2012) have presented a guideline for conducting
exploratory factor shown in figure below which is self-explanatory.
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Figure: 4.3: The 5-step Exploratory Factor Analysis Protocol
(Source: Williams, Brown, & Onsman , 2012)
Exploratory factor analysis is conducted in two steps. First is the extraction of
factors and the second is the rotation of factors. The purpose of extraction is to
determine factors underlying a number of variables (Miller et al., 2002). Principal
component analysis (PCA) is used to extract factors. It is the most widely used
technique where it extracts the maximum variance from collected data (Tabachnick
and Fidell, 2007). Kaiser‘s criterion and the scree plot are used to determine the
number of factors to be retained. According to Kaiser‘s criterion, factors having
eigenvalue of 1.0 or above are retained, where the eigenvalue is the amount of
variance explained by that factor.
The second step is rotation which presents the pattern of loadings that is easier
to interpret. In rotation, factors are rotated to determine which variable group
together. Two approaches are generally used for factor rotation: oblique rotation and
orthogonal rotation. The orthogonal rotations assume that extracted factors are
independent i.e., uncorrelated whereas the oblique rotations assume that the extracted
factors are correlated (Tabachnick & Fidell, 2007). The study used orthogonal
rotation with varimax rotation as it is commonly used and the results obtained from it
have a more generalisability and replicability as compared to oblique rotation
(Tabachnick & Fidell, 2007). Higher loadings depict that the variables are a pure
measure of the factor. Hence, loadings greater than 0.71 are considered excellent,
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more than 0.63 as very good, more than 0.55 as good, more than 0.45 fair and less
than 0.45 but more than 0.32 is considered to be poor (Comrey & Lee, 1992)
4.9.4 Descriptive Statistics
Descriptive statistics is concerned with the development of certain indices
from the raw data. Descriptive statistics includes measures of central tendency (mean,
median, mode) and variability (variance and standard deviation), measures of
asymmetry (skewness) and measures of relationship (correlation), etc., (Kothari,
2004). Correlation analyses were performed for each study variable to assess the
pattern of relationship between study constructs.
These analyses were performed for each variable separately to summarize the
demographic information of the participants in order to obtain preliminary
information about the sample.
4.9.5 Hypothesis Testing using Structural Equation Modeling
Structural equation modeling (SEM) is a multivariate statistical technique that
strives to clarify and explain the relationships among multiple observed or latent
variables (Schreiber et al., 2006). ―SEM facilitates researchers to address a set of
interrelated research questions in a single, systematic, and comprehensive analysis by
modeling the relationships among multiple independent and dependent constructs
simultaneously‖ (Gefen et al., 2000). The purpose of SEM is to ascertain that ―a
model derived from theory is in a close fit to the sample data in terms of the
difference between the sample and model-predicted covariance matrices‖ (Dion,
2008).
SEM is a preferred way of analysis as it combines multiple regression and
factor analysis (Schreiber et al., 2006). SEM is more effective tool to deal with the
problem of multicollinearity as it can be modeled and assessed in SEM as compared
to regression where multicollinearity may pose a problem among predictors and may
influence the size of the coefficients (Dion, 2008). Moreover, SEM can estimate
measurement error unlike other multivariate techniques that cannot measure or correct
for measurement error. SEM has the ability to test model with multiple dependents
and mediators and has the ability to handle difficult data such as time series, non-
normal data and even incomplete data.
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SEM has been used to assess the fit of the proposed model because the study
involves multiple predictors, mediators, and criterion variables, and for such studies,
the researchers recommend structural equation modeling as an appropriate method of
analysis as it allows estimating all coefficients in the model simultaneously (Brooke
& Price, 1989; Byrne, 2001). It differs from multiple regression analysis as it can
estimate a single relationship and there is a clear distinction between independent and
dependent variables whereas in SEM such concepts are used only in relative terms
and it can estimate multiple equations simultaneously which implies that dependent
variable in one equation can become an independent variable in other equations
(Gunzler, Chen, Wu, & Zhang, 2013). SEM models include both endogenous as well
as exogenous variables. ―Endogenous variables act as a dependent variable in at least
one of the SEM equations; hence they are called endogenous instead of response
variables because they may become independent variables in other equations with the
SEM model. On the other hand, exogenous variables are always independent
variables in the SEM equations‖ (Gunzler et al., 2013). Thus, it enables the researcher
to ―assess the significance and strength of a particular relationship in the context of
the complete model‖ (Dion, 2008).
Two-step structural equation modeling (Anderson & Gerbing, 1988) has been
performed in the study using AMOS. In the first step, measurement model is assessed
to validate the operationalisation of the theoretical constructs also known as
confirmatory factor analysis (CFA). The measurement model was tested using the
maximum likelihood estimation method (Hair et al., 1998). Maximum likelihood
method is suitable in models that do not fulfill the criteria of at least 5-items per
construct (Hair et al., 1998). Since some constructs had less than 5-items, maximum
likelihood was more appropriate. Moreover, maximum Likelihood (MLE) method is
preferred because it minimizes the difference between covariance and observed
matrices which in turn improves the parameter estimates (Hair et al., 2010). In the
second step, the structural equation model, specifying the relationship among the
constructs, is tested.
4.9.5.1. Measurement Model
The measurement model is tested using confirmatory factor analysis (CFA).
CFA is performed when there is some a priori knowledge about the underlying
137
constructs and their indicators (Byrne, 2001). It is highly preferable to perform
confirmatory factor analysis (CFA) after exploratory factor analysis in order to
ascertain the validity of the scales derived from EFA. In CFA, the contribution of
each corresponding scale item can be determined alongwith assessment of the
reliability of the scale i.e., ―how well the scale measures the concept‖ (Hair et al.,
2010).
The first step of CFA is model specification. The model is specified on the
basis of a priori theory to build relationships between factors and measures, and the
correlation among factors. Once the model is specified, the next step is model
identification which is followed by estimation of the model parameters. The overall
model fit is ascertained by the degree to which the hypothesized model is supported
by the sample data (Schreiber, 2006).
The goodness-of-fit of the hypothesized model is checked through various fit
indices. There are three types of fit measure indices: absolute fit indices, incremental
fit indices, and parsimonious fit indices (Hair et al., 1998). The absolute fit indices
assess the ability of the overall model. Likelihood ratio statistic chi-square (χ2)
(including the number of degree of freedom, and its p value), root mean square error
of approximation (RMSEA), and goodness of fit index (GFI) are used as absolute fit
indices (Boomsma, 2000; Hair et al., 2010). A value of .08 or less is considered as
indicating a relatively good fit for the RMSEA. Chi-square statistic is sensitive to
sample size because in cases where sample size is greater than 200, chi square is often
significant, implying a poor fit, even if all other indicators show a good model fit
(Joreskog and Sorbom, 1988). Since the chi-square is largely affected by the sample
size, other goodness-of-fit indices are suggested to help indicate the model fit
(Joreskog & Sorbom 1996).
The incremental fit indexes are used to make the comparison between the
proposed model and some baseline model and include indices like normed fit index
(NFI), and comparative fit index (CFI) (Hair et al., 1998). For both indices, values
equal or greater than 0.95 are considered as indicating a good fit. The goodness-of-fit
of the models is assessed with relative and absolute indices as recommended by Hu
and Bentler (1998). The parsimonious fit indices are used to investigate whether the
estimated model is simpler and can be improved further by specifying fewer estimated
paths. This index consists of the adjusted goodness-of-fit index (AGFI). Table 4.2
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shows the different types of fit indices alongwith their corresponding recommended
values:-
Table: 4.3: Goodness of Fit Statistics in SEM
Index Recommended Value Reference
Chi square -χ2 χ2, df, p >0.05 Joreskog and Sorborm (1988)
Ratio of χ2/df(degree
of freedom)
Less than 3 Byrne (2001)
Goodness-of-fit index Greater than 0.90 Byrne (2001)
Root mean square
error of approximation
(RMSEA)
Less than 0.05 good fit
and less than 0.08
acceptable fit
Byrne (2001); McDonald & Ho
(2002); Schreiber et al., 2006
Normed fit index (NFI) Greater than 0.95 Byrne (2001); Schreiber et al.,
2006
Comparative Fit Index
(CFI)
Greater than 0.95 Byrne (2001); Schreiber et al.,
2006
Adjusted goodness-of-
fit index (AGFI)
Greater than 0.90 Byrne (2001)
Factor loading Greater than 5 is
acceptable
Greater than 7 is good
Churchill (1979); Holmes-Smith
(2002)
Critical ratio (t-value) Greater than 1.96 Byrne (2001)
Standard residuals ±2.8 Byrne (2001)
In addition to the model fit indices, other standardized estimates are also used
to evaluate the measurement model such as standardized regression weight or factor
loadings and critical ratio (CR) estimates. The values of factor loadings should be
greater than 0.7 (Holmes-Smith, 2002), nonetheless, a value greater than 0.5 is also
acceptable (Churchill, 1979). R-square values should be relatively large and the t-
values for each of the factor loadings should be greater than 1.96 (Byrne, 2001).
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4.9.5.2 Unidimensionality
Unidimensionality refers to the existence of one latent construct underlying a
set of items (Gerbing & Anderson, 1988). Unidimensionality is established when all
the measuring items have acceptable factor loadings for the corresponding latent
construct (Awang, 2015). In the final measurement model, only those items should be
retained which have factor loading of more than 0.5.
4.9.5.3 Composite Reliability
Finally in CFA, we check for reliability (the squared multiple correlations
(SMC) or squared factor loadings of the observed variables in relationship to the
latent constructs (Schreiber et al., 2006). It explains the variance in an item due to
underlying construct. The cut-off value for items‘ composite reliability is 0.6 (Awang,
2015). After checking the reliability of items, construct validity is ascertained.
Composite reliability is calculated as follows:
Composite Reliability = (∑ Standardized loadings)
2
(∑ Standardized loadings)2+ ∑εj
εj is the measurement error of each item and can be calculated as 1-(Standardized
loadings)2.
4.9.5.4 Construct Validity
Construct validity as defined earlier is the degree to which the items represent
the underlying construct. There are two types of construct validity: convergent
validity and discriminant validity. Convergent validity refers to the extent to which
two items measuring the same construct highly correlate with each other whereas
discriminant validity refers to the extent to which an item differs from items of
another construct (Hair et al., 2006).
Convergent validity is established when the factor loadings and average
variance extracted are greater than 0.5 (Hair et al., 2010). Average variance extracted
is the average percentage of variation explained by the measuring items for a latent
construct (Awang, 2015). Recommended value of AVE is ≥0.5 and it is calculated
using the given formula:
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Average Variance Extracted = ∑ Standardized loadings
2
N
In the above formula, n is the number of items in a model. Retaining the low
factor loading items in a construct can cause that construct to fail on convergent
validity (Awang, 2015).
Discriminant validity is obtained by comparing the square root of the average
variance extracted (AVE) with correlation estimates among latent constructs.
Discriminant validity is established when square root of AVE is greater than the
correlation estimate between that construct and all other constructs (Hair et al., 2010).
Results of convergent validity and discriminant validity are represented in chapter 6.
4.9.5.5 The Structural Model
As discussed earlier, structural equation modeling is a two-step approach.
After evaluation of the measurement model through CFA, structural model is tested to
verify the hypothesized relationships between the latent constructs of the study. The
structural model is a path model which determines the direct/indirect impact of a
construct on other constructs in the model or in other words relates independent to
dependent variables (Schreiber et al., 2006; Hair et al., 2010).
4.10 Testing of Mediation
SEM facilitates the specification and testing of complex models involving
multiple mediators in tandem with the simultaneous testing of multiple paths, with
full statistical control over relationships between indicators variables nested with sets
of predictor, mediators and criterion variables (Wood, Goodman, Beckmann, & Cook,
2008). In fact SEM is the state-of-art approach for testing the mediated relationships
and is ‗more superior method on both theoretical and statistical grounds (Iacobucci,
Saldanha, & Deng, 2007). The present study employed five mediators, hence SEM
was considered the most appropriate analytical technique.
―Mediation exists when a predictor affects a criterion variable indirectly
through at least one intervening variable or mediator‖, (Preacher & Hayes, 2008).
Mediators are ‗behavioral, biological, psychological, or social constructs that transmit
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the effect of one variable to another variable‘ (Mackinnon, Fairchild, & Fritz (2007).
Mediator hypothesis posits how, or by what means, an independent variable (X)
affects a dependent variable (Y) through one or more putative intervening variables or
mediators (M) (Preacher & Hayes, 2008). Hence, mediator is a variable that lies in the
causal sequence between the two variables (Mackinnon et al., 2007).
MacKinnon and Fairchild (2009) explain mediation as a process in which an
antecedent variable affects a mediator variable which in turn affects a dependent
variable, thus making a chain of relations among the three variables. An effect that is
not mediated this way is called a direct effect.
Mediation of each mediator was tested through bootstrapping as recommended
by Preacher and Hayes (2008) and Mackinnon, Fairchild, and Fritz (2007).
―Bootstrapping is a nonparametric resampling procedure that does not impose the
assumption of normality of the sampling distribution. It is a computationally intensive
method that involves repeatedly sampling from the data set and estimating the indirect
effect in each resampled data set‖ (Preacher & Hayes, 2008). By repeating this
process thousands of times, the algorithm builds sampling distribution for the
estimates. From the sampling distribution, total effect, direct effect and indirect effect
between the constructs are estimated (Awang, 2015).
In bootstrapping, I used 1000 bootstrap samples and bias-corrected confidence
interval of 95% to determine the significance of each hypothesized mediation effect.
4.11 Ethical Considerations
The research was carried out according to the ethical guidelines of COMSATS
Institute of Information Technology, Islamabad. Researchers (Adams et al., 2014)
suggest that while planning research, ethical issues critical to the individuals as well
as to society must be considered. These issues range from obtaining an informed
consent to ensuring privacy and confidentiality of the respondents. In the present
study, the questionnaire was accompanied by a covering letter (See Appendix D).
This letter informed the participants about the purpose of the study, the possible
consequences of the research and the utility of the research and that their participation
in the study was voluntary. The respondents were also assured of their privacy and
confidentiality as they were not required to mention their names as the questionnaires
were already coded as a result of stratified random sampling. Contact information of
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the researcher was also provided in case the respondents needed any kind of
assistance regarding the completion of the survey. Confidentiality of the data was
ensured in such a way that the collected data was stored in password protected files to
avoid any intrusion or leakage of information.
4.12 Conclusion
This chapter presented the research methodology of the present study. It
started with philosophical approach which advocated objectivist ontology and
positivist epistemology. The research approach derived from this philosophy is
deductive approach and research design that complements this approach is
quantitative research design based on survey method. These sections were followed
by the details of sampling design, measurement scales, pre-testing the survey,
preliminary data analysis, hypothesis testing using SEM. The chapter ended with
ethical consideration of the research. All the elements of methodology explained in
this chapter have been summarized in table 4.3. The next chapter will present the
results obtained from preliminary data analysis and hypothesis testing using structural
equation modeling.
Table: 4.4: Details of the Research Methodology
Methodology Element Choice of this study
Research Ontology Objectivism
Research Epistemology Positivism
Research Approach Deductive
Research Design Quantitative
Research Strategy Survey Questionnaire
Sampling Technique Probability Sampling Technique
Time Horizon Cross-sectional
Data Collection Tool Self-Administered Questionnaire
Preliminary Data Analysis SPSS 20.0
Hypothesis Testing Structural Equation Modeling using
AMOS
(Source: Compiled by Researcher)
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Chapter 5
Results
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Results
This chapter presents the results and interpretation of the hypothesis testing
and data analysis using structural equation modeling. The chapter starts with the
preliminary data analysis which reports information on non-response bias, and
demographic characteristics of the participants. This further includes data screening,
missing values, outliers, normality, muticollinearity and descriptive statistics of the
study constructs. This is followed by findings of confirmatory factor analysis. The
final section reports results of the hypothesis testing using bootstrapping.
5.1 Non-response Bias
It was not possible for the researcher to obtain demographic information of all
non-respondents in order to compare them with the respondents for direct bias test.
Therefore, to check any potential non-response bias, it was assumed that employees
who failed to fill the questionnaire were more like those who delayed in responding
rather than those who filled the questionnaires on time (Babbi, 1990, p 180). Hence,
questionnaires received at different point of time of data collection (i.e., early
respondents and late respondents) were used in analysis to assess the non-response
bias. The respondents were divided in two groups and were analyzed with respect to
their demographic profiles. Analysis of variance and independent t-tests were
performed to estimate the response bias. The results are shown in Table 5.1 and 5.2,
respectively.
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Table: 5.1: Statistics of early and late responses
Response N Mean Std. Deviation Std. Error Mean
Company Early 364 3.10 1.385 .073
Late 144 2.85 1.516 .126
Education
Level
Early 364 1.54 .657 .034
Late 144 1.42 .610 .051
Gender Early 364 1.20 .403 .021
Late 144 1.15 .361 .030
Age Early 364 1.86 .846 .044
Late 144 1.72 .913 .076
Marital
Status
Early 364 1.46 .499 .026
Late 144 1.47 .501 .042
Table: 5.2: t-test for comparison of early vs late respondents.
T Df Sig.
(2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
Company 1.836 506 .067 .257 .140 -.018
Education
Level 1.813 506 .070 .115 .063 -.010
Gender 1.310 506 .191 .051 .039 -.025
Age 1.697 506 .090 .145 .085 -.023
Marital
Status -.217 506 .828 -.011 .049 -.107
Note: df (degree of freedom)
The results indicate that there were no statistically significant differences
between the early and late respondents. Thus, it may be implied that respondents were
not different from the non-respondents. Consequently, non-response bias was not
considered a serious limitation in this research survey.
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5.2 Demographic Characteristics of the Participants
The questionnaire was sent to 650 randomly selected telecom engineers and in
response 508 usable questionnaires were obtained, thus making a response rate of
78%.
Table: 5.3: Demographic Profile of the Respondents
Variable Category Frequency %Age
Gender Male 412 81
Female 96 19
Age
25-34 Years 245 48
35-44 Years 110 22
45 & Above 153 30
Educational Level
B.Sc 283 56
M.Sc 203 40
MS 12 2
PhD 10 2
Marital Status Single 272 53
Married 236 47
Work Experience Average 6.46 Years
Table 5.3 describes the demographic information of the sample. The sample
was homogeneous as the data was collected from telecom engineers. Majority of the
sample was male i.e., 81%. With regard to age, most of the respondents i.e., 48%
were between the ages of 25 to 34 years, 22% were between 35 to 44 years and 30%
were 45 years or above age bracket, which shows that majority of the sample was
young employees. In terms of educational level, the results revealed that 56%
respondents held B.Sc (Bachelors in science), followed by 40% having M.Sc (Masters
in science), and 2 % had M.S (equivalent to Masters in philosophy) degrees and it can
be inferred that most of the respondents held bachelors degree from the university.
There were 2% Ph.Ds (Doctors in Philosophy) in the sample. The average work
experience of the respondents was 6.46 years. 53% of the sample was single and 47%
was married.
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5.3 Preliminary Analysis of the Data
Preliminary analysis was performed with SPSS, version 20.0. The analysis
included screening of the raw data to ensure accuracy and normality of the data (Hair
et al., 2010). These steps have been discussed in the following sections.
5.3.1 Data Cleaning and Screening
Data was coded and values were entered according to the measurement scales.
First, demographic variables were coded, namely; age, gender, educational level,
work experience and marital status. Gender (1 = male, 2 = female), educational level
(1 = Bachelors in Engineering, 2 = MSc, 3 = MS, 4 = Ph.D), age (25-34 = 1, 35-44 =
2, 45 and above = 3), and marital status (single = 1, married = 2). Afterwards, data
related to scaled items or responses of the sample was entered (Likert type format).
The next step was checking of missing values and detection of outliers.
5.3.1.1 Missing Values
Missing values were detected and found to be 1.5 percent, well below the cut-
off value of 5 % as out of total 528 questionnaires, 12 questionnaires were discarded
due to response consistency bias whereas 8 questionnaires has missing values-
approximately 25% of each questionnaire was not answered. Following the
recommendations of Sekaran and Bougie (2010), these questionnaires were excluded
from the dataset, hence listwise deletion was considered most appropriate due to low
percentage of questionnaires having missing values. Moreover, biases and loss of
power are insignificant if the percentage of missing values is less than 5% (Graham,
2009). After listwise deletion, the remaining 508 questionnaires were complete in all
respects.
There are number of factors that account for this low percentage. First, the
questionnaire was self-administered and apart from demographic information, the
response format was 5-point likert type and respondents had to choose from these
given response points ranging from 1= strongly disagree to 5= strongly agree. De
Leeuw, Hox, and Huisman, (2003) suggest that self-administered questionnaires help
reduce the likelihood of occurrence of missing values. Design and layout of the
questionnaire should be simple and proper instructions should be incorporated to help
guide the respondents. These recommendations were followed in the present study in
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pre-testing with a focus group and pilot testing with a handful of respondents. In
addition, two sources were used in this study i.e., main respondents and supervisors
who assessed task/contextual performance of the respondents. Hence, the
questionnaires were not long for respondents. Moreover, after distributing the
questionnaires, the respondents who had any query were explained regarding that item
and the questionnaires were collected after two weeks in order to provide respondents
with sufficient time to understand the questions and reply accordingly.
5.3.1.2 Outliers
Outlier is an extreme value which may be high or low on a variable and may
result in non-normal data and distorted statistics (Hair et al., 2010). Univariate outliers
can be identified by determining frequency distributions of Z-scores of the observed
data (Kline, 2005). There were no univariate outliers as the study employed a 5 point
likert scale ranging from 1=strongly disagree to 5 = strongly agree. The response
anchors of ‗strongly disagree‘ or ‗strongly agree‘ could become outliers since these
are the extreme points of the scale.
Multivariate outliers were detected in this study with the Mahalonobis D2
which measures the squared distance of each observation from the mean centre of all
observations on a set of variables, providing a single value for each variable
irrespective of the number of variables considered (Hair et al., 2010). Arbuckle (1997)
elucidated the method to determine observations that may be outliers as: ―Small
numbers in the p1 column are to be expected. Small numbers in the p2 column, on the
other hand, indicate observations that are improbably far from the centroid under the
hypothesis of normality‖. This heuristic has been used as a threshold value to detect
outliers. There were a number of cases detected as outliers, but as they are source of
important information on the data (Hair et al., 2010), therefore, all outliers were
retained (see Table 5.4 in Appendix H).
5.3.1.3 Normality
After checking for missing values and outliers, the next step is to check
normality of the data. The normality of the data has been checked with skewness
(symmetry of the distribution) and kurtosis (―the pointedness or flatness of the
distribution compared with the normal distribution‖ (Saunders et al., 2012, p. 495).
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Table 5.5 shows descriptive statistics including values of skewness and kurtosis of
individual scale items of continuous variables. Values of skewness and kurtosis
should be within the range of ±2 (Tabachnick & Fidell, 2007). The values of
skewness and kurtosis were found within the recommended range thus indicating that
the data fulfills the normality assumption. However, the results show scores with both
positive and negative values but according to researchers (Pallant, 2007) positive and
negative skewness and kurtosis does not pose any problem if they are within the
acceptable range, rather these values represent the underlying nature of the constructs
(see Table 5.5 in Appendix I).
5.3.1.4 Correlations among the Study Variables
In general, most of the correlations between the study variables were
significant and in the expected direction. Tables 5.6 present the correlations between
the study variables.
Correlations among the study variables alongwith their reliability, standard
deviations and means are presented in Table 5.6. The correlations depicts that task
conflict was significantly correlated with all outcomes variables. Task conflict
positively correlated with task performance (r=0.57, p<.01) and contextual
performance (r=0.619, p<.01). Task conflict negatively correlated with turnover
intentions (r= -0.447, p<.01). Moreover, task conflict positively correlated with job
satisfaction and correlation was significant (r= 0.557, p<.01). Task conflict positively
correlated with work engagement and this correlation was significant (r= 0.547,
p<.01).
Relationship conflict negatively correlated with both task performance (r= -
0.493, p<.01) and contextual performance (r= -0.488, p<.01). However, relationship
conflict positively correlated with turnover intentions (r= 0.550, p<.01). Relationship
conflict also correlated positively with the three dimensions of job burnout such that it
positively correlated with exhaustion and the correlation was significant (r= 0.422,
p<.01). Relationship conflict positively correlated with cynicism and the correlation
was significant (r= 0.513, p<.01). Relationship conflict also reflected a positive and
significant correlation with Interpersonal strain at work (r= 0.340, p<.01). The
demographic variables did not significantly correlate to any of the study constructs;
therefore, they were not controlled in further analysis.
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Table 5.6 Correlations, Standard Deviations, Mean Values and Reliability Statistics
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5.3.1.5 Exploratory Factor Analysis
The purpose of exploratory factor analysis (EFA) is to reduce a number of
variables into a smaller number of higher order factors (Hair et al., 2010). In factor
analysis, factors need to be identified which specify the relationship between variables
and the factor and this relationship is referred to as factor loading (Hair et al., 2010).
The items were subjected to exploratory factor analysis using principal component
analysis with varimax rotation. Items with extraction communalities less than or equal
to 0.50 were deleted. Items with unique factor loadings less than 0.5 were deleted
(Hair et al., 2010; Tabachnick & Fidell, 2007). The following sections report the
results of EFA.
5.3.1.5.1 Validation of Task Conflict
Task conflict (TC) was measured with adapted scale of Jehn (1995). The
original scale had 4 items. Measurement items were subjected to an EFA on the data
(N=508). The items sufficiently loaded onto their underlying factor and had unique
contribution (KMO=0.784). Moreover, Bartlett‘s test of sphericity indicated that the
correlations between items were adequate (𝝌²= 681.391, p<0.000). One factor
emerged explaining 64.163% of the total variance. Cronbach‘s α for this scale was
0.812. All of the four items were retained for further analysis
Table: 5.7: Component Matrix-Task Conflict
Items Component (1)
TC1 0.874
TC2 0.770
TC3 0.770
TC4 0.786
KMO = 0.784, Variance = 64.163%, Reliability = 0.812
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5.3.1.5.2 Validation of Relationship Conflict
The study used the adapted version of Jehn‘s (1995) 4-items scale of
relationship conflict. Measurement items were subjected to an EFA on the data
(N=508). The items adequately loaded onto their respective factor and had unique
contribution (KMO=0.850). Moreover, Bartlett‘s test of sphericity indicated that the
correlations between items were adequate (𝝌²= 1308.729, p<.000). One factor
emerged explaining 78.198% of the total variance. Cronbach‘s α of the measure was
0.907. All of the four items were retained for further analysis.
Table: 5.8: Component Matrix- Relationship Conflict
Items Component (1)
RC1 0.870
RC2 0.898
RC3 0.896
RC4 0.873
KMO = 0.850, Variance = 78.198%, Reliability = 0.907
5.3.1.5.3 Validation of Work Engagement
The study adopted the shortened version of the Utrecht Work Engagement
Scale (UWES; Schaufeli & Bakker, 2010; Schaufeli et al., 2006; Schaufeli et al.,
2002, Schaufeli et al., 2008) that was originally a three factor model, each consisting
of 3-items, thus making 9-items scale. Measurement items were subjected to an EFA
on the data (N=508). Single factor emerged instead of three factors which had unique
contribution (KMO=0.918). Three items were deleted due to low communalities.
Moreover, Bartlett‘s test of sphericity indicated that the correlations between items
were adequate (𝝌²= 1812.607, p<.000). One factor emerged explaining 68.916 % of
the total variance. Cronbach‘s α of the measure was 0.863. Six items were retained for
further analysis.
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Table: 5.9: Component Matrix- Work Engagement
Items Component (1)
WE3 0.802
WE4 0.815
WE5 0.869
WE6 0.853
WE7 0.847
WE8 0.792
KMO = 0.918, Variance = 68.916%, Reliability = 0.863
5.3.1.5.4 Validation of Job Satisfaction
Job satisfaction was measured through a 3-items scale developed by Cammann
et al., (1983). Measurement items were subjected to an EFA on the data (N=508). The
items adequately loaded onto their respective factor and had unique contribution
(KMO=0.725). Moreover, Bartlett‘s test of sphericity indicated that the correlations
between items were adequate (𝝌²= 576.561, p<.000). One factor emerged explaining
74.852% of the total variance. Cronbach‘s α of the measure was 0.832. All three items
were retained for further analysis.
Table: 5.10: Component Matrix- Job Satisfaction
Items Component (1)
JS1 0.869
JS2 0.862
JS3 0.865
KMO = 0.725, Variance = 74.852%, Reliability = 0.832
5.3.1.5.5 Validation of Exhaustion
Exhaustion was measured through sub-scale (5-items) of the Maslach Burnout
Inventory-General Survey (MBI-GS; Schaufeli, Maslach, Leiter, & Jackson, 1996,
Borgogni et al., Measurement items were subjected to an EFA on the data (N=508).
The items adequately loaded onto their respective factor and had unique contribution
(KMO=0.814). One item was deleted in EFA. Moreover, Bartlett‘s test of sphericity
indicated that the correlations between retained items were adequate (𝝌²= 759.107,
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p<.000). One factor emerged explaining 67.187% of the total variance. Cronbach‘s α
of the measure was 0.799. Four out of five items were retained for further analysis .
Table: 5.11: Component Matrix- Exhaustion
Items Component (1)
EXH2 0.823
EXH3 0.831
EXH4 0.825
EXH5 0.799
KMO = 0.814, Variance = 67.187%, Reliability = 0.799
5.3.1.5.6 Validation of Cynicism
Cynicism was measured through the sub-scale (5-items) of Maslach Burnout
Inventory-General Survey (MBI-GS; Schaufeli, Maslach, Leiter, & Jackson, 1996,
Borgogni et al., 2012. Measurement items were subjected to an EFA on the data
(N=508). The items adequately loaded onto their respective factor and had unique
contribution (KMO=0.828). One item was removed due to low communality value.
Moreover, Bartlett‘s test of sphericity indicated that the correlations between items
were adequate (𝝌²= 944.874, p<.000). One factor emerged explaining 71.413% of the
total variance. Cronbach‘s α of the measure was 0.832. Four items were retained for
further analysis.
Table: 5.12: Component Matrix-Cynicism
Items Component (1)
CYN2 0.822
CYN3 0.872
CYN4 0.851
CYN5 0.834
KMO = 0.828, Variance = 71.413%, Reliability = 0.832
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5.3.1.5.7 Validation of Interpersonal Strain at Work
Interpersonal strain at work measured through the 6-items scale developed by
Borgogni et al., (2012). Measurement items were subjected to an EFA on the data
(N=508). The items adequately loaded onto their respective factor and had unique
contribution (KMO=0.888). One item was removed due to low communality value.
Moreover, Bartlett‘s test of sphericity indicated that the correlations between items
were adequate (𝝌²= 1414.002, p<.000). One factor emerged explaining 70.684% of
the total variance. Cronbach‘s α of the measure was 0.861. Five items were retained
for further analysis.
Table: 5.13: Component Matrix- Interpersonal Strain at Work
Items Component (1)
ISW1 0.864
ISW2 0.844
ISW3 0.851
ISW4 0.853
ISW5 0.797
KMO = 0.888, Variance = 70.684%, Reliability = 0.861
5.3.1.5.8 Validation of Task Performance
Supervisor rated in-role or task performance has been measured with 5 items
from Williams and Anderson (1991) scale. Measurement items were subjected to an
EFA on the data (N=508). The items adequately loaded onto their respective factor
and had unique contribution (KMO=0.799). One item was removed due to low
communality value. Moreover, Bartlett‘s test of sphericity indicated that the
correlations between items were adequate (𝝌²= 685.477, p<.000). One factor emerged
explaining 64.869% of the total variance. Cronbach‘s α of the measure was 0.812.
Four items were retained for further analysis.
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Table: 5.14: Component Matrix- Task Performance
Items Component (1)
TP1 0.795
TP2 0.852
TP3 0.778
TP4 0.795
KMO = 0.799, Variance = 64.869%, Reliability = 0.812
5.3.1.5.9 Validation of Contextual Performance
Supervisor rated extra-role or contextual performance was measured with
scale developed by Eisenberger et al., (2010). This is an 8 items scale Measurement
items were subjected to an EFA on the data (N=508). The items adequately loaded
onto their respective factor and had unique contribution (KMO=0.852). Three items
were removed during EFA due to low threshold of communality values. Moreover,
Bartlett‘s test of sphericity indicated that the correlations between items were
adequate (𝝌²= 866.338, p<.000). One factor emerged explaining 60.055% of the total
variance. Cronbach‘s α of the measure was 0.870. Five items were retained for further
analysis.
Table: 5.15: Component Matrix- Contextual Performance
Items Component (1)
CP1 0.779
CP3 0.815
CP4 0.788
CP5 0.748
CP6 0.742
KMO = 0.852, Variance = 60.055%, Reliability = 0.870
5.3.1.5.10 Validation of Organizational Turnover Intentions
Organizational turnover intention has been measured from Meyer et al.‘s
(1993) three-item scale. Measurement items were subjected to an EFA on the data
(N=508). The items adequately loaded onto their respective factor and had unique
contribution (KMO=0.691). Moreover, Bartlett‘s test of sphericity indicated that the
correlations between items was adequate (𝝌²= 411.947, p<.000). One factor emerged
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explaining 68.851% of the total variance. Cronbach‘s α of the measure was 0.774. All
of the three items were retained for further analysis.
Table: 5.16: Component Matrix- Organizational Turnover Intentions
Items Component (1)
OTI1 0.852
OTI2 0.795
OTI3 0.841
KMO = 0.691, Variance = 68.851%, Reliability = 0.774
5.4 Common Method Bias
The data on predictor variables, mediators and one of the outcomes i.e.,
turnover intentions was collected from telecom engineers, using a self-administered
questionnaire, and performance ratings were obtained from their supervisors in order
to avoid common method variance or bias. This is a variance that is attributed to
measurement method or source rather than to the study constructs which may create
systematic or random error, thus leading to spurious relationship between constructs.
In order to determine this possibility, Harman‘s single factor test (1976) was
performed on self-report constructs. In case only one factor emerges from the factor
analysis, or it accounts for over 50% of the variance in variables, then it is an
indication that common method variance has occurred.
All of the self-report items (Task Conflict, Relationship Conflict, Job
Satisfaction, Work Engagement, Exhaustion, Cynicism and Interpersonal Strain at
Work) were combined in a principal component analysis without any rotation. The
one factor solution gave 34.6% cumulative variance which is less than the threshold
of 50%. The results of common method bias are satisfactory as the value shows that
the single factor did not account for over 50% variance in the variable (see Table 5.17
in Appendix J)
5.5 Structural Equation Modeling
Structural equation modeling is used to test the relationships among latent
constructs where we are interested to understand the interrelationships among
multiple dependent and independent variables simultaneously (Hair et al., 2010).
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Structural equation modeling has been conducted in two steps. In the first step, the
measurement model has been specified using the interrelationships among latent
factors and indicators or observed variables. Confirmatory factor analysis (CFA) was
performed to test the measurement model. After CFA, the structural model specifying
the hypothesized relationships among latest constructs was tested.
5.6 The Measurement Model
Confirmatory factor analysis (CFA) was conducted on the measurement model
to ascertain the unidimensionality, reliability and validity of the underlying
dimensions of the constructs.
CFA can be run for every construct separately or for the complete model i.e.,
pooled measurement model. Awang (2015) suggests that CFA for pooled
measurement models is more efficient and highly recommended. Moreover, in pooled
CFA, ―there is no problem of model identification even if certain constructs have less
than four items because the combined constructs would increase the degrees of
freedom for the model‖ (Awang, 2015). Hence, pooled CFA was conducted on all
measurement models. CFA was performed on the measurement model consisting of
ten factors, which were: task conflict (TC); relationship conflict (RC); work
engagement (WE); job satisfaction (JS); exhaustion (EXH); cynicism (CYN);
interpersonal strain at work (ISW); task performance (TP); contextual performance
(CP); and organizational turnover intentions (OTI). The hypothesized measurement
model is presented in figure 6.1. These latent constructs were measured by their
respective indicators and are presented by ellipses or circles and indicator variables as
rectangles. The measurement model was evaluated through the maximum likelihood
(ML) estimation technique. The results of CFA for overall measurement model have
been presented in table 5.18
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Figure: 5.1: Confirmatory Factor Analysis of the Model
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5.6.1 Unidimensionality
The unidimensionality was obtained by testing the data in AMOS. All items
left after EFA were examined through this procedure. Unidimensionality is achieved
when all indicator variables have acceptable factor loading for their respective latent
constructs (Awang, 2015). It was observed that all factor-loadings of measuring items
were positive and above the threshold value i.e., 0.5 (Hair et al., 2010). No item was
deleted at this stage.
5.6.2 Validity
The validity of the data was established through the processes defined
hereunder:
5.6.2.1 Convergent Validity
Convergent validity is agreement between measures of the same construct
assessed by different methods (Campbell & Fisk, 1959). The Convergent Validity is
verified by computing the Average Variance Extracted (AVE) for every construct.
Convergent validity is achieved when values of AVE are greater than 0.5 (Awang,
2015; Hair et al., 2010). The AVE values for measurement model are presented in the
No. 5.20 in Appendix K. The values of AVE ranged between 0.502 to 0.710 for
constructs of the study demonstrating that convergent validity was established for
each construct.
5.6.2.2 Construct Validity
Construct validity refers to ―the extent to which measurement questions
actually represent the constructs being studied‖ (Saunders et al., 2012, p. 193).
Construct validity is established if the values of model fit indices meet their threshold
level (Awang, 2015). The values of fitness indicators established the construct
validity of the measurement model. The values of RMSEA, NFI, GFI and CFI were
within the required thresholds limits and have been shown in table.
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Table: 5.18: Goodness of Fit Indices
Model Fit Indices Values
GFI 0.917
CFI 0.980
NFI 0.921
MRSEA 0.025
Chisq/df 1.314
Note: GFI (Goodness of Fit Index), CFI (Comparative Fit Index), NFI (Normed Fit Index), Threshold
value greater than 0.9, RMSEA (Root Mean Square Error of Approximation)-threshold value less than
or equal to .08, Chisq/df- (degree of freedom) less than 3.
5.6.2.3 Discriminant Validity
Discriminant validity is the distinctiveness of different constructs (Campbell
& Fisk, 1959). The redundant items were deleted in the study to achieve the
discriminant validity. The following table presented the square root values of average
variance extracted (AVE) of the construct alongwith the correlation estimates between
the constructs. The results showed that the values of square root AVE (mentioned
diagonally in bold) were greater as compared to the corresponding correlation values
in same rows and columns which proves that the constructs in the model are
discriminant of each other.
Table: 5.19: Discriminant Validity Index
Items TC RC WE JS EXH CYN ISW OTI TP CP
TC (.728)
RC -.505**
(.843)
WE .547**
-.454**
(.792)
JS .557**
-.520**
.551**
(.789)
EXH -.471**
.422**
-.502**
-.446**
(.750)
CYN -.509**
.513**
-.499**
-.569**
.566**
(.787)
ISW -.464**
.340**
-.472**
-.439**
.492**
.497**
(.796
OTI -.447**
.550**
-.473**
-.515**
.496**
.520**
.435**
(.732)
TP .570**
-.493**
.630**
.598**
-.502**
-.552**
-.465**
-.461**
(.731)
CP .619**
-.488**
.628**
.631**
-.518**
-.561**
-.470**
-.441**
.558**
(.708)
Task conflict (TC); relationship conflict (RC); work engagement (WE); job satisfaction (JS);exhaustion
(EXH); cynicism (CYN); interpersonal strain at work(ISW); task performance (TP); contextual
performance (CP); and organizational turnover intentions (OTI)
Bold Values in diagonal are Square Root of Average Variance Extracted.
** Values are significant at 0.001.
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5.7 Reliability of the Measurement Model
The reliability of measurement model was tested by researcher through
average variance extracted (AVE) and composite reliability (CR) values. The AVE
and CR values are presented in the Table 5.19. The values of AVE are greater than
0.5 in all cases. The CR values were also well above threshold of 0.60 in all
constructs. Both requirements confirmed the reliability of the measurement model
(see Table 5.20 in Appendix K).
5.8 Direct Relationship
The structural equation model for direct relationship was performed in AMOS.
The direct impact of exogenous variables on outcome variables is presented in the
table and also shown in the figure. The table includes the standardized path
coefficients against their corresponding significance levels.
Figure: 5.2: Direct Relationship
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Table: 5.21: The standardized regression weights and its significance for each path
Construct Path Construct Standardize
d Estimate
P-
Value Result
Task Performance <--- Task Conflict 0.533 0.001 Significant
Contextual Performance <--- Task Conflict 0.611 0.001 Significant
Turnover Intentions <--- Task Conflict -0.278 0.001 Significant
Task Performance <--- Relationship Conflict -0.253 0.001 Significant
Contextual Performance <--- Relationship Conflict -0.152 0.006 Significant
Turnover Intentions <--- Relationship Conflict 0.499 0.001 Significant
5.8.1 Task Conflict and Task/Contextual Performance and Turnover
Intentions
Hypotheses 1a, 1b, and 1c investigated the relationship between task conflict
and task performance, contextual performance and turnover intentions. It was
hypothesized that there would be a positive relationship between task conflict and
both task performance and contextual performance, and a negative relationship
between task conflict and turnover intentions. The results demonstrated positive and
significant path from task conflict to task performance (β = 0.533, p = 0.001) and
contextual performance (β = 0.611, p = 0.001) and a negative and significant path
from task conflict to turnover intentions (β = - 0.278, p < 0.001). Thus, hypothesis 1a,
1b, and 1c were supported.
5.8.2 Relationship Conflict and Task/Contextual Performance and
Turnover Intentions
Hypotheses 4a, 4b, and 4c investigated the relationship between relationship
conflict and task performance, contextual performance and turnover intentions. It was
hypothesized that there would be a negative relationship between relationship conflict
and both task performance and contextual performance, and a positive relationship
between relationship conflict and turnover intentions. The results demonstrated
negative and significant paths from relationship conflict to task performance (β = -
0.253, p = 0.001) and contextual performance (β = -0.152, p = 0.006) and a positive
and significant path from relationship conflict to turnover intentions (β = 0.499, p <
0.001). Thus, hypothesis 4a, 4b, and 4c were supported.
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5.9 Testing of Mediation
5.9.1 Prerequisites for Mediation Testing
There are certain preconditions for testing mediation using structural equation
modeling (SEM). The first condition for mediation is that (1) predictor variable (X) is
related to the mediator (M) and (2) that the mediator (M) is related to the criterion
variable (Y) and these paths should be significant (MacKinnon, Lockwood, Hoffman,
West, & Sheets, 2002).
Furthermore, it has been argued by the researchers (Hayes, 2009; Preacher &
Hayes, 2008: Mackinnon, 2000) that the precondition of Baron and Kenny (1986)
about the relationship between predictor (X) and criterion (Y) variable being
significant is not necessary whilst the relationship between X and MY should be
significant (Zhao, Lynch, & Chen, 2010). ―The absence of a direct effect after
controlling for an initial mediator should not lead to the conclusions of full
mediation‖ (Rucker, Preacher, Tormala, & Petty, 2011). Researchers‘ quest for
mediation should be guided by theory and if there are theoretical reasoning for
likelihood of an indirect effect, or multiple indirect effects, researchers should explore
these effects irrespective of the significance of the total or direct effect (Rucker et al.,
2011). Mathieu and Taylor, (2006) contend that confounding, suppression or
interactive effect may decrease the overall X Y relationship since this effect indicates
the presence of non-linear relationships which violate an assumption of testing
mediation. Secondly, in inconsistent mediation models, in which one mediated effect
has a different sign than other mediated or direct effect (Mackinnon et al., 2007), the
mediation effects may reduce the total X Y relationship.
There were five mediators in the present study i.e., work engagement, job
satisfaction, exhaustion, cynicism and interpersonal strain at work. Bootstrapping
method has been used to test the mediation of each mediator as it a nonparametric
resampling technique that does not impose the assumption of normality of the
sampling distribution (Preacher & Hayes, 2008; Mackinnon, Fairchild, & Fritz
(2007). Being computationally intensive method, ―bootstrapping draws repeated
sampling from the data set and estimates the indirect effect in each resampled data
set‖ (Preacher & Hayes, 2008). With intensive repeated iterations, the algorithm
computes sampling distribution for the estimates. From the sampling distribution,
total effect, direct effect and indirect effects are estimated (Awang, 2015).
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The total effect is the degree to which a change in independent variable is
related with the dependent variable (XY). The indirect effect is the degree to which
a change in the independent variable produces a change in the dependent variable
through the mediator (XMY). The direct effect is the degree to which a change in
the independent variable is directly related with the dependent variable without going
through the mediator (Awang, 2015).
In bootstrapping, the researcher used 1000 bootstrap samples and bias-
corrected confidence interval of 95% to determine the significance of each
hypothesized mediation effect.
Table: 5.22: Results of Mediations
Path Total
Effect
Direct Effect Indirect Effect Lower
Bound
Upper
Bound Results
Estimate p-value Estimate p-value
TC → WE → TP 0.295 0.153 0.006 0.143 0.002 0.087 0.209 Partial
TC → WE → CP 0.380 0.261 0.002 0.120 0.001 0.062 0.187 Partial
TC → WE → OTI -0.015 0.043 0.479 -0.057 0.044 -0.138 -0.003 Full
TC → JS → TP 0.303 0.140 0.042 0.163 0.002 0.071 0.264 Partial
TC → JS → CP 0.449 0.248 0.003 0.200 0.002 0.092 0.321 Partial
TC → JS → OTI -0.066 0.082 0.241 -0.147 0.046 -0.278 -0.008 Full
RC → EXH → TP -0.103 -0.064 0.116 -0.038 0.036 -0.080 -0.005 Full
RC → EXH → CP -0.025 0.023 0.546 -0.048 0.016 -0.095 -0.011 Full
RC → EXH → OTI 0.382 0.321 0.001 0.061 0.006 0.013 0.143 Partial
RC → CYN → TP -0.115 -0.064 0.157 -0.051 0.044 -0.105 -0.001 Full
RC → CYN → CP -0.028 0.025 0.569 -0.053 0.037 -0.105 -0.004 Full
RC → CYN → OTI 0.390 0.326 0.001 0.064 0.045 0.001 0.137 Partial
RC → ISW → TP -0.101 -0.067 0.105 -0.034 0.024 -0.081 -0.003 Full
RC → ISW → CP -0.018 0.019 0.645 -0.037 0.040 -0.076 -0.002 Full
RC → ISW → OTI 0.382 0.327 0.001 0.056 0.016 0.015 0.103 Partial
Task conflict (TC); relationship conflict (RC); work engagement (WE); job satisfaction (JS);exhaustion (EXH); cynicism (CYN);
interpersonal strain at work(ISW);task performance (TP); contextual performance (CP); and organizational turnover intentions
(OTI)
166
Figure: 5.3: Mediation Model
167
5.9.2 Mediation of Work Engagement
Hypothesis 2a posits that work engagement mediate the link between task
conflict and task performance. Bootstrapping results confirmed partial mediation as
the direct relationship is still significant
Hypothesis 2b posits that work engagement mediates the link between task
conflict and contextual performance. Bootstrapping results confirmed partial
mediation as the direct relationship is still significant
Hypothesis 2c posits that work engagement mediates the link between task
conflict and turnover intentions. Bootstrapping results confirmed full mediation as the
direct relationship is no longer significant.
5.9.3 Mediation of Job Satisfaction
Hypothesis 3a posits that job satisfaction mediates the link between task
conflict and task performance. Bootstrapping results confirmed partial mediation as
the direct relationship is still significant.
Hypothesis 3b posits that job satisfaction mediates the link between task
conflict and contextual performance. Bootstrapping results confirmed partial
mediation as the direct relationship is still significant.
Hypothesis 3c posits that job satisfaction mediates the link between task
conflict and turnover intentions. Bootstrapping results confirmed full mediation as the
direct relationship is no longer significant.
5.9.4 Mediation of Exhaustion
Hypothesis 5a posits that exhaustion mediates the link between relationship
conflict and task performance. Bootstrapping results confirmed full mediation as the
direct relationship is not significant.
Hypothesis 5b posits that exhaustion mediates the link between relationship
conflict and contextual performance. Bootstrapping results confirmed full mediation
as the direct relationship is no longer significant.
Hypothesis 5c posits that exhaustion mediates the link between relationship
conflict and turnover intentions. Bootstrapping results confirmed partial mediation as
the direct relationship is still significant.
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5.9.5 Mediation of Cynicism
Hypothesis 6a posits that cynicism mediates the link between relationship
conflict and task performance. Bootstrapping results confirmed full mediation as the
direct relationship is not significant.
Hypothesis 6b posits that cynicism mediates the link between relationship
conflict and contextual performance. Bootstrapping results confirmed full mediation
as the direct relationship is not significant.
Hypothesis 6c posits that cynicism mediates the link between relationship
conflict and turnover intentions. Bootstrapping results confirmed partial mediation as
the direct relationship is still significant.
5.9.6 Mediation of Interpersonal Strain at Work
Hypothesis 7a posits that interpersonal strain at work mediates the link
between relationship conflict and task performance. Bootstrapping results confirmed
full mediation as the direct relationship is not significant.
Hypothesis 7b posits that interpersonal strain at work mediates the link
between relationship conflict and contextual performance. Bootstrapping results
confirmed full mediation as the direct relationship is no longer significant.
Hypothesis 7c posits that interpersonal strain at work mediates the link
between relationship conflict and turnover intentions. Bootstrapping results confirmed
partial mediation as the direct relationship is still significant.
5.10 Summary of Results
Table 5.23 shows the results of the direct relationships between independent
variables (Task conflict, relationship conflict) and dependent variables (task
performance, contextual performance and turnover intentions). All hypothesized
direct relationships were found to be significant and in the expected direction.
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Table: 5.23: Summary of Direct Hypotheses
Hypothesis Path Results
Hypothesis 1a Task ConflictTask Performance Supported
Hypothesis 1b Task ConflictContextual Performance Supported
Hypothesis 1c Task ConflictTurnover Intentions Supported
Hypothesis 4a Relationship ConflictTask Performance Supported
Hypothesis 4b Relationship ConflictContextual Performance Supported
Hypothesis 4c Relationship ConflictTurnover Intentions Supported
Table 5.24 shows the results of indirect relationship tested through
bootstrapping. Bootstrapping results supported mediation in all of our hypothesized
indirect relationships.
Table: 5.24: Summary of Indirect Hypotheses
Hypothesis Path (Mediator) Results
Hypothesis 2a Task ConflictTask Performance (WE) Supported
Hypothesis 2b Task ConflictContextual Performance (WE) Supported
Hypothesis 2c Task ConflictTurnover Intentions (WE) Supported
Hypothesis 3a Task ConflictTask Performance (JS) Supported
Hypothesis 3b Task ConflictContextual Performance (JS) Supported
Hypothesis 3c Task ConflictTurnover Intentions (JS) Supported
Hypothesis 5a Relationship ConflictTask Performance (EXH) Supported
Hypothesis 5b Relationship ConflictContextual Performance (EXH) Supported
Hypothesis 5c Relationship ConflictTurnover Intentions (EXH) Supported
Hypothesis 6a Relationship ConflictTask Performance (CYN) Supported
Hypothesis 6b Relationship ConflictContextual Performance (CYN) Supported
Hypothesis 6c Relationship ConflictTurnover Intentions (CYN) Supported
Hypothesis 7a Relationship ConflictTask Performance (ISW) Supported
Hypothesis 7b Relationship ConflictContextual Performance (ISW) Supported
Hypothesis 7c Relationship ConflictTurnover Intentions (ISW) Supported
WE=Work Engagement, JS= Job Satisfaction, EXH= Exhaustion, CYN=Cynicism,
ISW=Interpersonal Strain at Work
170
Chapter 6
Discussion and Conclusion
171
Discussion
Working life is characterized by individuals‘ daily interactions and
interpersonal conflict is an inherent part of this process since people with different
personal interests and professional backgrounds come together in their pursuit of
accomplishing the organization‘s goals. Researchers have devised theoretical model
of conflict types, and work behaviors (Jehn, 1995, Lu et al., 2011; Simons & Peterson,
2000). However, there still remains a great divergence between theory and empirical
evidence, particularly related to task conflict and its outcomes. More specifically, the
influence of relationship conflict on work behaviors is rather clear, the influence of
task conflict is more paradoxical (De Clercq, Rahman, & Belausteguigoitia, 2017; De
Drue & Weingart, 2003, De Wit et al., 2012). As noted earlier, this inconsistency may
be due to the dual nature of task conflict (Meier et al., 2013). Hence, the study sought
to address these inconsistencies in the conflict literature whereby the study examines
the link between task/relationship conflict, work behaviors and behavioral intentions
at individual level. Moreover, conflict research has been largely limited to main
effects. Thus, the ultimate goal of this study was to supplement the conflict literature
by exploring the potential mechanism through which task conflict and relationship
conflict in technical jobs affect work behaviors and behavioral intentions as more
thorough investigations of mechanisms that explain conflict effects is necessary to
advance theory and management of interpersonal conflict. Thereby, we aimed at
providing more insight into the processes by which task conflict and relationship
conflict translate into work behaviors. More specifically, the role of task conflict,
relationship conflict, work engagement, job satisfaction, burnout, task performance,
contextual performance and turnover intentions was studied in Pakistan‘s cultural
context.
Much of the previous research on the dynamics of workplace conflict has been
grounded in contingency perspective (Jehn and Bendersky, 2003). This perspective
has been, and still continues to be, an important framework for understanding conflict
but it did not account for the explanatory mechanisms underlying direct relationships
between conflict and work behaviors. However, results from the present study provide
an alternative perspective that draws insights from the Conservation of Resources
(COR) theory (Hobfoll, 1989) to explain how task conflict and relationship conflict
influence work behaviors and how different dimensions of workplace well-being play
172
the intervening role in conflict-work behaviors relationships. COR theory is based on
two key tenets- the resource investment/acquisition and the primacy of loss –and the
study found each tenet helpful in explaining a different path of the task
conflict/relationship conflict and work behaviors. The discussion of the study results
is centered around the research questions addressed in this thesis.
What is the impact of task conflict on (a) task performance (b) contextual
performance; and (c) turnover intentions?
Drawing from the COR theory (Hobfoll, 1989, 2001) and its resource
investment/acquisition principle, it was predicted that task conflict in technical jobs
represents a resource gain process that leads to positive outcomes in individuals since
it entails the exchange of cognitive resources. More precisely, task conflicts provide
employees with more resources which have a critical role in improving their work
behaviors as these task related perspectives enable them to work effectively and they
can think better ways of doing their jobs. Task conflict instills creativity as a result of
different perspectives held by individual (Jungst & Blumberg, 2016). Task conflicts
challenge long held beliefs resulting in improved decisions (De Wit, Jehn, &
Scheepers, 2016). From a COR theory perspective, this means that employees invest
their mental resources in task conflict through exchange of ideas, viewpoints and
contrasting perspectives (i.e., the resource investment principle) in order to gain more
resources (i.e., the resource acquisition principle) that result in better performance and
reduced turnover intentions. The results in Chapter 6 showed that task conflict was
positively related to task performance, contextual performance and negatively related
to turnover intentions of employees.
Individuals gain cognitive resources which enrich their existing reservoir of
resources that help them perform in a better way, thus improving their task
performance. In task conflict, employees come together in the pursuit of their work-
related goals, hence task conflict may serve as an opportunity to voice their
preferences (Sui, Lam, Lyu, & Lee, 2016) and learn from each other‘s perspectives
and creative insights (De Clercq et al., 2017), and induce helping behaviors. These
activities help improve their contextual performance. Additionally, enhanced
understanding of the task at hand, better performance and cooperation may improve
individuals‘ attachment with their organization. This results in decrements in turnover
173
intentions. These results are consistent with the literature as task conflict has shown
positive relationship with work attitudes and behaviors (Behfar et al., 2011; De Drue,
2006; Jehn, 1997; Lu et al., 2011; Matsuo, 2006; Parayitam and Dooley, 2009;
Tjosvold, 2008). While most of this research informs about the conditions under
which conflict is either positive or negative, our study explicates that process through
which task conflict leads to positive outcomes in individuals. What makes this study
distinct from previous research that also tapped its potential benefits such as exchange
of creative perspectives (De Clercq et al., 2017) is that it brings forth the unrealized
potential of task conflict within a particular context of technical jobs. The findings
provide important insights into the ways telecom engineers build on each other‘s
perspectives during task conflicts which improve their overall performance and
contribute towards weaker turnover intentions. This is not surprising, given that task
conflict have been shown to be somewhat dependent on context in which it occurs (Lu
et al., 2011), and that different effects (positive or negative) may be foregrounded or
accentuated in different contexts. Furthermore, based on the resource
investment/acquisition principle of the COR theory, it was predicted that work
engagement and job satisfaction mediate the relationship between task conflict and
task / contextual performance and turnover intentions.
Is the relationship between task conflict and task/contextual performance and
turnover intentions mediated by work engagement?
It was argued that when employees discuss their task related issues, they
exchange ideas and assimilate new information, which in turn makes them more
engaged in their work, thus eventually resulting in organizationally valued outcomes.
The results of the structural equation modeling generally supported the proposed
relationships. Specifically, it was found that as hypothesized, task conflict was not
only related to task / contextual performance and turnover intentions but also
indirectly through work engagement.
In addition, our results indicated that task conflict plays a significant role in
fostering work engagement and via work engagement also better task/contextual
performance and low turnover intentions. However, work engagement fully mediated
the relationship between TC-TP, and between TC-CP, but partially mediated the link
between TC-TI. Particularly the finding related to the full mediation of work
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engagement in the link between task conflict-task performance and with that of
contextual performance explains that work engagement leads to improved
performance and helping behaviors in individuals and also negatively impacts the
withdrawal behaviors such as turnover intentions. Although previous research has
documented positive relationship between task conflict and work behaviors (Lu et al.,
2011; Chen et al., 2011; Jehn 1997), the present study delineates the underlying
mechanism through which task conflict translates its effect to work behaviors.
This finding is consistent with the corollary of the COR which state that
individuals invest resources to increase their existing reservoir of resources and initial
resource gain manifest as gain spirals. More precisely, the results suggest that task
conflict in complex jobs may function as a resource that builds more resources in the
form of engagement, which in turn, affects both forms of performance positively and
intention to leave negatively. The positive link between challenging demands and
work engagement concurs with previous studies in a different organizational setting
(Karatepe et al., 2014). Moreover conflict researchers (De Clercq et al., 2017) contend
that individuals may experiences a sense of fulfillment as a result of expression of
contrasting viewpoints. In view of this evidence, it is reasonable to assume that
individuals experiencing task conflict in non-routine complex jobs will be more
engaged in their work (task performance), will exhibit a greater tendency to help each
other through constructive task related discussions, thus exchanging useful
information (contextual performance) and this work engagement also increases their
emotional attachment with their jobs (Schaufeli & Bakker, 2004; Van Beek et al.,
2014), hence reduces intention to leave. Our findings are consistent with previous
conflict studies in which task conflict was found to be beneficial as it helped uncover
disparity in perceptions, interpretation and practices (Floyed and Lane, 2000),
increased deep deliberations on information (Ford, Ford, and D‘Amelio, 2008), and
motivated and mobilized managers into taking action (Regner, 2003). However, our
findings advance the previous evidence by delineating the underlying psychological
process through which task conflict affects work behaviors.
Is the relationship between task conflict and task/contextual performance and
turnover intentions mediated by job satisfaction?
175
The study tested the mediation of job satisfaction in task conflict-work
behaviors relationship. Our findings revealed that task conflict influences task
performance and contextual performance positively, and turnover intentions
negatively and these relationships are mediated by job satisfaction. Nonetheless, job
satisfaction fully mediated the relationship between TC-TP, and that of TC-CP, but
partially mediated the link between TC-TI. Todorova et al., (2014) stated that task
conflict affects job satisfaction positively through positive emotions. Later, these
findings were revalidated by Rispens and Demerouti (2016) in which they stated that
task conflict may elicit positive emotions and excitement through constructive
discussions. Taking insights from these studies, our study establishes a positive
relationship between task conflict and job satisfaction based on the theoretical
underpinnings of the gain spirals corollary of the COR theory. The present study
offers an additional insight into the linking mechanism by suggesting job satisfaction
as a plausible mediator, and our findings support our assumption. While job
satisfaction is recognized to be a fundamental outcome for study purposes in its own
right, so there is particular interest in building empirical insights in this study in
relation to its mediating effects. These findings corroborate our theoretical
assumptions that task conflict motivates employees as they voice their differing
opinions and perspectives which makes them more focused, engaged and satisfied
with their jobs which in turn is related to better performance and lower turnover
intentions.
Our findings indicate that technical employees exchange their cognitive
resources during task conflict with their coworkers, and are more capable of
orchestrating resource gain, thus more likely to engage in constructive discussions
regarding how to accomplish work tasks. This makes them more engrossed in their
work and also contributes towards enhancing their sense of satisfaction. This resource
investment/acquisition leads to resource accumulation or gain spirals which manifest
in the form of engagement and job satisfaction-both being indicators of workplace
subjective well-being. Furthermore, mediating roles of work engagement as well as
that of job satisfaction help us better understand why and how task conflict positively
relates to individuals‘ performance and strengthens their bonding with their
organizations in the form of reduced turnover intentions. This is an interesting finding
showing that task conflicts can be energizing and motivating in themselves through
cognitive exchange of differing ideas, viewpoints and perspectives.
176
What is the impact of relationship conflict on (a) task performance (b) contextual
performance; and (c) turnover intentions?
Relationship conflict is an important issue for both managers and employees
which has been consistently related to negative outcomes such as low job satisfaction
and performance (Nifadkar & Bauer, 2016; De Drue & Weingart, 2003; De Wit et al.,
2012), and withdrawal behaviors (Avgar et al., 2014). These harmful effects demand
that researchers gain a clear and deep understanding of relationship conflict.
Moreover, it also explores the underlying mechanism linking these direct
relationships with the help of the conservation of resources (COR) theory. More
specifically, the role of relationship conflict, job burnout, task performance,
contextual performance and turnover intentions was studied in Pakistan‘s cultural
context and most of our study hypotheses were supported.
Consistent with the study‘s theoretical framework derived from the primacy of
loss principle and ‗loss begets loss (loss spirals)‘ corollary of the COR theory which
states that initial loss of resources leads to further loss of resources that leads to
negative outcomes in individuals (Hobfoll, 2001), the results revealed a significant
negative relationship between relationship conflict and task/contextual performance
and significant positive relationship between relationship conflict and turnover
intentions. These findings concur with the findings of the previous research on the
direct link of relationship conflict and individuals‘ outcomes (Afzal et al., 2009;
Avgar et al., 2014; Bear et al., 2014; Ismail et al., 2012; Kacmar et al., 2012;
Kurtzberg & Mueller, 2005; Lu et al., 2011; Nifadkar & Bauer, 2016; Zhang &
Zhang, 2012). This research also provides further evidence of the detrimental impact
of relationship conflict for effective organizational and employee functioning. The
results also corroborate our theoretical reasoning using the lens of COR theory that
relationship conflict triggers a loss process that leads to dysfunctional individuals
outcomes. These results also corroborate findings of Nifadkar and Bauer (2016) that
individuals experiencing relationship conflict fail to gain adequate resources to sustain
their performance and withdraw their interactions with their coworkers.
Is the link between relationship conflict and task/contextual performance and
turnover intentions mediated by job burnout (exhaustion, cynicism, and
interpersonal strain at work)?
177
We argued in our study that when individuals undergo relational tensions, they
are more likely to show symptoms of burnout. Our analyses revealed that relationship
conflict was positively related to job burnout (exhaustion, cynicism, and interpersonal
strain at work) and each dimension distinctively mediated the link between
relationship conflict-task performance, relationship conflict-contextual performance
and relationship conflict-turnover intentions. Exhaustion fully mediated the link
between relationship conflict- and work behaviors-task performance, contextual
performance and but partially mediated the link between relationship conflict and
turnover intentions. Cynicism i.e., unwillingness to exert effort, fully mediated the
link between relationship conflict-task performance, and relationship conflict-
contextual performance, and partially mediated between relationship conflict and
turnover intentions. The third dimension of job burnout-interpersonal strain at work
fully mediated the link between relationship conflict-task performance and
relationship conflict-contextual performance. Nonetheless, interpersonal strain at
work partially mediated the link between relationship conflict and turnover intentions.
The reason for partial mediation may account for other factors such as workplace
bullying/mobbing outside the scope of this research.
These findings corroborate the hypothesis of a resource depletion process
whereby relationship conflict deprives the individuals of their social associations at
workplace, resulting in depletion of resource more quickly, thus likely affecting their
work behaviors. What is especially noteworthy about these findings is the implication
that the three burnout dimensions have a differential effect for mediating different
outcomes, underscoring the distinct nature of these constructs. In the link between
relationship conflict and work behaviors i.e., task/contextual performance, and
turnover intentions, the three dimensions distinctively contributed towards work
behaviors which imply that relationship conflict affects these behaviors through
independent contribution of each dimension of burnout. This also corroborates our
hypothesis that when people undergo relationship conflict, they cut off their social
ties, lose their concentration and resolve to work, are no more co-operative towards
each other, and their disengaged indifferent attitude decreases their task and
contextual performance. Hence, a loss of social relationships gives rise to other losses
and these loss spirals are accompanied by loss of cognitive resources, energy
resources and social resources. Likewise, relationship conflict affects turnover
intentions strongly through mediation of these three dimensions. It indicates that
178
relationship rifts can have serious repercussions through different dimensions of job
burnout for individuals as well as their organizations since individuals lose their
interest in their work and their commitments/attachment with their coworkers (Maertz
& Griffeth, 2004; Reichers, 1985) and this results in greater intent to leave their
organizations as the social network which glues individuals together for their smooth
functioning is no longer supportive. These findings explicate the underlying process
that ultimately translates relationship conflicts with peers into decreased
task/contextual performance and increased turnover intentions. This also attests to our
predictions that strain (burnout) results from perceived poor social relations at work
(Spector & Fox, 2002). The preceding discussion suggests that when employees
encounter relationship conflict at workplace, they develop burnout which ultimately
translates into dysfunctional job outcomes. The study contributes beyond conflict
studies specifically on the link between relationship conflict and individual outcomes
(Afzal et al., 2009; Bear et al., 2014; Kacmar et al., 2012) as the present study has
delineated an underlying mechanism that links relationship conflict with individual
outcomes.
All in all, the study findings suggest two different linking mechanisms that
connect task conflict and relationship conflict to work behaviors. Although previous
research has documented positive relationship between task conflict and work
behaviors (Lu et al., 2011; Chen et al., 2011; Jehn, 1995), the present study delineates
the underlying mechanism through which task conflict translates its effect to work
behaviors through work engagement and job satisfaction. The findings of the study
also indicate that in a collectivist society where social harmony is valued as compared
to individualist culture (Ayoko, 2016; Chen, Chen, & Meindl, 1998) and relational
concerns are extremely salient (Halevy et al., 2012), relationship conflict can be
extremely disruptive and threatening (Way, Jimmieson, Prashant, & Bordia, 2016)
and has the potential to transform into severe psychological problems which may
manifest as job burnout and can be damaging for the individuals and their
organizations alike. This also adds to generalizability of findings carried out in a
collectivist culture with that of the western individualist cultures.
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Table: 6.1: Key Findings of the Study
Sr. No Findings
1 Task conflict positively related to task performance, contextual
performance and negatively related to turnover intentions of employees.
2
Work engagement mediates the link between task conflict and
task/contextual performance and turnover intentions.
However, work engagement partially mediated the relationship between
TC-TP, and TC-CP, but fully mediated the link between and TC-TI.
3
Job satisfaction mediates the link between task conflict and task/contextual
performance and turnover intentions. Nonetheless, job satisfaction partially
mediated the relationship between TC-TP, and that of TC-CP, but fully
mediated the link between TC-TI.
4
Relationship conflict negatively related to task/contextual performance and
significant positive relationship between relationship conflict and turnover
intentions.
5
Relationship conflict was positively related to job burnout and each
dimension (exhaustion, cynicism, and interpersonal strain at work)
distinctively mediated the link between relationship conflict-task
performance, relationship conflict-contextual performance and relationship
conflict-turnover intentions.
6
Exhaustion fully mediated the link between relationship conflict- and work
behaviors-task performance, contextual performance and fully mediated the
link between relationship conflict and turnover intentions.
7
Cynicism i.e., unwillingness to exert effort, partially mediated the link
between relationship conflict-task performance, relationship conflict and
contextual performance. However, cynicism partially mediated between
relationship conflict and turnover intentions.
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6.1 Research Contributions
The present study makes significant theoretical and substantive contributions
to the extant conflict literature in several ways. The primary aim was to illustrate the
conflict-work behaviors association at the level of the individual as well as to explore
the underlying mechanisms linking these direct relationships. The conflict research
has documented that task and relationship conflicts are often related (De Drue &
Weingart, 2003; De Wit et al., 2012), the results of the current study offer a different
perspective. Developing an understanding of the relationship between these variables
is important because of the implications of conflict types for individuals and their
organizations. Furthermore, this study also extends previous research by seeking to
explain the processes that influence the conflict and work behaviors relationship.
The conflict research has so far treated conflict as a shared perceptual property
of all group members by focusing mainly on team level. The main theme of this
research was that individuals in groups share an equal amount of conflict. The two
most notable meta-analyses by DeDreu and Weingart (2003) and the other by De Wit,
Greer and Jehn (2012) investigated the impact of task conflict and relationship
conflict on group performance and team member satisfaction. De Wit, Greer and Jehn
(2012) also measured the impact of process conflict and included outcome variables
like group performance, intragroup cohesion, trust, group members‘ intention to
remain in the group, and group member satisfaction and commitment. That is, conflict
researchers have consistently overlooked that individuals and groups may not, of
necessity, converge on the same parameters. Since researchers (Jehn et al., 2010; Lu
et al.2011) argue that individual level responses should not be aggregated to team
level, and that the perceptions of individuals differ about one and the same conflict
(De Wit, Jehn, & Scheepers, 2013), therefore, the present study made an effort to find
the plausible mediators in the relationship of task conflict, relationship conflict and
task performance, contextual performance and turnover intentions of employees at
individual level.
8
Interpersonal strain at work fully mediated the link between relationship
conflict-task performance and relationship conflict-contextual performance.
Nonetheless, interpersonal strain at work partially mediated the link
between relationship conflict and turnover intentions.
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First, this study contribute to the major debate in the conflict literature
regarding the influence of task conflict and relationship conflict on employees‘ work
behaviors (Amason and Loughry, 2014; De Wit at al., 2012, Solansky et al., 2014).
The striking aspect of the finding is that task conflict and relationship conflict
differentially predicted task/contextual performance and turnover intentions. Our
theoretical framework was successful in revealing two different processes responsible
for task/contextual performance and turnover intentions owing to conflict types. The
first process can best be described as a resource investment/acquisition process. More
precisely, task conflict positively influenced task performance, contextual
performance, and negatively influenced turnover intentions. Both work engagement
and job satisfaction (positive indicators of workplace subjective well-being) mediated
these direct relationships. This finding is important for organizations as well as
managers to consider in terms of employees performance and well-being given the
universality of these variables to employees as well as organizations alike. After all,
our data indicate the task conflict is not only positively related to job performance
(task as well as contextual), but also predictive of their intentions to stay or leave the
organization (as measured by turnover intentions).
The second process is resource depletion process, and starts with the
occurrence of relationship conflict where it was found to be negatively associated
with performance (task/contextual) and positively associated with turnover intentions.
The three dimensions of burnout (indicator of impaired well-being) distinctively
mediated the link between relationship conflict and work behaviors. These findings
reflect the necessity to identify distinctive associations of task conflict and
relationship conflict with organizationally valued outcomes. By doing so, we hope to
stimulate new theorizing and research in these areas by allowing researchers to
compare their work vis-à-vis others, and explore the distinctive patterns of behaviors
commensurate with conflict types. This evidence also paves the way for future
research to explore this distinctiveness of conflict types in other professional domains
and also breathes optimism into the research on task conflict that advocates its
positive effects.
Second, with regards to workplace subjective well-being, our study
contributes by clarifying the most relevant dimensions of well-being at work whereby
it distinguishes between positive (work engagement, job satisfaction) and negative
(dimensions of burnout) indicators of well-being. Specifically, our findings suggest
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that positive indicators of well-being mediate the path between task conflict and work
behaviors and negative indicators of well-being mediate the path between relationship
conflict and work behaviors. Our approach is in line with the well-being concept
presented by Diener et al., (2003) and Warr (2007), later on advanced by Bakker and
Oerlemans (2011). By conceptualizing mediators in this way, and by finding evidence
supporting this conceptualization, our study contributes to existing theory and
research on workplace subjective well-being. Specifically, it highlights the possibility
that positive effects of task conflict channel their effect through work engagement as
well as job satisfaction to task/contextual performance and turnover intentions.
Furthermore, negative effects of relationship conflict channel their effect through
three dimensions of burnout which independently and concomitantly contribute to
these individual outcomes.
The third contribution of this study is to provide a more holistic view of the
consequences of task conflict and relationship conflict by including three work
behaviors i.e., task performance, contextual performance and turnover intentions of
employees which are key indicators of organizational effectiveness (Newton &
Jimmieson, 2009). Behavioral intentions and work behaviors are ‗the most pivotal and
enduring set of constructs at individual level organizational research‘ (Harrison,
Newman, & Roth, 2006). These criterion variables apart from task performance have
received little attention in conflict studies (Choi, 2010). In addition, the purpose is to
comprehend whether the links between interpersonal conflict and attitudinal
consequences differ from those between interpersonal conflict and behavioral
consequences. Furthermore, the study used supervisory ratings of task/contextual
performance in order to provide more objective view of the performance. In this way,
the study has also answered the call of Puck and Pregernig (2014) to use supervisor-
rated performance to measure the effect of interpersonal conflict.
The study contributes significantly to the conflict literature, which has
predominantly focused on portraying conflict as a stressor (De-Drue, 2008; Dijkstra,
De Dreu, Evers, Dierendonck, 2009) and ignored the role of task conflict as a
resource which has the potential of initiating a motivational process which may lead
to positive outcomes in individuals. Although prior research has established an
association between task conflict and positive work behaviors (Ehie, 2010; Lu et al.,
2011; Parayitam & Dooley, 2009; Todorova et al., 2014), there has been relative
silence on the underlying mechanisms through which task conflict leads to positive
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outcomes in individuals. Building on the existing literature on task conflict (Sui, Lam,
Lyu, & Lee, 2016), we tested a mediating model that link task conflict with work
behaviors. The findings of the study lend strong credibility to the notion that task
conflict is not inherently negative and has the potential to positively affect well-being
and ultimately individuals‘ outcomes.
Moreover, it contributes to the literature on work engagement and job
satisfaction by highlighting their mediating roles for such behaviors. Based on the
conceptualization of the task conflict as a resource in technical jobs in the backdrop of
the COR theory, the study has found some very interesting evidence. First, our
findings revealed that task conflict is significantly related to task performance,
contextual performance and turnover intentions of individuals and these relationships
are mediated by work engagement and job satisfaction. The results support the
resource investment/acquisition tenet of the COR in which exchange of cognitive
resources i.e., task conflict resulted in more resources or gain spirals which manifest
as engagement as well as satisfaction among employees. These findings confirm our
assumption that task conflict in challenging jobs acts as a resource for employees and
fosters work engagement and job satisfaction through task related discussions and
multiple perspectives presented and exchanged by employees.
Furthermore, this study responds to Christian et al.‘s (2011) research call by
testing work engagement as a mediator that may simultaneously result in task
performance as well as contextual performance and help decrease propensity to leave
the jobs. The findings of the study are robust in the sense that both task and contextual
performances were rated by the supervisors. From a practical point of view, task
conflict in complex jobs has the potential to initiate a motivational process that leads
to positive behaviors in individuals, therefore, task conflict should not be considered
as a stressor but a resource in context of technical jobs which can energize the
individuals and bring forth positive outcomes to the benefit of the organizations.
Likewise, the relationship conflict is hypothesized to negatively impact task
performance, contextual performance and positively impact turnover intentions
through mediation of different indicators of job burnout. This path has been
explicated through the ‗loss begets loss‘ corollary of the COR theory. The study
broadened our knowledge of relationship conflict by examining job burnout as an
important variable in the link between relationship conflict at work and its possible
consequence for individual outcomes. We found a significant positive association
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between relationship conflict and different dimensions of job burnout that was further
transmitted to negatively influence a broad spectrum of job performance and
positively influence turnover intentions. In doing so, exhaustion, cynicism and
interpersonal strain at work, the psychological vital signs that are core indicators of an
individual‘s impaired well-being i.e., burnout, differentially mediated the link
between relationship conflict and work behaviors. Assessment of these vital signs of
burnout may provide meaningful information and understanding of their role as
mediators that can independently transmit the effect of relationship conflict to
performance and turnover intentions. In this way, the current research has extended
the past literature (Jungst & Blumberg, 2016) by examining the separate contribution
of each dimension of burnout to better understand the impact of relationship conflict
on work behaviors.
The findings indicate that job burnout serves as a key intervening mechanism
that explains associations among relationship conflict and work behaviors. It also
suggests that for task/contextual performance, and turnover intentions that the unique
contributions from relationship conflict may be accounted for by burnout. It is not just
that relationship conflict perceived as stressful and threatening for social fabric
(Hopkins & Yonker, 2015), results in burnout, which saps energy that could otherwise
be applied to activities that contribute to organizational effectiveness. Rather,
relationship conflict also has other negative outcomes as a result of burnout in the
form of withholding of performance related contributions and increase in withdrawal
behaviors as employees tend to cut off their social ties, thus losing social resources
(Hill, Chênevert, & Poitras, 2015). In addition, this study contributes to the broader
work stress literature, as future investigations of relationship conflict may provide
additional insight into how organizations should structure interventions and wellness
programs that curb the negative effects of unavoidable stressors in the work
environment.
At the more specific level, our study contributes to theory by offering and
testing a theoretical model guided by the tenets of the COR theory whereby the study
tests two competing perspectives by delineating contrasting psychological processes
that explain why task conflict and relationship conflict have different relationships
with work behaviors. Indeed, the most important contribution of the present research
derives from the fact that consideration of the different indicators of workplace
subjective well-being-engagement, job satisfaction and burnout-is essential to
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understanding the linking processes between conflict and performance (both task and
contextual) and turnover intentions-central concepts in organizational behavior, and
management research, thereby bridging sub-disciplines of conflict, psychology and
organizational behaviors. Moreover, this study investigated the dynamics of
interpersonal conflict, workplace subjective well-being and work behaviors in
participants who were employed individuals-telecom engineers by profession, thus
providing a unified framework under which to study these constructs in the
workplace. These study constructs deserve attention in their own right.
Our study highlighted a series of important pathways using COR theory for
understanding dynamics of interpersonal conflict and work behaviors at individual
level. Our focus specifically on dynamics of conflict types and individual level
outcomes is especially important because conflict can be best understood by taking
into account individual level differences where these phenomena are more discernible
and might have the most potential to be invigorating or depleting to the individuals. In
this way, our study helps expand the set of theoretical lenses beyond the contingency
perspective suggested by Jehn and Bendersky (2003), which might help us better
understand the psychological processes underlying the conflict-work behaviors, and
makes unique contributions to the relevant research. These different approaches
should not be viewed as mutually exclusive, but instead as different lenses that
highlight diverse aspect of the same phenomenon. For instance, the contingency
perspective suggests that the positive or negative effect of task or relationship conflict
depends upon the context in which the conflict occurs, which determines the nature of
their effect, whereas the COR framework adopted in this study addresses why and
how task and relationship conflict differentially relate to work behaviors.
Furthermore, the conceptual and empirical evidence we provide between interpersonal
conflict, workplace subjective well-being and work behaviors further provide a bridge
between the literature informing this area, and opens up new avenues for both the
theoretical development and empirical research. These findings are noteworthy as
they extend nomological network of outcomes related to conflict, and because
performance was supervisor-rated, which helps to minimize common source bias
concerns (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003).
These findings also support Hakanen and Schaufeli‘s (2012) contention that
―experiences at work are particularly important for the individual‘s overall level of
well-being and mental health.‖ Finally, while task conflict and relationship conflict
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have been heavily studied in work groups and teams, these have not been extensively
studied at individual level. It is for this reason that the evidence on the mediating
effect of different indicators of workplace well-being in the relationship between
conflict types and work behaviors is an important first step en route to further
theorizing and empirical verification. Our view on conflict through such a paradigm is
by investigating factors that transmit the effect of task conflict and relationship
conflict to work behaviors is the main contribution we offer to the conflict literature.
Considering the implications of interpersonal conflict on individuals as well as
organizations-the continuous expansion of field of conflict seems both logical and
inevitable.
6.2 Research Limitations
Although this study has come up with some very interesting findings for
organizational theory and application, there are several limitations of our study which
invariably inform important avenues for future research. First, while the approach
used in this study whereby employees‘ provide ratings of their independent variables,
mediators, and turnover intentions, and their supervisors provide ratings of their task
and contextual performance, excludes the possibility of common method variance
(Podsakoff, Mackenzie, Lee, & Podsakoff, 2003), our data are cross-sectional like
most studies published in organizational behavior.
We assumed unidirectional view of relations among the study variables and
owing to the cross-sectional design the present research did not systematically
examine the temporal sequence of the principal variables, hence alternative pathways
cannot be ruled out. The reverse causality could not be established and it may not be
inferred whether independent variable caused dependent variable or vice versa. The
survey was conducted over two months and was administered to the respondents at a
single point in time. Although the structural equation modeling approach is capable of
examining increasingly complex relationships among variables, such correlational
analysis cannot be termed as causal. However, the conclusions drawn follow
conceptual logic, theoretical reasoning and supportive findings.
The specific sample of telecom managers constitutes another delimitation of
the present study, hence we must cautiously draw conclusions regarding the
generalizability of the results to working populations outside the telecom sector due to
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considerable contextual variance that can also affect the generalizability of findings.
As Johns (2006, p.389) states, ‗‗context is likely responsible for one of the most
vexing problems in the field; study-to-study variation in research findings‘‘. Hence,
there is a likelihood that certain features of the research context may have contributed
to our results such as work design as well as working environment. Stasser, Stewart,
and Wittenbaum, (1995) state that when respondents are identifiable, they are more
likely to discuss and share unshared information. We may attribute the positive results
of task conflict to this feature of our sample as telecom engineers due to their similar
professional identity are more likely to discuss task problems openly and reap the
benefits associated with it since they do not feel pressured as there are no power
differentials. Thus, we encourage replicative research in additional more diverse
samples that would allow for a more systematic assessment of sample-specific
characteristics and also to better establish the generalizability or boundary conditions
of our relationships.
Similarly, because we focused exclusively at the managerial level, we are
unable to discern whether such findings would replicate for lower (e.g., technicians,
foremen etc.,) or higher-level (e.g., chief-managers/engineers) positions. Moreover,
the contrasting results of task and relationship conflict may be more or less relevant
for other occupations that are less professional (i.e., not highly
educated/trained).Hence, these findings may be associated with the peculiarities of
this particular sample. However, focusing on a homogeneous sample of telecom
engineers somewhat eliminates confounding factors such as occupational differences
that could have a role otherwise. Additionally, the sample of this study provided
valuable insight into the impact technical professions have on interpersonal conflict,
well-being and work behaviors, an insight which could never have been achieved in a
professionally diversified sample. The technical staff i.e., telecom engineers who
comprise the sample also bring unique and high levels of training and expertise to
their field.
Another promising direction for future research is to conduct cross-industry
comparisons. For this purpose, research indifferent occupational groups such as
research on service providers (doctors/nurses/lawyers/public v/s private sector
employees/educationists etc.,), will help generalize our results to a broader labour
market to see whether the impact of task conflict and relationship conflict on work
behaviors differs according to the organizational context. Such a research will surely
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yield interesting insights for researchers and practitioners and will also add to the
generalizability of findings.
6.3 Directions for future research
The results of our study lead to a number of fruitful directions for future
research. First, we invite future researchers to examine our hypotheses in a
longitudinal study (e.g., Bauer, Erdogan, & Liden, 2006), to replicate the cross-
sectional findings and to establish the causal sequence among the study constructs,
and the extent to which this association is explained by principles of conservation of
resources theory. This would help to answer the questions related to how task/
relationship conflict, indicators of subjective well-being and individual outcomes
change over time and how the mediating effect of work engagement, job satisfaction
and burnout becomes either more or less pronounced. Such research will add to the
current findings and will also consolidate the proposed mediation theory in greater
depth, thus indicating the causality patterns that link the variables we studied
presently. Moreover, qualitative research, using direct observations and in-depth
interviews could yield additional insights on the dynamics of task and relationship
conflict, and work behaviors.
Another direction is to examine these phenomena at different levels since the
present study focused on the implications of interpersonal conflict among managers,
which means horizontal conflict i.e., conflict between peers was studied. An
interesting avenue for future studies would therefore be to take into account vertical
conflict i.e., conflict between supervisors and subordinates and explore its
implications since Frone (2000) contends that conflict with coworkers differs in terms
of outcomes as compared to conflict with supervisors. Therefore, perspectives from
multiple sources would lead to an enhanced understanding of the workplace conflict
and ensuing behaviors.
It is conceivable that well-being (both positive and negative) constitutes a
mediator between conflict-work behaviors, as has been demonstrated by study
findings. This is not to suggest that paths through studied indicators of well-being are
the only one leading to work behaviors, but these indicators of workplace well-being
served as explanatory mechanisms that explained relevant amount of variance in each
sequence. However, there may be more plausible mediators between task conflict-
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work behaviors such as other dimensions of well-being such as workaholism, positive
effect, etc., not explored in this study, may mediate the direct relationships. We
encourage researchers to further unlock the ‗black box‘ by investigating additional
intervening mechanisms and boundary conditions of the conflict and broader work
behaviors link.
Likewise, there may be more putative mediators between the link of
relationship conflict and work behaviors such as cognitive distraction from the tasks,
denial of help, biased use of information etc., which have not been measured in the
current study. Additionally, we also suggest including context-free indicators of well-
being such as psychosomatic complaints, and health-related problems such as
depressive symptoms and sleeping deprivation, particularly in the link between
relationship conflict and work behaviors. These forms of resource depletion could be
examined both independently and in co-occurrence with each other or with other
resource depletors. Given that employees spend around half of their waking hours at
work, it becomes important avenue for studying well-being. For this reason,
continuous research aimed at improving our understanding of the pathways leading
from task and relationship conflict to important work behaviors is of crucial
importance. Future studies can incorporate these mediators and gauge their impact on
direct relationships.
We did not include any moderators or boundary conditions in the study, future
research should focus on potential dispositional, motivational or situational
moderators that may affect the conflict-work behaviors relationship. Research in this
direction may uncover important insights into our understanding of the conflict
dynamics in organizations. Although participants in our sample were from telecom
sector and had similar job responsibilities (worked in design and analysis of telecom
services), it may be that contextual characteristics such as job type influence the
pattern of findings. It also would be interesting to examine the potential interactions
between task conflict, relationship conflict and contextual features such as work
climate. Furthermore, research on plausible moderators seems warranted. Given that
there may be other individual/dispositional, organizational, and non-work factors that
also affect and moderate conflict-well-being relationship, we encourage researchers in
this area to explore these factors in the future.
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This study used task conflict and relationship conflict as predictor variables,
future studies may incorporate process conflict and gauge its impact on employees‘
well-being, attitudes and work behaviors. However, extant research suggests that
there are measurement problems with process conflict as it failed to demonstrate
adequate discriminant validity to distinguish it from task conflict (Behfar, Mannix,
Peterson, & Trochim, 2011). We also suggest that it is also essential to learn more
about how task conflict and relationship conflict might affect each other over time as
in the present study we did not test their interactive effects.
The present study employs task versus contextual distinction to identify
performance behaviors. There are other dimensions of performance, such as counter-
productive work behaviors which should also be taken into account in future research
particularly in the context of relationship conflict which might uncover how
relationship conflict relates to behaviors such as mobbing, bullying or intimidating
that have practical implications for employees‘ well-being and work behaviors.
Including these different dimensions might provide valuable additional insights into
the conflict-performance relationship. Future researchers should also attempt to gauge
more objective measures of performance such as productivity, efficiency, or quality
since in present study both dimensions of performance were gauged by employees‘
supervisor, which still represents a subjective assessment of performance. Looking
beyond job performance and turnover intentions which are considered key individual
outcomes (Kahya, 2007), research could examine whether the mechanisms we suggest
apply to other work outcomes of interest to organizations and their employees such as
innovation, commitment and counterproductive work behaviors. Subsequent work
should expand this area by looking at other types of strains such as physical
symptoms and ill health as plausible outcome of workplace stressors. For instance, it
could be interesting to see how relationship conflict relates to different health
problems and depressive symptoms. Alternatively, it could be worth exploring how
task conflict could affect other motivational states such as commitment, and job
involvement etc. In demonstrating relationships between task conflict, relationship
conflict and work-related outcomes including but not limited to those documented
above, researchers could demarcate the range of outcomes pertinent to task conflict
and relationship conflict and illuminate further the benefits- and limitations –of both
types respectively in organizations. Future research may also determine the extent to
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which our results are context-specific. Additional research is also needed into conflict
perceptions and well-being from differentiated sources in other environments.
Interventions to attenuate the deleterious effects of relationship conflict can
occur at either the individual or the organizational level and typically include a
combination of both. Furthermore, intervention studies that would suggest employees‘
trainings to deal with relationship conflict would benefit practice leaders as well as
academic researchers are warranted which may contribute to resilience and can help
prevent drifting into destructive relationships. Employee-oriented interventions are
therefore highly desirable for both practical and theoretical reasons because the
phenomenon has enormous implications both for individual well-being and for
organizational effectiveness as it involves loss of critical resources (Nifadkar &
Bauer, 2016). These training interventions should try to reduce potential negative
stress reactions of relationship conflict but also create awareness of the negative
consequences of mental and behavioral trade-offs involved. These interventions may
help individuals transform themselves into effective and socially integrated
employees. It would be worthwhile to examine the ultimate effect of such
interventions on individuals‘ approaches to manage relationship conflicts. Further, it
should be ensured that individuals as well as their organization can reap the full
benefits of interventions designed to reduce the negative effects of this potent, and
increasingly prevalent, workplace stressor.
Finally, our findings come from collectivistic settings. ―Culture influences
perceptions, reactions, and expressions of conflict‖ (Shaw et al., 2011), and it may be
inferred that the differential impact of task conflict and relationship conflict is the
result of socio-cultural norms and beliefs. For instance, collectivists may consider
their tasks as shared responsibility and may not consider task conflict as threatening.
Likewise, relational harmony is highly valued in collectivist culture, and naturally
relationship conflict represents a serious threat to the well-being of individuals, doing
severe damages in the form of burnout and diminished performance and increased
withdrawal behaviors. Hence, we encourage future researchers to conduct more cross-
cultural research to extend the generalizability of findings across different cultures.
Such a research will surely yield interesting insights for researchers as there are vast
differences in the social and cultural environments between various geographical
regions.
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6.4 Theoretical Implications
This study has yielded several significant findings, which are important for
academic understanding and practical insight for organizations. First, a critical
contribution of the current research is the application of COR theory as a novel
theoretical framework in examining conflict and work behaviors relationship and the
underlying mechanisms linking these relationships. This come amidst calls for further
theorizing in the broader conflict and work behaviors link (Amason and Loughry,
2014; De Wit et al., 2012), providing unique insights into previously untested
underlying processes. While COR theory is popular in occupational health
psychology, it has not yet been introduced into the conflict literature to understand
how conflict impact individual outcomes such as task performance, contextual
performance and turnover intentions. Through the adoption of COR, the thesis
identified and empirically tested two key underlying mechanisms linking task conflict
and relationship conflict to work behaviors.
At a group level, much research has focused on contingency perspective
propounded by Jehn and Bendersky (2003) that explained the conditions under which
conflict can be constructive or destructive. Although informative as to employees‘
general tendencies, this perspective could not account for the explanatory mechanisms
underlying conflict and work behaviors. Based on our findings, we suggest that the
COR theory offers a promising opportunity for understanding why and how task and
relationship conflict predict task/contextual performance and turnover intentions of
employees. By adopting investment/acquisition principle of the COR theory, and
related corollary of gain spirals, we examined that task conflict and work behaviors
relationship and tested work engagement and job satisfaction as explanatory
mechanisms between this direct relationship. Taking a lead from primacy of loss
principle and related corollary of loss spirals, we explored the relationship conflict-
work behaviors link, and mediations of three dimensions of burnout. At this point, it
is important to notice the relevance of both motivational and resource-draining
processes to understand the implications of task conflict and relationship conflict
respectively on technical employees. Both of these insights are of high intuitive and
practical value for understanding the differential impact of task conflict and
relationship conflict on work behaviors. These processes provide additional
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information on the way resource gain as well as resource depletion processes affect
work behaviors.
We contribute to the COR literature by corroborating resource
investment/acquisition principle in the task conflict-work behaviors relationships. The
findings also provide evidence for the ―engines‖ that drive the effects of task conflicts
to work behaviors. These engines are work engagement and job satisfaction which
served as explanatory mechanisms. We demonstrate how employees build on
resources (gain spirals) ensuing task conflicts which manifests as making them more
immersed in their work and deriving satisfaction from these cognitive exchanges of
ideas, viewpoints and concepts.
With regards to relationship conflict, this study supports our findings with the
help of the resource depletion process of the COR theory which states that
relationship conflict is one of the antecedents of the job burnout that leads to
deleterious outcomes in individuals. Consistent with the primacy of loss principle of
the COR theory (2001), and the corresponding corollary that initial loss of resources
begets further loss of resources which becomes loss spirals (Hobfoll, 2001), this study
empirically proves that individuals lose their social ties as a result of relationship
conflict, and this loss leads to impaired well-being i.e., job burnout, thus ripping-off
more resources and making individuals ill-equipped to deal with the demands of
work. This resource depletion process leads to poor performance behaviors as well as
extreme consequences such as an increased intention to leave the job since individuals
do not have sufficient resources to cope up with the demands of their jobs. This
finding is a valuable contribution to the conflict research as it explicates the route
from relationship conflict to important individuals‘ outcomes.
From a theoretical perspective, the study corroborates the primacy of loss
principal and a corresponding corollary of ‗loss begets loss‘ (loss spirals) of the COR
theory. The findings of the study validate our assumptions that social relationships at
work are a valuable resource at workplace and relationship conflict is the loss of such
resources. The findings also indicate that relationship conflicts act as one of the
dissociative forces that diminish employees‘ attachment with their organization. It
further augments our theoretical assumption that this loss of social ties leads to further
loss in the form of burnout since it fuels high-arousal negative psychological states
and as the result of this loss spiral, employees are left with insufficient resources to
cope up with their performance threshold. This depletion of resources is likely to
194
exacerbate other stressors at work and causes relationship conflict to smoulder. The
findings also indicate that individual level perceptions of relationship conflict are
more strongly linked with work behaviors and behavioral intentions and that job
burnout explains the underlying resource draining mechanism between these
connections.
Another theoretical contribution of our study stems from the differentiation of
burnout dimensions. We tested each dimension of burnout separately in order to
gauge its distinctive impact on work behaviors. As such it gives an overview of the
burnout landscape with complete detail of its distinctive dimensions. The positive
association between relationship conflict and burnout generates unique information
about how to develop effective interventions to reduce relationship conflict and
burnout. For example, work interventions could include ways to improve
interpersonal harmony since high-quality relationships with coworkers have been said
to contribute towards better workplace functioning (Fernet at al., 2010), and this
relationship harmony may further protect against burnout. The findings also suggest
that relationship conflict with peers can be devastating and socially dangerous for an
individual and prove to be fatal for the sustainability of social networks in
organizations since relationships are the lifeblood of an organization (Ren & Gray,
2009). Relationship conflict induces social detachment in individuals which leads to
poor job performance and intensifies their intentions to leave the jobs. The findings
also indicate that relationship conflict can prove damaging to employees, their
coworkers and their organization as its negative consequence may likely impair
organizational functioning and hurt its performance. Employees undergo severe
psychological issues and develop a detached attitude towards their coworkers. This
emotional contagion not only affects their core activities but also their contextual
performance which may indirectly affect the performance of coworkers. Moreover,
low productivity, detached behavior and faltered commitment to continue with the
organization may harm the organizational viability. Van Dick and Haslam (2012)
state that ―when individuals react negatively to stress (as evidenced through
withdrawal or burnout, this impact directly on organizational functioning‖. Although
more difficult to quantify, the negative psychological impact of relationship conflict
can translate into reduced performance and higher turnover intentions. Based on our
findings, it is suggested that relationship conflict should be carefully managed so that
195
it does not lead to burnout which in turn can have serious setback for the individuals
and their organizations alike.
On a theoretical note, our findings indicate that it is essential to distinguish
conceptually and empirically between different forms of interpersonal conflict; each
one has its own distinct mediators and consequences. Conflict has several positive
outcomes when it is task related, but is dysfunctional and threatening to the well-
being of a social system when it threatens relationships. For instance, task conflict
serves as a means to accumulate cognitive resources that enhance deep understanding
of the task, employing their whole self into their work (work engagement) and
deriving satisfaction through these task related cognitive exchanges (job satisfaction),
and it also serves social functions for their coworkers through intellectual cooperation
and building cohesiveness thus reducing turnover intentions. Similarly, relationship
conflict may be more likely to serve signaling functions for organizations that
employees may develop burnout. By increasing the distance between oneself and the
work environment with psychologically (exhaustion, cynicism, interpersonal strain at
work) or factually (turnover intentions), these responses can be considered as
alarming signs for both management practitioners and academic researchers. Here, we
assert that interpersonal conflict has proved important in organizational context
because it has enormous implications both for individual work behaviors and for
organizational effectiveness.
6.5 Practical Implications
The current study has produced some practical implications which could aid
managers and organizations to better understand the dynamics of task conflict and
relationship conflict. The framework offers the potential for practitioners to approach
conflict with different lenses for understanding the psychological processes. Although
literature recognized task conflict as a double-edged sword (Bradley et al., 2012;
Meier et al., 2013), no evidence for this contention is found in this thesis. Instead,
consistent with COR theory (Hobfoll, 1989), managers should realize the untapped
potential of task conflict (Rispens & Demerouti, 2016).
From a practical point of view, our results inform managers that task conflict
in technical jobs motivates employees to think out of box on their task related
problems where task related synthesis of different perspectives among employees can
196
make them more engaged and satisfied through mixing of diverse ideas, concepts and
viewpoints. Intellectually stimulating task related information exchanges encourage
employees to think about problems and challenges in novel ways, and to question old
assumptions and consider what has not been considered previously. Employees invest
their mental resources in order to gain more resources which manifest as gain spirals
in the form of work engagement and job satisfaction. It also improves their positive
social functioning thereby engaging in invigorating social interactions. This implies
that task conflict has the potential to initiate a motivational process that leads to
positive behaviors in individuals, therefore, task conflict should not be considered as a
stressor but a resource which has the potential to energize the individuals and bring
forth positive outcomes to the benefit of the organizations.
The findings of this study provide some new insights into how relationship
conflict is related to particular dimensions of burnout and to individual behaviors.
Such insights may provide clues as to what may be the most appropriate areas to
target for interventions to reduce the risk of being poor performer and also the risk of
individuals exiting early from their organizations. Therefore, a key challenge for the
literature on relational tensions is to identify the conditions under which the
occurrence of relationship conflict is either minimized, or it negative effects
mitigated. Managers and their supervisors must be vigilant and cautious with regards
to the occurrence of relationship conflict since the findings clearly show that
relationship conflict is a major factor that leads to burnout which in turn leads to
decrements in task and contextual performance and low retention. Supervisors should
also introduce such training interventions that help train employees to cope effectively
with relational problems to neutralize or reduce the detrimental effects of relationship
conflict. Early detection and targeting of problematic interpersonal relationships at the
workplace may help reduce the risk of employees developing burnout as it can cause
lower productivity and ineffectiveness (Maslach et al., 2001). These interventions will
help safeguard overall organizational effectiveness and efficiency since organizational
performance is contingent upon the aggregated contribution of its employees and on
the quality of their working relationships (Hopkins & Yonker, 2015), thus individual
performance decrements will collectively lead to an erosion of overall organizational
performance. Organizations can also introduce counseling and employee assistance
programs (EAP) to make employees aware of the costs and consequences of
relationship conflicts and how to cope during its occurrence in order to reduce the
197
harmful effects of stressful encounters and to guard against burnout and thereby
attempt to offset the progression of the resource depletion process. Managers should
encourage overt discussion of the value of good interpersonal relationships in their
work units. Organizations should be able to identify the troubled employees and
provide them with an appropriate level of support. Our findings also highlight the
importance of being aware of the need to manage employees‘ resource depletion
through social support as without employees‘ willingness to help recuperate their
coworkers encountering relational problems, organizations would be less productive.
Moreover, the relational rifts in a collectivist society should be taken as a serious
threat to the smooth functioning of the organization since it may jeopardize its
viability as employees lose interest in their jobs, become less cooperative and even
may think of leaving their organizations.
This study establishes that work engagement, job satisfaction and burnout are
theoretically relevant constructs for understanding the resource acquisition as well as
resource depletion processes in conflict-work behaviors relationship. Therefore
research needs to investigate the contextual factors that may enhance the positivity
embedded in task conflict and possible interventions further to discover how best to
prevent relationship conflict among coworkers and its progression into job burnout.
Employers and managers need to ensure workplaces and work per se are designed for
improved well-being and performance. Managers themselves need to take
responsibility for their own level of stress caused by the relationship conflicts and to
develop the appropriate coping strategies to deal with such work stressors. The
management of relationship conflict involves identifying and determining sources of
relational tensions and developing support and resources to help individuals manage
stress and reduce the occurrence of relationship conflict. All in all, we believe these
findings to be intrinsically relevant to scholar and practitioners in the field of conflict
literature, organizational behavior, psychology, and management due to their
longstanding interest in conflict dynamics and how they can affect individual
behaviors at work.
6.6 Conclusion
Interpersonal conflict is a pervasive phenomenon, transcending across
individuals, teams and workgroups. Conflict plays an important role in employees‘
198
everyday working life. Motivated by key concerns with past research on task and
relationship conflict—its prime focus on team level analysis rather than individual
level effects, its focus on ―main effect approach‖ i.e., considering only the direct
relationships between interpersonal (task and relationship) conflict and work
behaviors, less focus on relationship conflict and outcome variables such as
contextual performance, and its neglect of the explanatory mechanisms which link
these two conflict types with work behaviors, we advanced the literature on conflict,
workplace subjective well-being and work behaviors in a sample of telecom
engineers. Our theoretical model was based on two fundamental assumptions, namely
(a) task conflict and relationship conflict have differential impact on work behaviors,
and (b) that due to their differential effects, task and relationship conflict have
different set of mediators that transmit their impact on work behaviors.
Building on these assumptions and previous research and taking insights from
the COR theory as an explanatory framework, we proposed that task conflict has a
positive impact on task performance, contextual performance, and negative impact on
turnover intentions, and these relationships are mediated by work engagement and job
satisfaction, and (b) that the relationship conflict has a negative impact on task
performance, contextual performance, and positive impact on turnover intentions, and
these relationships are mediated by job burnout.
The direct effects of task and relationship conflict on work behaviors (positive
and negative, respectively) support the view shared by many conflict scholars (e.g.,
Amason; 1996; Jehn, 1995; 1997; Lu et al., 2011). Based on these differential effects,
it was expected that task and relationship conflict have different mediators that link
them to work behaviors, the findings extends existing literature and provide evidence
that adds to prior research. The findings supported our assumptions derived from the
resource investment/acquisition principle that task conflict triggers exchange of
cognitive resources which leads to positive outcomes. It was further revealed that
these direct paths were mediated by work engagement and job satisfaction in case of
task conflict-work behaviors relationship. These explanatory mechanisms were
guided by the related corollary of gain spirals. Furthermore, guided by the primacy of
loss principle, it was delineated that relationship conflict initiates a resource depletion
process which leads to negative outcomes. Consistent with the related corollary of
loss spirals, the findings corroborated that relationship conflict represents a loss which
199
begets other losses that manifest as burnout. Each dimension of burnout i.e.,
exhaustion, cynicism and interpersonal strain at work mediated distinctively between
relationship conflict and work behaviors.
We hope that our research will stimulate new research that may help advance
the knowledge and theory on conflict, subjective well-being and work behaviors. It
may also stir future research with different set of mediators and moderators of the
conflict—work behavior relationships. Our findings can inform organizations what
interventions to invest in order to decrease relationship conflict. Given that
interpersonal conflict is a central contemporary issue, the findings of this study point
to an emerging model of task and relationship conflict in context of technical jobs.
This study‘s findings with regards to task conflict suggest that various
occupational groups may be motivated by different contextual factors. Such work is
needed to develop a more complete understanding of the pervasive influence of
conflict on our working lives. Moreover, our findings suggest that relationship
conflict may do serious harm to individuals as well as their organizations through
burnout as it incapacitates their performance and retention, hence must be managed
both at individual level as well as organizational level. The study identifies
differential effects of task and relationship conflict in an engineering context. It is
critical that researchers are aware of the nature of telecom engineers‘ perceptions of
conflict, since engineers‘ epistemological positions-how they view conflict – will
influence the way they behave in organizations.
Taken together, this research shows that the conflict-work behaviors
relationship depends on the type of conflict (i.e., task versus relationship), and
accounted for, by a conflict‘s impact on individual well-being in terms of work
engagement, job satisfaction and job burnout. Although our study provides interesting
results, it also elicit an array of other questions that we hope future researchers will
examine in an effort to better understand the linkages between conflict types,
workplace well-being and a broad range of work behaviors. All in all, our study is a
step forward toward clarifying the linking mechanism through which task conflict and
relationship conflict differentially impact individual outcomes. Our study generates a
new line of thinking through applying two principles of the Conservation of
Resources theory and serves as a platform for stimulating new theory, research and
practice in the broad domain of social scientific research. We encourage additional
200
research that clarifies and extends our knowledge of the relationships between conflict
types and individual outcomes in different cultural contexts.
201
Chapter 7
References
202
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Appendices
239
Appendix-A
Table: 1.1: Summary of Empirical Studies in the link between Interpersonal Conflicts
and Group Level Outcomes
Author(s)/Year/Titl
e of Paper Key Findings Critical Synthesis
Jehn (1995), ―A
multimethod
examination of the
benefits and
detriments of
intragroup conflict‖.
Task and relationship
conflict were negatively
related to individuals'
satisfaction, liking of other
group member, and intent to
remain in the group. Task
conflicts were detrimental to
group functioning in routine
tasks, whereas in non-routine
task, task conflicts were
beneficial.
Direct relationships between task
conflict/relationship conflict and
group performance and affective
reactions were studied. Task and
relationship conflict were found
to be negatively related to
affective reactions but task
conflict were found to be
constructive in non-routine work.
De Dreu & Weingart
(2003), ―Task versus
relationship conflict,
team performance,
and team member
satisfaction: A meta-
analysis‖.
Results from meta-analysis
showed that both task and
relationship conflicts are
problematic for team
performance. They further
argued that relationship
conflict does more damage to
team‘s satisfaction as
compared to task conflict.
Meta-analyses on 30 studies with
main focus on direct relationships
and moderators. Findings
depicted both task conflict and
relationship conflict as disruptive
for team performance and team
member satisfaction, but
relationship conflict termed as
more disruptive
Dijkstra,
Dierendonck, Evers,
& De Dreu (2005),
―Conflict and well-
being at work: the
moderating role of
personality‖.
Conflict was found to be
negatively
associated with well-being in
individuals with low
agreeableness, weak
emotional stability or low
extraversion.
Interpersonal conflict had a
negative relationship with well-
being. In this study conflict types
were not decoupled, and conflict
was treated as a workplace
stressor
240
Medina, Munduate,
Dorado, Martı´nez,
&Guerra, (2005),
―Types of intragroup
conflict and affective
reactions‖.
Task and relationship
conflict differentially related
to affective reactions, and
relationship conflict mediates
the link between task conflict
and affective reactions
Relationship conflict was found
to have negative relationship with
satisfaction, wellbeing and
propensity to leave whereas task
conflict was not found to be
directly related to affective
reactions. Relationship conflict
was positively related to
propensity to leave, whereas
interaction between task and
relationship conflict predicted
desire to leave the job and the
latter mediated between task
conflict and affective reactions.
Passos & Caetano
(2005), ―Exploring
the effects of
intragroup conflict
and past
performance
feedback on team
effectiveness‖.
Perceptions of team decision
effectiveness fully mediated
the relationship between
process conflict and team
performance. Task and
relationship conflict were not
found to be significantly
related to team performance
and satisfaction with the
team. Task conflict had no
effect on team performance
which validated the previous
studies‘ results.
Effects of conflict types were
measured on team performance
and satisfaction. Perception of
team decision effectiveness was
studied as a mediator and it fully
mediated the link between
process conflict and team
performance and satisfaction.
Both relationship and task
conflicts were found to be
unrelated to team performance
and satisfaction with the team.
241
Tjosvold, Law, &
Sun, H. (2006)
(2005),
―Effectiveness of
Chinese teams: the
role of conflict types
and conflict
management
approaches‖
Relational conflict was found
to be negatively related to
team effectiveness, but
results about task conflict
were a bit complicated. Task
conflict did not significantly
relate to team effectives as
reported by team members or
team leader.
The study tested the direct
relationship between relational
conflict, task conflict, and team
effectiveness. Relationship
conflict had a negative impact on
team effectiveness, but task
conflict was not found to be
related to team effectiveness. The
researchers suggested a need for
further analysis with better scales
in order to assess the role of task
conflict.
Langfred (2007),
―The downside of
Self-Management:
A longitudinal study
of the effects of
conflict on trust,
autonomy, and task
interdependence in
self-managing
teams‖
Relationship conflict had a
negative relationship with
trust, autonomy and
interdependence. Task
conflict was negatively
related to task
interdependence but
positively related to trust and
autonomy.
Conflict types were measured
against trust, autonomy and task
interdependence. Relationship
conflict negatively related to
Trust, autonomy and task
interdependence whereas task
conflict was not found to be
negatively related to trust, or
autonomy except task
interdependence. The study did
not take into account any
mediators or moderators.
Gamero, Gonza´lez-
Roma & Peiro
(2008), ―The
influence of intra-
team conflict on
work teams‘
affective climate: a
longitudinal study‖
Relationship conflict
completely mediated the link
between task conflict and
teams‘ affective climate, thus
revealing that task conflict is
an antecedent of relationship
conflict. Team members‘
interaction moderated the
relationship
Relationship conflict mediated
the link between task conflict and
team‘s affective climate such as
the relationship became negative.
However, team member
interaction moderated this
relationship between two type of
conflict and it weakened the
relationship as highly interactive
242
team members had very low
levels of conflict.
Ayoko & Pekerti
(2008), ―The
mediating and
moderating effects
of conflict and
communication
openness on
workplace trust‖
Task, process and
relationship conflicts were
found to be negatively
related to trust, and conflict
duration, however, these all
types positively related to
conflict intensity.
Task, process and relationship
conflict negatively related to
trust, and conflict intensity and
conflict duration mediated these
relationships and communication
openness moderated the
relationship. Conflict intensity
was found to be negatively
associated with workplace trust
whereas conflict duration was
positively related to trust
De Jong, Schalk, &
Curseu (2008),
―Virtual
communicating,
conflicts and
performance in
teams‖
In teams with higher level of
virtuality, there was more
positive impact of task
conflict on perceived team
performance. Process
conflict had a negative
relationship with perceived
team performance.
Relationship conflict was not
found to be related to
perceived team performance.
The study tested direct
relationships between conflict
types and perceived team
performance and level of team
virtuality was studied as a
moderator. Task conflict had a
positive impact on perceived team
performance in teams with high
virtuality, whereas relationship
conflict did not have negative
effect on performance and
process conflict had a negative
impact on perceived team
performance.
Kisamore, Jawahar,
Liguori, Mharapara,
& Stone (2010),
―Conflict and
abusive workplace
behaviors, The
Interpersonal conflict
positively impacted abusive
behavior at workplace and
political skill and self-
monitoring were positively
related to abusive behavior.
Relationship of interpersonal
conflict and abusive work place
behaviors was studied.
Interpersonal conflict was
positively related to abusive
behavior. Political skill, self-
243
moderating effects
of social
competencies‖
No significant relationship
was observed between
interpersonal conflict and
emotional intelligence due to
overlapping between
emotional intelligence and
political skill.
monitoring and emotional
intelligence were studied as
moderators. Both political skill
and self-monitoring positively
impacted abusive behaviors
except emotional intelligence as it
had no significant relationship
with abusive behaviors. Conflict
types were not decoupled.
Farh, Lee, & Farh
(2010), ―Task
Conflict and Team
Creativity: A
Question of How
Much and When‖
Moderate task conflict was
positively related to team
creativity and this
relationship was strong at
early team phase. At final
stage of team life cycle, task
conflict was unrelated to
team creativity.
Task conflict had a curvilinear
effect on team creativity, and
creativity was highest at moderate
level of conflict, and this link was
moderated by team phase such
that the curvilinear effect was
most significant at early phase.
Shaw, Zhu, Duffy,
Scott, Shih, &
Susanto (2011), ―A
Contingency Model
of Conflict and
Team Effectiveness‖
Relationship conflict
intensified the negative
relationship between task
conflict and team member
satisfaction, but task conflict-
team satisfaction negative
relationship is not significant
when relationship conflict is
low.
Relationship conflict moderated
the task conflict-team member
satisfaction relationship such that
in case of low relationship
conflict, this relation was
curvilinear, but when relationship
conflict was high, this
relationship became linear and
negative.
244
Martínez-Corts, Boz,
Medina, Benítez,
Munduate (2011),
―Coping with
Interpersonal
Conflict at Work in
Small Business: The
Moderating Role of
Supervisor and Co-
Worker Support‖
High levels of relationship
conflict led to low level of
job satisfaction whereas
higher perceived supervisor
support enhanced job
satisfaction. Task conflict
had no direct relationship
with job satisfaction. But job
satisfaction is positive when
task conflict interacts with
high levels of perceived co-
worker support.
Relationship conflict had a
negative relationship with job
satisfaction and high perceived
supervisor support weakened this
relationship. Task conflict was
not found to be related to job
satisfaction but the relationship
turns positive in presence of
perceived coworker support.
Perceived Supervisor /coworker
support moderated the
relationship between conflict
types and job satisfaction
Kacmar, Bachrach,
Harris, & Noble,
(2012), ―Exploring
the role of supervisor
trust in the
associations between
multiple
sources of
relationship conflict
and organizational
citizenship behavior‖
Relationship conflict had a
significant negative impact
on task-focused OCB and
supervisor trust mediated this
relationship. However,
supervisor trust did not
mediate the link between
relationship conflict and
person-focused OCB.
Only relationship conflict was
studied and it was found to be
negatively related to task-focused
OCB and person focused OCB.
Supervisor trust mediated
between relationship conflict and
task-focused OCB but it did not
mediate between relationship
conflict and person-focused as
both were directly related.
Moreover, supervisor trust
moderated the coworker conflict-
citizenship behavior associations.
De Wit, Greer,
&Jehn, (2012), ―The
Paradox of
Intragroup Conflict:
A Meta-Analysis‖
Relationship conflict and
process conflict both had
negative relationship with
group performance. Task
conflict and group
performance had positive
relationship where
Direct relationships between
conflict types and group level
outcomes were studied. Both
relationship conflict and process
conflict negatively related to
group performance whereas task
conflict had a positive impact on
245
association between task
conflict and relationship
conflict was weak, and in
studies among top
management teams.
team performance in top
management teams, and in studies
where performance was financial
performance or decision quality
rather than overall performance.
Bradley,
Postlethwaite, Klotz,
Hamdani, & Brown
(2012), ―Reaping the
Benefits of Task
Conflict in Teams:
The Critical Role of
Team Psychological
Safety Climate‖
Task conflict and team
performance were found to
be positively related under
high psychological safety.
Only task conflict was studied
and it had a positive effect on
team performance in presence of
psychological safety.
Puck & Pregerning
(2014), ―The effect
of task conflict and
cooperation on
performance of
teams:
Are the results
similar for different
task types?‖
Task conflict had a negative
effect on performance and
this effect, contingent upon
the task type is mediated by
cooperation
Only task conflict was studies and
it negatively affected
performance and team member
cooperation mediated this
relation.
246
Appendix-B
Table: 1.2: Summary of Empirical Studies in the link between Interpersonal Conflicts
and Individual Level Outcomes
Title of Paper/
Author(s)/Year/
Country
Key Findings Critical Analyses
Kurtzberg & Mueller,
(2005), ―The influence
of daily conflict on
perceptions of
creativity: A
Longitudinal Study‖
Task conflict
positively impacted
creativity at individual
level but not at team‘s
level. Process conflict
and relationship
conflict also had a
negative impact at
team's perception of
creativity.
Task conflict had a positive
impact on individual's
perception of creativity but
a negative impact at team's
level which shows that
results for task conflict
differed at both levels.
However, both
relationship/process conflict
negatively impacted
creativity
Lu, Zhou, & Leung
(2011), ―Effects of task
and relationship
conflicts on individual
work
behaviors‖
Task conflict was found to
be positively related to
both innovative behaviors
and knowledge sharing
behaviors. Relationship
conflict had a negative
relationship with both
individual-directed
organizational citizenship
and knowledge sharing
behaviors.
This is an individual level
study in which both task
conflict and relationship
conflict distinctively
predicted individual work
behaviors. Task conflict had
a positive impact on
innovative and knowledge
sharing behaviors.
Relationship conflict
negatively impacted OCB
and knowledge sharing
behaviors
247
Zhang & Zhang, (2012)
―Conflict types,
resolution, and relational
satisfaction: A U.S.-
China investigation‖
Task conflict tends to be
resolved and is associated
with higher relational
satisfaction than
relationship conflict in both
cultures. During conflict,
Chinese experience less
relational satisfaction than
Americans. Culture
mediates the effect of
conflict types and conflict
resolution on relational
satisfaction.
Conflict types and conflict
resolution were studied
against relational
satisfaction and culture
mediated these links. It was
concluded that task conflict
gets easily resolved in both
US and Chinese cultures
and is related to relational
satisfaction. Relationship
conflict negatively affects
relational satisfaction.
Avgar, Kyung Lee, &
Chung (2014), ―Conflict
in context: Perceptions
of conflict, employee
outcomes and the
moderating role of
discretion and social
capital‖
Employee discretion
moderated the relationship
between task conflict and
job stress. Unit-level social
capital moderated the link
between relationship
conflict and employee
turnover intentions
Both task conflict and
relationship conflict
positively affected stress
and turnover intentions.
Employee discretion
moderated between task
conflict and job stress. Unit-
level social capital
moderated between
relationship conflict and
turnover intentions
248
Appendix-C
Table: 1.3: Summary of Empirical Studies in the link between Interpersonal
Conflicts and Individual Level Outcomes in Pakistani context
Title of Paper Result Critical Analyses
Afzal, Khan, & Ali,
(2009), ―Linkage
between Employee‘s
Performance
and Relationship Conflict
in Banking Scenario‖
Relationship conflict
negatively influenced job
performance of
employees
Only relationship conflict
was studied and it negatively
impacted job performance
Ul-Haq, ( 2011), ―The
impact of interpersonal
conflict on job outcomes:
Mediating role of
perception of
organizational politics‖
Interpersonal conflict
was found to be
positively related to
interpersonal/organizatio
nal workplace deviance.
Perception of politics
mediated these
relationships.
Conflict types were not
decoupled. Interpersonal
conflict positively impacted
interpersonal/organizational
workplace deviance.
Perception of politics
mediated between
interpersonal conflict-job
stress and between
interpersonal conflict-
intentions to quit.
Anwar, Maitlo, Soomro,
& Shaikh (2012), ―Task
Conflicts and its
Relationship with
Employee‘s
Performance‖
Task conflict was found
to be negatively related
to employees
performance
Only task conflict was
studied and it had a negative
effect on employee
performance
Ahmed, Shahzad, Fareed,
Zulfiqar, &Naveed
(2014), ―Impact of
Relationship, Task &
Task conflict was found
to be positively related to
teacher's performance
whereas relationship
Conflict types differentially
related to performance. Task
conflict had a positive impact
on performance whereas
249
Role Conflict
on Teaching Performance
in Educational
Institutes‖
conflict and role conflict
had a negative impact on
teacher's performance.
relationship/role conflicts
had a negative effect on
performance
250
Appendix-D
COMSATS INSTITUTE OF INFORMATION TECHNOLOGY
ISLAMABAD
Interpersonal Conflict, Well-being, Work Behaviors Survey 2015
8th
January 2015
Dear Sir / Madam,
You are invited to participate in a study of Interpersonal Conflict, Well-being,
and Work Behaviors in Telecom Services Industry. I hope that the study will reveal
fruitful outcomes for management of human resources in Telecom Sector. You were
selected as a possible participant in this study being an important member of
management.
If you decide to participate, please complete the enclosed survey. Your return
of this survey is implied consent. The survey is designed to find out the relationship /
impact of Interpersonal Conflicts on your well-being and job performance. It will take
about 10 minutes. No benefits accrue to you for answering the survey, but your
responses will be used to find key factors behind the success / failure of the
organization. Any discomfort or inconvenience to you derives only from the amount
of time taken to complete the survey.
Any information that is obtained in connection with this study and that can be
identified with you will remain confidential and will not be disclosed.
Your decision whether or not to participate will not prejudice your future
relationships with your organization. If you decide to participate, you are free to
discontinue participation at any time without prejudice.
If you have any questions, please ask. If you have additional questions later,
contact the undersigned.
Thank you for your time.
Sincerely,
(Razia Shaukat)
0320-5555866
251
Appendix-E
COMSATS INSTITUTE OF INFORMATION TECHNOLOGY
ISLAMABAD
Interpersonal Conflict, Well-being, Work Behaviors Survey 2015
Please encircle the response that best represents the level of Interpersonal
conflict at your workplace with the following statements.
Q# Question None Som
e
times
Often Freq
uently
A lot
1
How often do people at your workplace
disagree about opinions regarding the
work being done?
1 2 3 4 5
2 How frequently are there conflicts about
ideas at your workplace? 1 2 3 4 5
3 How much conflict about the work you do
is there at your workplace? 1 2 3 4 5
4 To what extant are there differences of
opinion at your workplace? 1 2 3 4 5
5 How much friction is there among
members at your workplace? 1 2 3 4 5
6 How much relationship tension is there
among members at your workplace? 1 2 3 4 5
7 How often do people get angry while
working at your workplace? 1 2 3 4 5
8 How much emotional conflict is there
among members at your workplace? 1 2 3 4 5
Please read each statement carefully and select if you ever feel this way about your
job:-
Q# Question Never Rarely Some
times
Often Always
9 At my work, I feel bursting with energy. 1 2 3 4 5
252
10 At my job, I feel strong and vigorous. 1 2 3 4 5
11 I am enthusiastic about my job. 1 2 3 4 5
12 My job inspires me. 1 2 3 4 5
13 When I get up in the morning, I feel like
going to work. 1 2 3 4 5
14 I feel happy when I am working
intensely. 1 2 3 4 5
15 I am proud of the work that I do. 1 2 3 4 5
16 I am immersed in my work. 1 2 3 4 5
17 I get carried away when I am working. 1 2 3 4 5
18 I feel emotionally drained from my
work. 1 2 3 4 5
19 I feel used up at the end of the workday. 1 2 3 4 5
20 I feel tired when I get up in the morning
and have to face another day on the job. 1 2 3 4 5
21 Working all day is really a strain for me. 1 2 3 4 5
22 I feel burned out from my work. 1 2 3 4 5
23 I have become less interested in my
work since I started this job. 1 2 3 4 5
24 I have become less enthusiastic about
my work. 1 2 3 4 5
25 I just want to do my job and not be
bothered. 1 2 3 4 5
26 I‘ve become more cynical about whether
my work contributes anything. 1 2 3 4 5
27 I doubt the significance of my work. 1 2 3 4 5
28 At work, I feel more comfortable
keeping distance from others. 1 2 3 4 5
29 At work, I find myself to be insensitive
to other people‘s problems. 1 2 3 4 5
30 At work, I treat others in a cold and
detached manner. 1 2 3 4 5
31 At work, I‘m not particularly interested 1 2 3 4 5
253
in what happens to others.
32 Sometimes when I‘m working, it
happens to me to mistreat someone. 1 2 3 4 5
33 At work, I feel irritated by other people. 1 2 3 4 5
Please indicate how often the following statements apply to you by encircling the
appropriate number from the scale:-
Q# Question
Strongl
y
Disagre
e
Disagree
Neither
Disagree
Nor
Agree
Agree Strongly
Agree
34 All in all, I am satisfied with
my job. 1 2 3 4 5
35 In general, I do not like my job. 1 2 3 4 5
36 In general, I like working here. 1 2 3 4 5
37 I often think of quitting this
organization. 1 2 3 4 5
38
I think of searching for another
position with another
organization.
1 2 3 4 5
39
I often think of leaving the
organization within the next
year.
1 2 3 4 5
General Information
Name. (Optional) ----------------------------------- Designation.-----------------------
Cellular Service Provider Company. --------------------------- Department.------------
Education Level B.Sc M.Sc. MS Ph.D Others
Gender. Male Female
Age: 25-35 35-45 45 & above
Work Experience. (No of Years) ---------------------
Marital Status: Single Married
Thank you so much for participating in the study.
254
Appendix-F
COMSATS INSTITUTE OF INFORMATION TECHNOLOGY
ISLAMABAD
Work Behaviors Survey 2015
8th
January 2015
Dear Sir / Madam,
You are invited to participate in a study of Work Behaviors in Telecom
Services Industry. I hope that the study will reveal fruitful outcomes for management
of human resources in Telecom Sector. You were selected as a possible participant in
this study being an important member of management.
If you decide to participate, please complete the enclosed survey. Your return
of this survey is implied consent. The survey is designed to find out the Work
Behaviors of the employees working under your command. It will take about 05
minutes. No benefits accrue to you for answering the survey, but your responses will
be used to find key factors behind the success / failure of the organization. Any
discomfort or inconvenience to you derives only from the amount of time taken to
complete the survey.
Any information that is obtained in connection with this study and that can be
identified with you will remain confidential and will not be disclosed.
Your decision whether or not to participate will not prejudice your future
relationships with your organization. If you decide to participate, you are free to
discontinue participation at any time without prejudice.
If you have any questions, please ask. If you have additional questions later,
contact the undersigned.
Thank you for your time.
Sincerely,
(Razia Shaukat)
0320-555586
255
Appendix-G
COMSATS INSTITUTE OF INFORMATION TECHNOLOGY
ISLAMABAD
Work Behaviors Survey 2015
Please rate the performance of your subordinate based on his / her work performance.
Q# Question Strongly
Disagree Disagree
Neither
Agree
Nor
Disagre
e
Agree Strongly
Agree
Task Performance
1 This employee adequately
completes assigned duties. 1 2 3 4 5
2
This employee fulfills
responsibilities specified in
(his/her) job description.
1 2 3 4 5
3
This employee meets formal
performance requirements of the
job.
1 2 3 4 5
4 This employee completes tasks
that are expected of him/her. 1 2 3 4 5
5
This employee neglects aspects
of the job he/she obligated to
perform (R).
1 2 3 4 5
Contextual Performance
6
This employee looks for ways to
make this organization more
successful.
1 2 3 4 5
7 This employee takes action to 1 2 3 4 5
256
protect this organization from
potential problems.
8
This employee makes
suggestions to help this
organization).
1 2 3 4 5
9
This employee keeps well-
informed where his / her opinion
might benefit this organization.
1 2 3 4 5
10
This employee continues to look
for new ways to improve the
effectiveness of his / her work.
1 2 3 4 5
11
This employee encourages
coworkers to try new and more
effective ways of doing their job.
1 2 3 4 5
12
This employee speaks favorably
of this organization to other
employees.
1 2 3 4 5
13
This employee gains knowledge,
skills, and abilities that will be of
benefit to this organization.
1 2 3 4 5
General Information
Name of Supervisor.(Optional) -----------------------------Designation.-------------------
Education Level B.Sc M.Sc. MS Ph.D Others
Work Experience. (No of Years) --------------------
Name of Subordinate. ---------------------------Working under you since.--------------
Thank you so much for participating in the study.
257
Appendix -H
Table: 5.4: Mahalanobis Distance
Observation Number Mahalanobis d-squared p1 p2
462 75.504 .001 .444
17 73.872 .002 .218
227 73.624 .002 .068
402 69.831 .004 .194
412 68.504 .006 .195
184 67.547 .007 .183
381 67.329 .008 .108
324 65.868 .011 .185
370 65.611 .011 .129
351 64.762 .014 .159
298 64.660 .014 .101
499 64.232 .015 .091
386 64.202 .015 .052
424 63.467 .018 .074
77 61.907 .024 .261
344 61.302 .027 .324
142 61.113 .028 .284
500 61.098 .029 .208
437 60.871 .030 .189
176 60.441 .032 .219
455 60.239 .034 .200
397 59.835 .036 .233
150 59.488 .039 .257
394 59.487 .039 .192
488 59.318 .040 .174
395 59.137 .042 .162
496 58.796 .044 .189
387 58.743 .045 .150
367 58.707 .045 .115
490 58.305 .048 .154
182 58.195 .049 .134
326 58.065 .051 .121
200 58.025 .051 .093
258
243 57.920 .052 .080
224 57.840 .053 .066
258 57.836 .053 .046
472 57.682 .054 .044
158 57.392 .057 .056
293 57.119 .060 .069
368 57.058 .061 .056
334 56.887 .062 .057
23 56.857 .063 .043
241 56.651 .065 .048
245 56.615 .065 .037
503 56.096 .072 .083
346 55.925 .074 .088
463 55.532 .079 .143
421 55.504 .079 .117
3 55.429 .080 .104
433 55.390 .081 .086
136 55.370 .081 .067
335 55.248 .083 .066
484 55.186 .083 .056
505 55.156 .084 .045
403 54.738 .090 .089
332 54.697 .091 .074
330 54.675 .091 .059
434 54.506 .093 .066
173 54.102 .100 .125
399 54.002 .101 .122
179 53.883 .103 .124
396 53.797 .105 .118
295 53.781 .105 .096
487 53.588 .108 .116
384 53.533 .109 .103
297 53.510 .110 .086
126 53.440 .111 .079
149 53.220 .115 .104
473 53.139 .116 .099
259
180 53.020 .119 .103
428 52.882 .121 .113
464 52.672 .125 .144
235 52.639 .126 .126
6 52.430 .130 .160
411 52.325 .132 .164
400 52.157 .135 .191
7 52.116 .136 .173
143 52.049 .138 .164
341 51.986 .139 .155
168 51.950 .140 .138
185 51.874 .141 .134
390 51.632 .147 .187
234 51.611 .147 .163
134 51.537 .149 .159
102 51.382 .152 .184
398 51.335 .153 .171
338 51.086 .159 .238
139 51.048 .160 .219
415 51.044 .160 .187
153 50.950 .162 .192
410 50.866 .164 .193
372 50.785 .166 .194
494 50.721 .167 .188
371 50.645 .169 .187
489 50.609 .170 .170
413 50.565 .171 .158
270 50.472 .174 .164
429 50.412 .175 .158
212 50.162 .181 .229
401 50.126 .182 .212
260
Appendix –I
Table: 5.5: Assessment of Normality
Items N-
Valid N-Missing Skewness
Std. Error of
Skewness Kurtosis
Std. Error
of Kurtosis
TC1 508 0 -0.224 0.108 0.126 0.216
TC2 508 0 -0.232 0.108 0.069 0.216
TC3 508 0 -0.389 0.108 0.403 0.216
TC4 508 0 -0.393 0.108 0.410 0.216
RC1 508 0 0.796 0.108 0.072 0.216
RC2 508 0 0.849 0.108 0.172 0.216
RC3 508 0 0.809 0.108 0.124 0.216
RC4 508 0 0.877 0.108 0.214 0.216
WE1 508 0 -0.841 0.108 0.525 0.216
WE2 508 0 -0.739 0.108 0.559 0.216
WE3 508 0 -0.430 0.108 0.403 0.216
WE4 508 0 -0.310 0.108 0.329 0.216
WE5 508 0 -0.276 0.108 0.211 0.216
WE6 508 0 -0.148 0.108 0.035 0.216
WE7 508 0 -0.192 0.108 0.002 0.216
WE8 508 0 -0.209 0.108 0.237 0.216
WE9 508 0 -0.476 0.108 0.206 0.216
EXH1 508 0 0.373 0.108 0.122 0.216
EXH2 508 0 0.422 0.108 -0.075 0.216
EXH3 508 0 0.666 0.108 0.472 0.216
EXH4 508 0 0.494 0.108 0.197 0.216
EXH5 508 0 0.382 0.108 -0.057 0.216
CYN1 508 0 0.396 0.108 0.495 0.216
CYN2 508 0 0.470 0.108 0.007 0.216
CYN3 508 0 0.352 0.108 -0.129 0.216
CYN4 508 0 0.445 0.108 0.036 0.216
CYN5 508 0 0.553 0.108 0.431 0.216
ISW1 508 0 0.283 0.108 0.154 0.216
ISW2 508 0 0.262 0.108 0.176 0.216
261
ISW3 508 0 0.248 0.108 0.087 0.216
ISW4 508 0 0.261 0.108 0.093 0.216
ISW5 508 0 0.235 0.108 0.117 0.216
ISW6 508 0 -0.175 0.108 -0.536 0.216
JS1 508 0 -0.608 0.108 -0.232 0.216
JS2 508 0 -0.591 0.108 -0.312 0.216
JS3 508 0 -0.655 0.108 -0.202 0.216
OTI1 508 0 0.306 0.108 0.000 0.216
OTI2 508 0 0.320 0.108 0.126 0.216
OTI3 508 0 0.340 0.108 0.069 0.216
TP1 508 0 -0.741 0.108 0.165 0.216
TP2 508 0 -0.652 0.108 0.018 0.216
TP3 508 0 -0.565 0.108 -0.287 0.216
TP4 508 0 -0.595 0.108 -0.299 0.216
TP5 508 0 -0.772 0.108 0.028 0.216
CP1 508 0 -0.581 0.108 0.438 0.216
CP2 508 0 -0.547 0.108 0.385 0.216
CP3 508 0 -0.542 0.108 0.389 0.216
CP4 508 0 -0.466 0.108 0.161 0.216
CP5 508 0 -0.429 0.108 0.253 0.216
CP6 508 0 -0.589 0.108 0.345 0.216
CP7 508 0 -0.584 0.108 0.419 0.216
CP8 508 0 -0.424 0.108 -0.068 0.216
262
Appendix-J
Table: 5.17: Common Method Bias
Component
Initial Eigenvalue Extraction Sums of Squared Loadings
Total % of
Variance
Cumulative
% Total
% of
Variance
Cumulative
%
1 12.466 34.627 34.627 12.466 34.627 34.627
2 2.420 6.722 41.349
3 2.325 6.457 47.806
4 1.655 4.597 52.403
5 1.518 4.215 56.618
6 1.358 3.771 60.389
7 1.086 3.015 63.404
8 1.014 2.817 66.222
9 .885 2.459 68.681
10 .808 2.245 70.926
11 .745 2.070 72.996
12 .700 1.943 74.939
13 .609 1.691 76.631
14 .578 1.605 78.236
15 .537 1.492 79.728
16 .493 1.370 81.098
17 .475 1.320 82.418
18 .473 1.314 83.732
19 .450 1.250 84.982
20 .440 1.222 86.204
21 .432 1.200 87.404
22 .410 1.140 88.544
23 .397 1.102 89.646
24 .376 1.043 90.689
25 .349 .970 91.659
26 .342 .951 92.610
27 .321 .891 93.502
28 .309 .859 94.361
263
29 .303 .840 95.201
30 .288 .801 96.002
31 .271 .752 96.754
32 .265 .735 97.489
33 .253 .702 98.191
34 .232 .644 98.835
35 .222 .617 99.452
36 .197 .548 100.000
Extraction Method: Principal Component Analysis
264
Appendix-K
Table: 5.20: Average Variance Extracted & Composite Reliability Values
Construct Item Factor Loading AVE (Above
0.5) CR (Above 0.6)
Task Conflict
TC1 0.813
0.531 0.818 TC2 0.679
TC3 0.696
TC4 0.719
Relationship
Conflict
RC1 0.82
0.711 0.908 RC2 0.862
RC3 0.863
RC4 0.826
Work
Engagement
WE1 Deleted
0.628 0.812
WE2 Deleted
WE3 0.766
WE4 0.765
WE5 0.848
WE6 0.816
WE7 0.815
WE8 0.742
WE9 Deleted
Job
Satisfaction
JS1 0.797
0.623 0.832 JS2 0.778
JS3 0.786
Exhaustion
EXH1 Deleted
0.563 0.766
EXH2 0.757
EXH3 0.781
EXH4 0.742
EXH5 0.718
Cynicism
CYN1 Deleted
0.620 0.797 CYN2 0.757
CYN3 0.826
CYN4 0.806
265
CYN5 0.759
Interpersonal
Strain at Work
ISW1 0.824
0.634 0.848
ISW2 0.804
ISW3 0.809
ISW4 0.82
ISW5 0.731
ISW6 Deleted
Organizational
Turnover
Intentions
OTI1 0.78
0.537 0.775 OTI2 0.634
OTI3 0.775
Task
Performance
TP1 0.717
0.535 0.749
TP2 0.788
TP3 0.692
TP4 0.726
TP5 Deleted
Contextual
Performance
CP1 0.715
0.502 0.695
CP2 Deleted
CP3 0.762
CP4 0.717
CP5 0.656
CP6 0.688
CP7 Deleted
CP8 Deleted
Note: The items having factor loadings less than 0.5 were deleted.
266
Appendix-L
Job Description of Telecom Engineer
Networking for Data Transmission through Wireless, Copper Wired & Fiber Optics
Solutions for Cellular, Cable and Broadband Services.
Undertaking site surveys for new data lines or to troubleshoot the faults.
Conducting relevant research for new products/networks
Planning, designing, commissioning and monitoring of telecommunication
equipment.
Analyzing and interpreting data for GSM & GPRS networks and products.
Producing contingency management plans for backup support.
To ensure the SOPs on Cyber Security in all data transmission networks.
Add/drop Multiplexers, Routing and Switching and Transmission technologies.
Liaising with suppliers for inspections from technical aspects before purchase.
