role of work life balance in maintaining the productivity among layoff...

ROLE OF WORK LIFE BALANCE IN MAINTAINING THE

PRODUCTIVITY AMONG LAYOFF SURVIVORS

By

Muhammad Imran Malik

Ph. D. Scholar Reg. No. 131/FUIMCS/Ph.D. (MS) - 2006

FACULTY OF

MANAGEMENT SCIENCES

2012

ii

Role of Work Life Balance in Maintaining the Productivity among

Layoff Survivors

By


A thesis submitted to the

FUIEMS

Foundation University, Islamabad

In partial fulfillment of the requirements for the

DEGREE OF DOCTORATE OF PHILOSOPHY

IN

MANAGEMENT SCIENCES

FACULTY OF MANAGEMENT SCIENCES

2012

iv

TEAM OF SUPERVISORS, FOREIGN EVALUATORS AND

EXAMINAERS

Supervision Dr. Mehboob Ahmad Supervisor Head of Department,

[email protected] Management Sciences,

Bahria University,

Islamabad, Pakistan.

Dr. Muhammad Iqbal Saif Co – supervisor Head of Department,

[email protected] FUIEMS,

Foundation University,


Evaluation Dr. Ayse Kucuk Yilmaz Foreign Evaluator Department of Aviation,

[email protected] Management, School of

Civil Aviation, Anadolu

University, 26470,

Eskisehir, Turkey.

Dr. Amin Sarkar Foreign Evaluator Dean,

[email protected] School of Business,

Alabama A & M

University, USA.

Examiners Prof. Dr. Abdul Qayyum External Examiner Dean,

[email protected] Institute of

Management Studies,

University of Peshawar,

Pakistan.

Dr. Khurram Shahzad External Examiner Head of Department,

[email protected] Faculty of

Management Sciences,

Riphah International

University, Islamabad,

Pakistan.

Dr. M. Nadeem Safwan Internal Examiner Professor,

[email protected] FUIEMS,

Foundation University,


mailto:[email protected]


mailto:Department%20of%20Aviation,[email protected]

mailto:Department%20of%20Aviation,[email protected]





v

CERTIFICATE

I have supervised the research “Role of Work Life Balance in Maintaining

the Productivity among Layoff Survivors” by Muhammad Imran Malik, a

Ph.D. scholar of Foundation University, Institute of Engineering and

Management Sciences (FUIEMS), Islamabad. The work is worth presenting

for final defense.

(Dr. Mehboob Ahmad)

Professor

Head, Department of Management Sciences,

Undergraduate Studies,

Bahria University, Islamabad, Campus,

Pakistan.

vii

WORK PUBLISHED IN THE COURSE OF THIS THESIS

(REFEREED ARTICLES)

Malik, M.I., & Ahmad, A. (2011). Lucky or Unlucky People: Layoff Survivors. Far East

Journal of Psychology and Business, 2(3): 23-35.

Saif, M.I., Malik, M.I., & Awan, M.Z. (2011). Employee Work Satisfaction and Work

Life Balance: A Pakistani Perspective, Interdisciplinary Journal of Contemporary

Research in Business, 3(5):606-617.

Malik, M.I., Hussain, S., & Mahmood, A. (2011). Examining a Chain Relationship of

Layoff Survivors’ Role Overload, Work -Life Balance and their Productivity.

Interdisciplinary Journal of Contemporary Research in Business, 3(6): 402-409. Malik, M.I., & Usman, A. (2011). Role Overload and Job Satisfaction and their Effect

on Layoff Survivor’s Job Retention and Productivity. Interdisciplinary Journal of

Contemporary Research in Business, 2(11): 427-440.

Malik, M.I., Ahmad, M., Saif, M.I., & Safwan, M.N. (2010). Relationship of

Organizational Commitment, Job Satisfaction and Layoff Survivor’s Productivity.

Interdisciplinary Journal of Contemporary Research in Business, 2(7): 200-211.

Malik, M.I., Ahmad, A., & Hussain, S. (2010). How Downsizing Affects Job

Satisfaction and Life Satisfaction of Layoff Survivors. African Journal of Business and

Management, 4(16): 3564-3570. (ISI Indexed Journal/Impact factor 1.105).

Malik, M.I., Bibi, S., & Rahim S.H., (2010). Non - Financial Measures of Layoff

Survivors’ Satisfaction. Interdisciplinary Journal of Contemporary Research in Business,

2(8), 60-70.

viii

TABLE OF CONTENTS

Description Page No.

TITLE PAGE ii

APPROVAL SHEET iii

LIST OF SUPERVISORS, EVALUATORS AND EXAMINERS iv

CERTIFICATE v

DECLARATION vi

WORK PUBLISHED IN THE COURSE OF THIS THESIS vii

TABLE OF CONTENTS viii

LIST OF TABLES xi

LIST OF FIGURES xii

LIST OF APPENDICES xiii

LIST OF ABBREVIATIONS xiv

DEDICATION xvi

ACKNOWLEDGEMENTS xvii

ABSTRACT xviii

Chapters

1. INTRODUCTION 1

1.1. Background 2

1.2. Problem area of study 5

1.3. Knowledge gap 6

1.4. Research Problem(s) 8

1.5. Research objectives 9

1.6. Significance of the study 10

1.7. Academic contributions of the study 11

1.8. Concepts and definitions 12

1.9. Organization of the dissertation 20

2. LITERATURE REVIEW 21

2.1. Relationship of the variables 22

ix

2.1.1. Perceived post layoff work load increase and role overload 22

2.1.2. Role overload and work life balance 25

2.1.3. Role overload and job satisfaction 29

2.1.4. Role overload and life satisfaction 31

2.1.5. Work life balance and job satisfaction 32

2.1.6. Work life balance and life satisfaction 38

2.1.7. Work life balance and employee retention 43

2.1.8. Work life balance and organizational commitment 48

2.1.9. Job satisfaction and employee productivity 50

2.1.10. Life satisfaction and employee productivity 52

2.1.11. Employee retention and employee productivity 53

2.1.12. Organizational commitment and employee productivity 54

2.2. Summary of the literature review 57

3. ORGANIZATIONAL BACKGROUND AND

THEORETICAL FRAMEWORK 58

3.1. Historical background of the organizations 59

3.2. Operational definitions of the concepts 60

3.3. Proposed model 65

3.4. Hypothesis 75

4. RESEARCH METHODOLOGY 78

4.1. Pilot study 79

4.1.1. Population 79

4.1.2. Sample 79

4.1.3. Instruments 80

4.1.4. Procedure 88

4.1.5. Results and conclusion 89

4.2. Main study 92

4.2.1. Objectives 92

4.2.2. Sampling design 92

4.2.3. Instruments 96

4.2.4. Data collection 96

x

4.2.5. Statistical methodology 97

4.2.6. Confirmatory factor analysis 97

5. ANALYSIS AND RESULTS 108

5.1. Demographic and organizational profile 109

5.2. Normality and reliability measurements 110

5.3. Confirmatory factor analysis 111

5.4. Path Analysis - SEM 113

5.4.1. Survey related terms 115

5.4.2. The analysis 119

5.5. Independent sample t – test. 125

6. CONCLUSION AND RECOMMENDATIONS 127

6.1. Comparison of results and discussion 129

6.2. Implications 135

6.3. Recommendations 137

6.4. Limitations 145

REFERENCES 148

APPENDICES 182

xi

LIST OF TABLES

Table Description Page No.

3.1. Hypothesized relationships and theoretical support. 76

4.1. Demographics and respondents profile – pilot study. 89

4.2. Reliability statistics and scales – pilot study. 91

4.3. Finding a base sample size. 93

4.4. Distribution of respondents among provinces. 95

5.1. Demographics and respondents profile – Main study. 109

5.2. Uni – variate statistic for shape of distribution. 110

5.3. Reliability statistics of scales. 111

5.4. Summary of CFA and Model fitness. 113

5.5. Fit of the model. 121

5.6. Hypothesis testing based on Regression Weights. 121

5.7. Independent sample t – test. 126

xii

LIST OF FIGURES

Figure Description Page No.

3.1. Illustration by figure of hypothesis. 65

4.1. Single factor analysis for perceived workload increase. 98

4.2. Single factor analysis for role overload. 99

4.3. Single factor analysis for work life balance. 100

4.4. Single factor analysis for life satisfaction. 101

4.5. Single factor analysis for job satisfaction. 102

4.6. Single factor analysis for employee retention. 103

4.7. Single factor analysis for organizational commitment. 104

4.8. Single factor analysis for employee productivity. 105

4.9. Single factor analysis for employee productivity revised. 106

5.1. Results of tested model. 120

xiii

LIST OF APPENDICES

Appendix Description Page No.

A Cover letter for the survey. 183

B Questionnaire for the study. 184

xiv

LIST OF ABBREVIATIONS

AGFI Adjusted Goodness of Fit Index

AMOS Analysis of Moment Structures

AOC Affective Organizational Commitment

AUTO Autonomy

BLU Baluchistan

CFA Confirmatory Factor Analysis

CFI Comparative Fit Index

Chi – Sq. Chi – Square

COC Continuance Organizational Commitment

CR Critical Region

df Degree of Freedom

EFCY Efficiency

EP Employee Productivity

ER Employee Retention

FDR Federal

GFI Goodness of Fit Index

HBL Habib Bank Limited

HRD Human Resource Development

HRM Human Resource Management

JA Job Autonomy

KP Khyber Pakhtoonkhwa

Mgt. Management

MSQ Minnesota Satisfaction Questionnaire

NOC Normative Organizational Commitment

OC Organizational Commitment

P – J Person Job

PTCL Pakistan Telecommunication Company Limited

PUN Punjab

RMSEA Root Mean Square Error of Approximation

xv

RO Role Overload

SD Standard Deviation

SE Standard Error

SEM Structure Equation Modeling

SND Sindh

SPSS Statistical Package for Social Sciences

SWLS Satisfaction With Life Scale

TIME Meeting Time Demands

TLI Tucker-Lewis Index

WFC Work Family Conflict

WLB Work Life Balance

WLI Workload Increase

xvi

DEDICATION

If you are planning for ONE year, grow rice.

If you are planning for TEN years, grow trees.

If you are planning for HUNDRED years, EDUCATE your children.

- Confucius

Dedicated to educationists

xvii

ACKNOWLEDGEMENTS

I have no words to express my gratitude to ALMIGHTY ALLAH, THE

MOST MERCIFUL, THE MOST BENEFICIENT AND THE GRANTER

OF GRACES, who enabled me with strength and courage to learn and

contribute a drop in the ocean of the knowledge.

I would like to express my sincere gratitude to my supervisor, Professor Dr.

Mehboob Ahmad, whose expertise, vast knowledge, outstanding command

over research methods, economics, family matters, curriculum development

and patience, added considerably to my research work. He was always ready

to guide me and gave a more than enough time for my research work. I

doubt that I will ever be able to convey my appreciation fully, but I owe him

my eternal gratitude.

I am grateful to Professor Dr. Muhammad Iqbal Saif, Dr. Muhammad

Nadeem Safwan and Dr. Humayun Naeem who motivated and encouraged

me to develop a focus and become interested in Ph. D. studies. Moreover I

am grateful to Dr. Kashif Ur Rehman for his moral support and the time

spared for guidance.

I would like to thank all of my family members specially my beloved Father

for moral support and kind guidance they provided me throughout the

completion of this research work, in particular at all stages of the research

work. Without their cooperation, guidance and encouragement, it would not

have been possible.

I am grateful to the Higher Education Commission of Pakistan (HEC) for

facilitating the research work. HEC has provided access to major published

research data bases. Without the support of HEC this research study would

have been too difficult to complete.

By summarizing, I recognize that this research would not have been possible

without the input of respondents and express my gratitude to them for their

inputs and time. I would like to thank all those people who made this thesis

possible and a great experience for me.

xviii

ROLE OF WORK LIFE BALANCE IN MAINTAINING THE

PRODUCTIVITY AMONG LAYOFF SURVIVORS

ABSTRACT

The cut throat competition, economic dependency and scarcity of resources pressurize the

organizations to opt for restructuring. Restructuring has been one of the main areas of

policy making in developed countries and transition economies but little evidence is

available regarding developing countries. Now the trend has set in to adopt the same

strategies in the developing countries as well. Mostly organizations go for downsizing to

avoid the negative effect of the operations and to avoid low profitability. Research on the

effects of downsizing has focused on global, organizational and the individual levels.

However, this research, conducted at the individual level, focuses specifically on the after

effects of downsizing on the survivors. Downsizing refers to activities undertaken by

management to improve the efficiency, productivity, and competitiveness of the

organization by reducing the workforce size. The researchers across the globe have

explained the types of response one can expect from survivors of organizational

downsizing. The purpose of this research is to examine the relationship of several

variables effecting survivors. This is accomplished by systematically analyzing the

responses of layoff survivors. This study examines how the perceived workload increase

affects the actual role overload of layoff survivors. Moreover, this study examines the

effects of role overload on job satisfaction, life satisfaction and work - life balance of

layoff survivors. How perceived work - life balance effects their job and life satisfaction,

retention and organizational commitment. Study also looks into the relationship of job

satisfaction and life satisfaction, retention and organizational commitment with layoff

survivors’ productivity using questionnaire. The data was obtained form the layoff

survivors working in two major organizations of the country including Pakistan

Telecommunication Company Limited (PTCL) and Habib Bank Limited (HBL). These

organizations laid - off their employees in the recent past. Path analysis, a segment of

structural equation modeling is used to test the model and the hypothesis. The results of

the study are based on 450 responses retrieved from layoff survivors. Mostly the

measures for the assessment of the variables included in the study are adopted from the

xix

previous available research studies but a few minor changes are made as per requirements

of the study. The findings show that higher level of perceived work loads are positively

related to role overload, a type of stress, and role overload negatively affects the work -

life balance, job satisfaction and life satisfaction of layoff survivors. Rational quantity of

workload is necessary for ensuring employee performance where as the excessive

workload harms productivity. The work - life balance practices in the organization

positively effect job satisfaction, retention of layoff survivors in the same organization,

their organizational commitment and life satisfaction. Finally the job and life satisfaction,

retention and commitment of layoff survivors effect their productivity positively. This

study is beneficial for the organizations going for downsizing; to manage their activities

and employee related issues regarding work, life and employee productivity.

Key Words: Downsizing, Layoff, Work Life Balance, Job Satisfaction and Life

Satisfaction, Employee Retention, Organizational Commitment and

Employee Productivity, Pakistan.

Layoff Survivors’ Productivity 1

Chapter 1

Introduction

Background

Problem area of study

Knowledge gap

Problem statement

Research objectives

Significance of the study

Academic contributions

Concepts and definitions

Organization of the dissertation


Chapter 1

Introduction

Work force reduction is an important issue concerning organizations in a competitive

world. Chapter one presents the over all picture of the dissertation. Specifically the

researcher discusses the background of the study, the objectives, the knowledge gap and

the significance of the study.

1.1. Background

Layoffs, downsizing, rightsizing, reduction - in - work force, all of these terms, for

employees, mean having no more job. Employees and their loved ones may experience

anxieties due to this happening. Leaving the job is a whirlwind of uncertainty and a state

of near panic for the employees leaving a job. On the other hand those who are left

behind also have to face a lot of difficulties in terms of job insecurity and mistrust in

senior management. Here the role of management comes to action to pull up the morale

of the remaining employees and motivate them to work in an effective manner.

Work - Life Balance (WLB) is an ever emerging issue and has great importance

for the management of the organizations, governments, research scholars in the recent

past (Fleetwood, 2007; De Cieri, Holmes, Abbott, & Pettit, 2005; Scholarios, & Marks,

2004; Nord, Fox, Phoenix, & Viano, 2002; Pocock, van Wanrooy, Strazzari, & Bridge,

2001; Russell & Bowman, 1999) and has impact on different organizational and

individual issues. Breakspear and Hamilton (2004) mention that employees should seek

balanced work and life otherwise they tend to hinder the productivity of both the

organization and other colleagues. Other researchers mention that organizations could

adopt the strategy of enhancing productivity, reducing stress among employees,

absenteeism, annual medical expense by adopting work - life balance practices efficiently

(Smith & Gardner, 2007). Work - life balance is one way of providing employees with

alternative work arrangements to keep them motivated and to maintain the higher level of

productivity among them.

Konard and Mangel (2000) examined the relationship of adopting work - life

programs and their impact on firm productivity. They surveyed 658 Human Resource


Executives and revealed that professionals and women were the two major groups which

were positively related to the development of widespread work - life programs. Moreover

they also revealed that work - life programs had positive impact on the productivity when

women and professionals comprised a larger percentage of the workforce.

Schermerhorn, Jr., Hunt, & Osborn (2002, p. 255) states that the factors that

separate organizations from their competitors include the enhancement of knowledge,

skills, abilities and commitment of the employees working for the organization. The

companies that manage employees well outperform the companies that do not.

The success of any organization lies in the truth that how the organization thinks

about itself and its people so that it makes the way to profits, productivity, innovation,

and real organizational learning (Schermerhorn et al., 2002).

The current study examines the role of work - life balance among layoff

survivors. Layoff survivors are the outcome of reduction in the work force (downsizing).

Downsizing may be considered in terms of compulsory reduction in the work force or it

may be cutting down the work force by offering them different benefits. The study

concentrates upon the after effects of the downsizing, such as layoff survivors.

Downsizing is an unavoidable phenomenon for the organization of today’s world.

Different words are being used by different researchers for the concept of downsizing

such as restructuring, work force reduction etc. (Sronce & McKinley, 2006). Chu and Ip

(2002) reported that in USA, since the beginning of 2000, 53 internet businesses have

closed and more than 24,000 employees had been laid off since November 2000. In the

Hong Kong dot.com companies laid off over 1300 employees in the year 2000. An

organization’s conscious plan of workforce reductions in an attempt to improve its

efficiency and/or effectiveness is known as downsizing (Budros, 1999). Downsizing is a

strategy that affects the volume of the work force, the cost and the work processes

(Cameron, 1994). In the words of Hall (1996); Mroczkowski and Hanaoka, (1997),

downsizing is a process of shrinking the size of an organization. It is defined as conscious

work force decrease by an organization (McKinley, Zhao & Rust 2000).

Organizations have different objectives to achieve with respect to Human

Resource Management (HRM) and enhancing employee productivity. In their effort of


achieving high productivity organizations have to recognize the value of a qualified,

motivated, stable, and responsive team of employees (Huselid, 1995).

Researchers have highlighted that the successful downsizing is one in which

special attention is paid to both the employees, those who have lost their jobs and those

who have not (Cameron et al., 1993).

The current study concentrates on only those people who are still working in the

same organization after downsizing that are the layoff survivors. Layoff survivors

perceive increased workloads as a result of absorbing the responsibilities of their co -

workers who have been laid off (Fong & Kleiner, 2004; Virick, Lilly & Casper, 2007).

The layoff survivors are the outcome of the downsizing which organizations do over a

period of time to improve their efficiency and effectiveness and to manage their

expenses. On the other hand layoff survivors have to face work and role overload and this

over load results in employee turnover, absenteeism and may result in low productivity.

Grunberg, Anderson-Connolly and Greenberg (2000) reveal that perceptions of unfair

treatment of layoff survivors are associated with lower commitment regardless of

employee position. Close contact with layoffs is found to be associated with the greater

use of sick hours by the professionals and managers and lower use of sick hours and

higher work effort by employees holding lower positions.

Layoff survivors have to confront different problems including role overload.

Role overload results in low job satisfaction (Yousef, 2002) and life satisfaction

(Evandrou & Glaser, 2004). The layoff of employees may result in anger, lost confidence

in management, insecurity, guilt, decline in loyalty, impairment caused by job insecurity,

unfairness, anxiety, depression, decreased motivation, dissatisfaction with the planning

and communication, loss of credibility in the firm's management team, increased stress

level (Appelbaum & Donia, 2000; Noer, 1993; Thornhill & Saunders, 1998) and

frustration among the layoff survivors (Virick et al., 2007).

Guiniven (2001) discusses the new era of Human Resource Management and

highlights downsizing as an economic aspect, creating a serious problem among layoff

survivors. Author found out that disloyalty, disaffection, increased absenteeism, and acts

of sabotage were rising among workers who viewed downsizing not an economic issue

but as a social issue. He also mentioned that layoffs were the outcome of downsizing


which invariably occurred in bad economic times that was in the late 1970’s and the

competition encouraged employers to implement strategies focused on reducing current

labor costs. Organizations that ignored the human side ran risks in the aftermath of

downsizings.

Robbins (1999) mentions that indications of this sickness (downsizing) may

include job insecurity, perceptions of unfair treatment by the organization, depression,

stress created by increased work loads, fear of change, disloyalty by the employees, loss

of commitment, reduced risk taking, lack of motivation, loss of confidence in the upper

management, un - willingness to do anything beyond the required minimum, sense of

being less informed, and feelings of anger. These psychological states influence

motivation level, job satisfaction, work performance and commitment to the

organizations among layoff survivors.

Most of the related studies have been carried out on layoff survivors in the

Western countries of the world (Virick, et al., 2007; Sronce & McKinley, 2006; Farrell

& Mavondo, 2005; Sturges & Guest, 2004; Guiniven, 2001; Budros, 1999). Such studies

are still needed to be carried out in the other parts of the world especially in the

developing countries. This is so because no such research, of which researcher is aware

of, has been carried out, on layoff survivors, in this part of the world in general and in

Pakistan in particular. This study examines the role of work - life balance among layoff

survivors in two organizations of Pakistan including Pakistan Telecommunication

Company Limited (PTCL) and Habib Bank Limited (HBL), which have cut down their

work force in the recent past.

1.2. Problem area of study

Researchers have time and again highlighted the issues related to the downsizing and its

effects on the performance, efficiency and effectiveness of the left over employees in the

work organizations (e.g. Charles & Harris, 2007; Virick et al., 2007; Grunberg,

Anderson-Connolly & Greenberg, 2000; Mishra & Mishra, 1994: Casio, 1993) and how

progressive organizations have been trying to overcome these problems.

The problem area relates to the maintenance of productivity among layoff

survivors in the presence of perceived work - life balance effecting job and life


satisfaction, layoff survivors’ retention and their organizational commitment in the

organizations operating in Pakistan.

The study looks at the importance of maintaining productivity among layoff

survivors after a big layoff. Layoff has psychological effects on the employee

performance that may result in decreased productivity. After the layoff there is a need to

maintain the productivity among layoff survivors to carry out operations in an

organization for its successful accomplishment of goals.

The researchers have defined work - life balance as the management of the

individuals’ work and other domains of life, without a conflict or opposition of one

domain to the other (Blunsdon, Blyton, Reed, & Dastmalchian, 2006).

Breakspear and Hamilton (2004), Konard and Mangel (2000) and Smith and

Gardner (2007) have highlighted the importance of work - life balance practices having

positive effects on productivity. The productivity of employees has been defined by the

Corporate Leadership Council (2003) as the amount of time an employee physically

performs a job and it also includes the extent to which an employee is efficiently

functioning or “mentally present” while at job.

In this research the researcher intend to examine relationship among different

variables by developing a model in the light of available literature. The variables

examined are post layoff perceived workload increase, role over load and its relationship

with other factors such as work - life balance, job satisfaction, life satisfaction and the

relationship of job satisfaction, life satisfaction, employee retention and organizational

commitment with productivity of layoff survivors.

1.3. Knowledge gap

The research studies available in the literature have discussed the issues like downsizing,

layoff survivors and work - life balance in the western part of the globe (Virick, et al.,,

2007; Charles & Harris, 2007; Sronce & McKinley, 2006; Farrell & Mavondo, 2005;

Sturges & Guest, 2004; Budros, 1999; Kane, 1999; Cameron, 1994; Freeman, 1994). But

none, up to the researcher’s knowledge, of these have examined the role of work - life

balance in maintaining the productivity among layoff survivors through job and life

satisfaction, employee retention and organizational commitment. Each culture is different


and has diverse effects on issues (Hofstede, 1983), therefore there is a need to address

these issues and problems in a country like Pakistan. This study is the first attempt in

Pakistan to highlight issues relating “layoff survivors”. This study also makes suggestions

to the organizations which intend to go for layoff schemes like Voluntary Separation

Scheme (VSS) and Golden Handshake (GHS) and to maintain the satisfactory level of

employee productivity to carryout organizational activities. Previous researches about

survivors have found that downsizing and job insecurity negatively effect survivors’ well

- being (Hartley, Jackson, Klandermans, & van Vuuren, 1991; Ashford, 1988) and work

attitudes (Brockner, Tyler, & Cooper- Schneider, 1992). This study examines and tests a

model (Figure 3.1) about layoff survivors of two main organizations of Pakistan.

In the galaxy of research the researchers have conducted studies on the issues

related to workload (e.g. Skinner & Pocock, 2008; Adebayo, 2006), role overload (Perry-

Jenkins, Goldberg, Pierce, & Sayer, 2007; Thiagarajan, Chakrabarty & Taylor, 2006;

Evandrou & Glaser, 2004), work - life balance (Charles & Harris, 2007; Brough, Holt,

Bauld, Biggs, & Ryan, 2008), job satisfaction (Alqashan & Alzubi, 2009; Moyniohan &

Pandey, 2007; Wright & Bonett, 2007; Lingard & Sublet, 2002), life satisfaction (Karimi,

2009; Judge et al., 2005; Rode, 2004), organizational commitment (Solinger, Van Olffen,

& Roe, 2008; Perry, 2004), employee retention (Jensen, McMullen, & Stark, 2007;

Brown & Schainker, 2008; Kim & Lee, 2007), and employee productivity (Yu & Park,

2006; Giles & Campbell, 2003; Chan & Kaka, 2007; Forde, Slater & Spencer, 2006) but

none of these have considered all the above variables at one place in the form of a model

(Figure 3.1).

The author is inspired by the previous researches. The model discussed in this

study is the improved form of model earlier presented by Virick, Lilly and Casper. They

examined how increased workload and role overload of layoff survivors related to their

work life balance, job satisfaction and life satisfaction. They joined two main streams of

studies earlier carried out under the job loss literature and the work life balance literature.

Virick, Lilly and Casper (2007) revealed that high workloads experienced by

layoff survivors are a cause of reduced job satisfaction and life satisfaction and work -

life balance play the role of a mediator. The authors suggest that more researches should

be carried out to determine the generalizability of the findings of their study.


The present study has made contributions to fill the gap by testing the relationship

of job satisfaction, life satisfaction, employee retention and organizational commitment

with employee productivity in culturally different settings. Committed employees

generally tend to remain in the organizations and contribute in the successful operations

of the organizations and ultimately are related to the better productivity (Salami, 2008;

Perry, 2004). So, keeping in mind the above stated importance the variables of employee

retention, organizational commitment and employee productivity are added to the model

earlier presented by Virick, Lilly and Casper.

Additionally, Virick et al. (2007) conducted research study in a single technology

based industry like previous research studies by Weber, and have only focused on the

managerial and professional jobs (Virick et al., 2007). Where as the current study

concentrates on examining the relationship of variables in the diverse industries including

the telecommunication and the banking industries. Moreover the sample includes all the

levels of management such as the top managers, the middle level managers and the first

level managers whereas the earlier studies only focused on examining the high tech

employees.

In the previous studies the authors have reported that their findings could not be

generalized as they have considered only a singly industry (Virick et al., 2007). Where as

the findings of the current study may be generalized to the organizations undergoing

downsizing.

Moreover the current study examines whether there is a difference between mean

scores of several variables among two different groups of layoff survivors working at

Pakistan Telecommunication Company Limited and Habib Bank Limited, that has not

been examined earlier.

In addition to few gaps identified for the study the relationship of work -life

balance with job satisfaction, employee retention, organizational commitment and life

satisfaction and the relationship of these four variables (job satisfaction, employee

retention, organizational commitment and life satisfaction) with employee productivity,

has not been simultaneously examined earlier.


1.4. Research problem(s)

More specifically the subject study investigates the following issues:

What is the effect of role overload on the work - life balance, job satisfaction and

life satisfaction of the layoff survivors?

How work - life balance effects job satisfaction, employee retention,

organizational commitment and life satisfaction of the layoff survivors?

How employee productivity is affected by job satisfaction of layoff survivors,

their retention organizational commitment and life satisfaction in the presence of

layoff survivors’ perception about work - life balance.

1.5. Research objectives

The objectives mainly to be addressed in the current study are discussed as follows:-

To highlight the significant factors effecting layoff survivors’ productivity in the

organizations operating in Pakistan.

To test the extended model in a culturally different settings in a sample of layoff

survivors.

Downsizing give rise to many problems faced by layoff survivors, perceived work

overload and role overload are among those problems mentioned by the

researchers in different research studies and leftover employees, following

downsizing, may come across unique work - life problems because they have to

face increased role overload. Another objective of this research is to analyze the

relationship of role overload with work - life balance, job satisfaction and life

satisfaction of layoff survivors.

Work - life balance facilities are provided by the organizations to their employees

to comfortably carryout work and non - work activities, so the next objective of

the research is to analyze whether work - life balance is positively or negatively

related to job satisfaction, layoff survivors’ retention, organizational commitment

and life satisfaction.

Additionally, to examine the relationship of layoff survivors’ retention,

organizational commitment, job satisfaction and life satisfaction with layoff

survivors’ productivity.


Further it is examined whether there are any differences of mean scores among

layoff survivors of HBL and PTCL with respect to the variables included in the

model.

Last but not the least objective of the study is submission of research work as

dissertation for the completion of doctorate degree in management sciences from

Foundation University Institute of Engineering and Management Sciences

(FUIEMS), Foundation University Islamabad, Pakistan.

All that needed is to understand the importance of maintaining the productivity

among layoff survivors because the people who have under gone the process of

downsizing lose the confidence in the organization, experience insecurity guilt,

frustration, perceived unfairness and loss of productivity.

1.6. Significance of the study

The study proves to be significant for its focus on layoff survivors of the two giant

organizations operating in Pakistan. The combination of different variables in the form

of a model tested in a Pakistani sample reveals the results beneficial for the management

of organizations considering the option of downsizing. Firstly, the relationship of role

overload with work - life balance, job satisfaction and life satisfaction is examined.

Afterwards, the relationship of work - life balance with job satisfaction, employee

retention, organizational commitment and life satisfaction is analyzed. At third stage, the

study examines the relationship of these four variables (job satisfaction, layoff survivors’

retention, organizational commitment and life satisfaction) with employee productivity

that has not been examined earlier. The results of the current study prove to be a source

of generalization of results of the few relationships tested earlier by the researchers in

different parts of the world.

Employee productivity remains the crucial concern for the management of the

organizations. Many studies emphasize the importance of maintaining and enhancing the

employee productivity for the betterment of organizations.

The study also remains significant by filling the existing knowledge gap regarding

the role of work - life balance in maintaining productivity among layoff survivors. This

study highlights the importance of work - life balance for increased productivity in the


Pakistani environment. The work - life balance phenomenon differs in culturally

diversified environment (Asadullah & Fernández, 2008). So there is a need to explore

the same in other cultures like Pakistani culture.

This study can help the practitioners, bank managers, academicians and policy

makers working in different organizations to find out the most important factors that

effect layoff survivors productive in Pakistan.

This study also contributes to the available literature by developing and testing an

improved version of the model related to the productivity of layoff survivors. One of the

related models has already been tested in United States of America among layoff

survivors by Virick, Lilly and Casper in the year 2007.

1.7. Academic contributions of the present study

This study identifies a gap in existing research and contributes to the existing literature as

follows;

1. Extensive literature is available regarding the concept and importance of job

satisfaction of employees, organizational commitment and employee retention.

There is a lack of empirical research focusing on work - life balance and its

relationship with these variables in the developing countries. This is the first

empirical, model based study on the relationship of the variables mentioned. This

study, therefore, offers important contributions to the existing literature.

2. The impact of constructs such as job satisfaction, life satisfaction, layoff survivors

retention and organizational commitment, which are the out comes of good work -

life balance, have rarely been investigated with respect to layoff survivors

productivity. This study empirically demonstrates the influence of these variables

on layoff survivors’ productivity.

3. There is no substantial empirical research on layoff survivors’ productivity.

Researchers in developing countries, like Pakistan, have rarely addressed the

issues of role overload, work - life balance and employee productivity.

4. This study examines the impact of job satisfaction, life satisfaction, employee

retention and organizational commitment on employee productivity in the


organizations which have undergone the process of restructuring. There are near

to none empirical studies highlighting such relationships.

5. This study reports the differences of mean scores among layoff survivors’

experiences with respect to perceived workload increase, role overload, work -

life balance, job satisfaction, life satisfaction, employee retention, organizational

commitment and productivity, in the two organizations such as Habib Bank

Limited and Pakistan Telecommunication Company Limited.

1.8. Concepts and definitions.

The overview and the definitions of the variables used in the model are explained below.

The concepts are used by different researchers and are defined in their research studies

which help the researcher to clearly understand the meanings of the terms used.

1.8.1. Post - layoff perceived workload increase.

Perceived work overload increase (WLI) reflects a situation in which an individual thinks

he has too much to accomplish in an inadequate span of time (Frone et al., 1992).

Workload increase is also termed as work overload by various researchers (Elloy &

Smith, 2003; Brown & Benson, 2005; Skinner & Pocock, 2008). Work overload occurs

where multiple demands exceeds resources (Elloy & Smith, 2003). Some authors have

also mentioned two types of work overload, qualitative and quantitative. The former

refers to a situation where the task is too difficult to accomplish and the later refers to a

situation where one has to accomplish too many tasks.

Skinner and Pocock (2008) state that work overload is one of the factors of work

demands also known as quantity of work. Whereas Brown and Benson (2005) state that

work overload is the extent to which the job performance needed in a job is too much or

overload due to performance needed on a job (Iverson & Maguire, 2000).

1.8.2. Role overload.

One of the outcomes of work load increase and role stress is role overload (RO). It has

been suggested that self threat experienced by layoff survivors results in anxiety, job

insecurity and stress. These all factors result in role stress. Tetrick (1992) mentions role


stress as a perception pointed out by ambiguity, conflict, and overload arising from the

features of individual and the organizational environment.

Only one aspect of role stress is used for the current study that is role overload.

The role overload can be experienced by the employees when they have too little time,

resources and capabilities to accomplish their role behaviors (Rizzo, House, & Lirtzman,

1970). Reilly (1982) defines role overload as conflict occurring when the level of demand

goes beyond a person’s available resources, when a person has too many tasks to do. The

extent of role overload depends on the level of demands imposed on the person and other

factors in the person’s environment.

Role overload occurs when too much is expected and the individual feels

overwhelmed with work (Schermerhorn, Jr. Hunt, & Osborn, 2002). Home (1998) state

that role overload is the situation where there is insufficient time to meet all the demands

of the work. Role overload is the opportunity of satisfying the requirements of some

given roles at the expense of other role expectations (Greenhaus & Beutell, 1985).

Simply it is “too much to do and too little time to do them” (Adebayo, 2006). Role

overload can be described as a situation in which employees feel that there are too many

responsibilities or activities expected of them in respect to their available time and

abilities (Pareek, 2002; Dasgupta & Kumar, 2009).

Thiagarajan, Chakrabarty and Taylor (2006) state that role overload exists when

the total demands on time and energy related to the set activities of multiple roles are too

vast to perform the roles adequately or comfortably (Voydanoff, 2002). Conley &

Woosley (2000) note that role overload exits when role expectations are more than the

individual’s abilities and motivation to do a task. Moreover they also state that it is the

feeling of not being able to finish a given task within a given period of time. Role

overload is the stage when an employee is much involved in one role and unable to

maintain balance with other (Nadeem & Abbas, 2009).

Role overload is an extra pressure put on an employee to do more work when it is

difficult for him/her to complete a “normal” day’s work (Glazer, 2005). Hang-yue, Foley,

and Loi (2005) state that role overload is prominent among the clergy, because of

irregular working schedules that often include unpaid overtime and an expectation of


high involvement in various roles related to work. Overload is the too much work or

work that is outside one's capability (Bashir & Ramay, 2010).

Jones, Chonko, Rangarajan and Roberts (2007) defines role overload as the

degree to which persons are overtaxed cognitively as a result of being under time

pressure and having too many commitments and responsibilities. Theoretically however,

the best possible level of workload exists where work is challenging and demanding

enough of employees’ time, skills and abilities to keep them engaged, committed and

satisfied, but not so high as to be de-motivating (Pienaar, Sieberhagen & Mostert, 2007)

1.8.3. Work - life balance.

It is the third variable included in the model. Work - life balance (WLB) or work - family

balance are terms commonly used for the concept but work life balance is a vast term in

terms of subject matter as compared to work family balance. It is about achieving the

balance between family roles in addition to other domains of life, not only family roles.

Family roles are confined to only family matters leaving all other aspects of life. As

suggested by Blunsdon et al. (2006) that work - life balance means that one can manage

both work and other domains of one’s life, without a conflict or opposition of one domain

to the other.

From an employee point of view, work - life balance is the maintenance of a

balance between work responsibilities and home responsibilities. Employers view the

benefits or working conditions that are, provided by them, to help employees balance the

family and work domains (Bardoel, Tharenou, & Moss, 1998; Russell & Bowman, 2000).

Guest (2002) defines work - life balance in subjective and objective terms, the

subject measure is regarding individuals’ perception about a balance between their work

and the other aspects of life, whereas the objective measure of work - life balance is the

consequences of the behavior such as time spent on the work or other demands. A policy

made by the organization to help their employees to better balance their work and life

roles is known as work - life balance policy (Eaton, 2003; Konard & Mangel, 2000)..

Reiter (2007) categorizes the definitions of work - life balance according to a

framework of ethical ideologies. The author mentions that each work - life balance

definition has a value perspective that determines what factors will be seen as relevant to


achieve balance, and definitions can be categorized according to these value perspectives

using taxonomy of ethical ideologies. Understanding the value perspective is crucial to

appropriate application of definitions.

The author further state that almost every article on work - life balance has a

different definition of what work - life balance actually “is” and definitions of work - life

balance can be considered according to the extent to which the definition implies

universal rules of what balance “is” versus definitions that are relative to an individual as

well as the idealism of the definition.

Another definition given by the New Zealand Department of Labor (2004) is

creating a productive work culture where the potential for tensions between work and

other parts of people’s lives is minimized (Malik, Saleem & Ahmad, 2010).

1.8.4. Job satisfaction.

Job satisfaction (JS) is specific to one’s job (Wright & Bonett, 2007) and is defined as a

“pleasurable or positive emotional state resulting from one’s job or career” (Locke,

1976, p. 1304). Other researchers state that it is the pleasurable or positive emotional

state resulting from the appraisal of one’s job or job experience (Moynihan & Pandey,

2007; Hancer & George, 2003; Alqashan, & Alzubi, 2009). Job satisfaction is generally

measured by different facets which relate to an employee’s satisfaction with work, pay,

rewards, promotion, and co-workers that contribute to an overall measure of employee

job satisfaction. Job satisfaction is an added response to a particular job or various facets

of it (Ahmed, Muddasar & Perviaz, 2012).

Job satisfaction is the contentedness of employees with their work. Many factors

can influence a person’s level of job satisfaction, such as; the level of pay and benefits,

perceived fairness of the promotion system, the quality of the working conditions,

leadership and social relationships (Nizami et al., 2006).

Job satisfaction is an enjoyable or positive emotional state resulting from the

appraisal of one’s job (Howard, Boles & Donofrio, 2004). Armstrong (1996) defines job

satisfaction as the attitudes and feelings people have about their job. Positive and

favorable attitudes towards the job show job satisfaction and negative and unfavorable

attitudes towards the job show job dissatisfaction. Job satisfaction is the fulfillment or


gratification of certain needs that are related to the work (Hopkins, 1983; Lambert &

Paoline, 2008). It is the degree that a person likes his/her job (Spector, 2003; Lu, While &

Barriball, 2005; Lambert & Hogan, 2008).

Lambert, Hogan and Barton (2002) noted job satisfaction as a subjective,

individual - level feeling reflecting whether a person’s needs are or are not being met by a

particular job. Job satisfaction is an affective or emotional attitude of an individual

towards his/her job (James & Jones, 1980). It is a general approach towards a job and

some specific facet of it (Knoop, 1995). Job satisfaction is an affective response by

people toward their jobs (Cranny, Smith & Stone, 1992). Job satisfaction is a general

feeling about a job or career in terms of specific aspects of the job or career (Thompson,

Thompson & Orr, 2003).

Job satisfaction includes general elements and specific elements: the whole

perception of job pleasure is deemed as general elements; job security, pay, co - worker,

supervision and personal growth and development are deemed as specific elements of the

satisfaction from job (Hackman & Oldham, 1980). Malik, Saleem and Ahmad (2010)

report job satisfaction as the degree to which people like their jobs.

1.8.5. Life satisfaction.

It is the satisfaction with specific domains of life (Diener, 1984; Iverson & Maguire,

2000). Some of the researchers focused on the global aspect of the life satisfaction (LS)

(e.g. Judge & Watanabe, 1993; Judge, Locke, Durham, & Kluger, 1998) where as few

other researchers focused on the facets of life satisfaction (e.g. Andrews & Withey, 1976;

Iverson & Maguire, 2000).

Life satisfaction is conceptualized as the result of satisfaction with various life

domains such as work, family, health, etc., and the effects of environmental conditions on

life satisfaction are assumed to be largely mediated by satisfaction with life domains.

Research studies indicate that satisfaction with work and non-work domains accounts for

about 50 percent of the variance in life satisfaction (Andrews & Withey, 1976; Hart,

1999; Near, Smith, Rice, & Hunt, 1984).

The terms associated with life satisfaction include quality of life, well - being.

Throughout the current discussion the term well - being will be used more or less


interchangeably with life satisfaction. An important consideration that needs to be taken

into account when conceptualizing life satisfaction is the point of reference from which

the concept is measured.

Sousa and Lyubomirsky (2001) believe that satisfaction with one’s life implies a

satisfaction with or acceptance of one’s life circumstances, or the fulfillment of one’s

wants and needs for one’s life as a whole. Tang (2008) states that Diener (1984) grouped

the definition of well - being into three divisions. Firstly, well - being is defined by

external criteria such as good quality or holiness. This definition of well- being is not

thought as a subjective state but rather as one possessing some desirable qualities.

Secondly, he categorizes the definition according to the question of what leads people to

assess their lives in positive terms. This definition of well-being is also known as life

satisfaction and depends on the respondents to determine what a good life is. Thirdly, the

meaning of well- being denotes a presence of positive over negative affect (Bradburn,

1969), which highlights pleasant emotional experiences.

Diener et al. (1985) define life satisfaction as a cognitive, judgmental process

which dependent upon a comparison of one’s state of affairs with what is thought to be a

suitable standard. (p.71). Life satisfaction refers to the individual’s positive feeling of

his/her general life (Diener, 1984; Emmons & Diener, 1985; Diener & Diener, 1995;

Lucas et al., 1996; Yetim, 2002; Chen, Cheung, Bond, & Leung, 2006; Çeçen, 2008).

Life satisfaction is one’s positive assessment of his/her entire life according to the

standards determined by the individual himself (Diener et al., 1985).

Life satisfaction does not mean the satisfaction of a specific situation but the

satisfaction of the whole set of experiences. It is the state of well - being in terms of

happiness, morale etc. (Vara, 1999). Life Satisfaction is a subjective and open measure of

human welfare. It is subjective because generally in surveys people are simply asked

whether they are satisfied with their life as a whole and open because researchers do not

pre - define the components of social welfare. It depends upon each individual respondent

to judge whether they are satisfied (Donovan & Halpern, 2002).

Arslan, Hamarta and Uslu (2010) note that life satisfaction point outs the result

which appear after the comparison of individual’s expectations with the real situation.

Generally life satisfaction includes one’s whole life and the various dimensions of life.


Life satisfaction is the individual’s experiences in the important life areas such as life,

school, job, family, etc. which create positive feelings are more in number than the

experiences that create negative feelings (Diener, 2000).

1.8.6. Organizational commitment of layoff survivors.

Organizational commitment (OC) is defined as the extent to which the employees feel

devoted to their organization (Spector, 2000). Many researches relating to organizational

issues found that commitment is a diverse concept and is divided into three facets such as

affective, continuance, and normative, each with its own underlying ‘psychological

states’ (Meyer & Allen, 1991). Organizational commitment can also be defined as the

degree to which an employee is dedicated and loyal to their organization (Spector, 2000).

Lancaster and Velden (2004) shed light on the concept of organizational

commitment by defining it as the relative strength of identification and involvement of

organizational members with in an organization. Organizational commitment is a vast

researched area by the researchers (Ogba, 2008), that revealed some common themes

such as organizational attachment, higher switching costs for employees and loyalty to

the organization (Meyer & Allen, 1991; Ogba, 2008). Commitment of employees to the

organizations results in the favorable organizational outcomes. There is a need to retain

the committed employees to achieve the organizational goals.

Yousef (2002) defines the same concept as an employees feeling of obligations

towards their organization. Allen and Meyer (1990) differentiate between two types of

organizational commitment that are, affective commitment that is an emotional

attachment to an organization, and continuance commitment that is remaining with an

organization because there is no other and better alternative.

1.8.7. Employee retention.

Employee retention (ER) can better be understood as the ability of an organization to

keep people involved in their work (Jamison, 2003). Another researcher defines

employee retention as the skill to keep volunteers involved. The volunteers are the people

who successfully complete their initial commitment and continue serving at the

workplace (Connors, 1995; Jamison, 2003). It is the ability of an organization to hold on


to highly talented core employees which could be important for the future survival of the

organization (Whitner, 2001).

Retention is believed as multifaceted part of an organization’s human resource

strategies. It starts with the recruiting of right people and continues with practicing

programs to keep them engaged and committed to the organization (Freyermuth, 2007).

Johnson (2000) states that employee “retention is the ability to hold on to those

employees you want to keep for longer than your competitors”.

Researchers have constantly identified employees’ expressed intentions to stay as

a reliable antecedent to actual turnover and as reflective of employees’ commitment to

the organization (Griffeth, Hom & Gaertner, 2000; Hom & Kinicki, 2001). Udechukwu

and Mujtaba (2007) define employee retention as an employee’s deliberate willfulness to

stay in the organization.

1.8.8. Employee productivity.

To understand employee productivity (EP) first one has to understand productivity that is

what one can accomplish with material, capital and technology. Productivity is core issue

of personal manner. It is an attitude that one must continuously improve (Japan

Productivity Centre, 1958 - from Bjo¨rkman, 1991).

Another researcher defines productivity as an extent one produces well outcomes

from the resources used. If one produces more or better goods from the same resources, it

is increased productivity. If one produces the same goods from lesser resources, it is also

increased productivity. By “resources”, we mean all human and physical resources, i.e.

the people who produce the goods or provide the services, and the assets with which the

people can produce the goods or provide the services (Bernolak, 1997). Productivity is

the effective use of the available resources to achieve operational goals (Reynolds, 1998;

Reynolds & Biel, 2007).

For the present study the term productivity has been defined as earlier defined by

the Corporate Leadership Council (2003) as employee productivity is the amount of time

an individual is present physically at a job and also the degree to which he or she is

“mentally present” or efficiently functioning while present at a job. The concept is also

defined by Goetzel and Ozminkowski (2002) in one of their writings in the same words.


The productivity is the quantity or volume of the major product or service that an

organization provides (De Cenzo & Robbins, 1994). Pritchard (1992) defined

productivity as a combination of efficiency and effectiveness. The efficiency is the

quality of resources used and effectiveness is the achievement of goals by using the same

resources.

1.9. Organization of the dissertation

The current study comprises six chapters. Chapter one gives an overview regarding the

query by exploring background history and need for the study. It identifies the knowledge

gap and the problem area. It also reveals the objectives of the study, its significance and

rationale. Chapter two consists on rigorous literature review to develop theoretical

framework of the study. Literature review is based on the relevant studies concerning

relationships which a researcher want to test in a form of a model. Chapter three sheds

light on the historical background of the organizations considered for the study. It also

explains variables and constructs included in the model. Thematic diagram is also

presented in this chapter. Chapter four presents the methodology of the study. Chapter

five reflects the analysis and results of the study based on the results of Path Analysis,

Structure Equation Modeling (SEM). Finally, chapter six contains conclusion,

implications, limitations and suggestions arising out of the current study.


Chapter 2

Literature review

Relationship of the variables

o Post layoff perceived workload increase and role overload

o Role overload and work - life balance

o Role overload and job satisfaction

o Role overload and life satisfaction

o Work - life balance and job satisfaction

o Work - life balance and life satisfaction

o Work - life balance and employee retention

o Work - life balance and organizational commitment

o Job satisfaction and employee productivity

o Life satisfaction and employee productivity

o Employee retention and employee productivity

o Organizational commitment and employee productivity

o Work - life balance and employeeproductvity

Summary of the literature review


Chapter 2

Literature review

In this chapter the researcher summarizes the available literature related to perceived

workload increase after downsizing (WLI), role overload (RO), work - life balance

(WLB), job satisfaction (JS) and life satisfaction (LS), employee retention (ER) and

employee productivity (EP) and their relationships. The researcher explores the literature

about the effects of downsizing and its relevance to perceived work load increase. Then

the relationship of role overload with job satisfaction, life satisfaction and work - life

balance is reported. The researcher also reports the relationship of work - life balance

with job satisfaction, life satisfaction, employee retention, and organizational

commitment. Lastly the relationship of these four variables (job satisfaction, employee

retention, organizational commitment and life satisfaction) with employee productivity is

reported. Literature focuses on the findings of the research studies conducted by various

researchers.

2.1. Relationship of the variables

Principal constructs, included in the model, are reviewed in order to develop hypothesis

for the current study. Various researchers have noted that the workplace changes are

affecting the number of hours worked by the employees as well as the intensity of work,

such as, the employees are expected to work harder, faster and are expected to

accomplish more complex activities (Green, 2002). These changes may be driven by the

desire to improve productivity, but it is observed by the researchers that those changes

have not always achieved the intended goals (Gandolfi & Neck, 2003). Related literature

with regards to one by one relationship presented in the model is discussed below.

2.1.1. Post layoff perceived workload increase and role overload.

The evidence is available in the literature that with the increase in the task demands there

is decline in the perceptual sensitivity across the task, accompanied by increase in the

perceived workload ratings (Dember, Warm, Nelson, Simon, Hancock & Gluckman,

1993). Other researchers mention that workers who experience mental and temporal work


demands and frustration report workload (Temple, Warm, Dember, Jones, LaGrange &

Matthews, 2000).

With regards to types of workloads Dasgupta and Kumar (2009) highlighted two

types of workloads namely quantitative workload and qualitative workload. Former arises

when there is increased number of tasks to perform in a specific period of time and later

occurs when the work requirements exceed worker’s intellectual competence and skills.

Various constructs showing employees’ workload, such as perceptions of role

overload or the number of hours spent at work are among the most studied predictors of

work - family conflict (see Eby et al., 2005: Byron, 2005). Byron (2005) states that in

addition to the undesired affect at work and at home, high workload leads to increased

work - to - family conflict. He also notes that in a meta - analytic investigation of cross -

sectional studies the researchers found that work - to - family conflict correlates

positively (r = 0.26) with number of hours worked and (r = 0.65) with perceptions of role

overload.

Bashir and Ramay (2010) identified eleven factors used as antecedents of stress

including overload, role vagueness, role conflict, responsibility for people, participation,

lack of feedback, keeping up with quick technological change, being in an innovative

role, career growth, organizational structure and environment, and recent episodic events.

According to (Rose, 2003) employees have propensity towards greater stress concerning

time, working for longer hours which reduced employees urge for performing better.

Some other researches indicated that one of various stressors in the organization

included overload of the work responsibility (Fields, 2004; Yao, Wang & Zhang, 2007).

Nadeem and Abbas (2009) stated that organizational changes such as downsizing and

restructuring were the reasons for increasing workloads and work stress and decreasing

job security which proved to be a source of work - to - family conflict. Role overload

could result in an employee experiencing anger and frustration toward persons thought

responsible for the overload in work (Marini, Todd, & Slate, 1995).

Shultz, Wang and Olson (2009) carried out a research study to investigate whether

role overload and under - load are related to different negative health outcomes. They

also examined whether different job characteristics like control over work schedule,

differentially buffered the effects of role demands on work stress for workers


experiencing role under - load, role overload or neither. The group of respondents that

experienced neither role overload nor under - load was termed as ‘matched’ The authors

used Euro - barometer Survey on working conditions to investigate the said relationship

and found that role overload had the highest level of all 16 negative health outcomes,

with the role under - load being the next highest. They also revealed that time buffered

stress for the role matched and role under - load groups, while both time and autonomy

buffered stress for the role overload group.

Marks and MacDermid (1996) conducted two studies, first on a sample of 65

wives and mothers who had at - least one child of 18 years or younger living at home and

second study was conducted among 333 college students studying at the University of

Maine. Three hundred and three students responded to the questionnaire resulting in 90 %

response rate.

Authors inferred the association of role balance with indicators of positive

functioning and found no association between the role hierarchy and positive functioning.

Moreover, they found that people who remained more balanced in their systems of roles

and activities scored lower on measures of role strain and depression and higher on

measures of self esteem, role ease and other measures of well - being.

Bliese and Castro (2000) tested whether role clarity (i.e. role ambiguity), like

control, would moderate the relationship between demands and psychological strain.

Secondly, they assessed support (from leaders) as a macro characteristic of the work -

group environment. Data were drawn from a large study of US army constituting of 1786

lower enlisted male soldiers. They observed a three-way multilevel interaction among

work demands, role clarity and support by using Multilevel Random Coefficient

Modeling. The authors revealed that the relationship between demands and psychological

strain was moderated by role clarity; however, the moderating relationship was found

only when work-group support was high. They also found that work overload was

positively related to psychological strain and role clarity was negatively related to

psychological strain.

Rizzo et al. (1970) and Virick et al. (2007) found a relationship between

perceived work loads and actual role overload especially in a sample of layoff survivors.


It seemed more significant to examine the effects of workload on the factors affecting

layoff survivors work experiences.

Researchers noted that due to restructuring organizations were forced to change

and become more effective and efficient in order to familiarize to the changing

environment (Irving & Coleman, 2003; Lopopolo, 2002; Robbins, 2003; Siu, 2003).

Job dissatisfaction was found to be one of the outcomes of work related stress that

might come from excessive work. Moreover work stress affected doctors’ health as well

as their abilities to manage job demands (Dasgupta & Kumar, 2009). Low level of

psychological well - being was found to be another out come of workload that also

resulted in job stress (Greenhaus et al., 1987). Dasgupta and Kumar (2009) concluded

that in the highly competitive world man had to deal with all kinds of stressors that could

affect on all spheres of life.

Quick, Quick, Nelson and Hurrell (1997) stated that role overload could be

distinguished from work overload in a manner that work overload was based on actual

tasks, whereas role overload was based on the behaviors that were expected of the

individual. Role overload occurred when too many behaviors were expected of an

individual or the behavior expected was too complicated or difficult for the individual to

execute.

2.1.2. Role overload and work - life balance.

Role overload whether quantitative or qualitative, is one of the types of stress that have

negative effects on the human health and it also leads to time based stress that demands

balance in work and non - work roles.

Tang and Chang (2010) proposed the effects of role ambiguity and role conflict

(collectively role stress) on employees’ creativity among 202 employees of Taiwanese

companies. The authors revealed a direct and negative connection between role

ambiguity and creativity, and also found a direct and positive connection between role

conflict and creativity. Both self-efficacy and job satisfaction served as partial mediators

between role conflict and creativity. However, only job satisfaction (and not self -

efficacy) was a partial mediator between role ambiguity and creativity.


The worse effects of role stress (role ambiguity) on employee creativity may be

curbed out through employee training and personnel development which emphasize

tolerance of ambiguity and uncertainty in order to reduce role ambiguity.

Skinner and Pocock (2008) used stratified random sampling and gathered 887

responses from full - time employees. They applied Multiple Regression Analysis to

examine the relationship between work - life conflict, work overload, work schedule

control and work hours and work hours fit and revealed that work - life conflict was

strongly associated with work overload followed by work schedule control, work hours

and work hours fit. Authors mentioned three main sources of work - life conflict such as

time based conflict including time pressures, lack of time for family and leisure. Strain

based conflict included anxiety, fatigue and tension. The third source of work - life

conflict mentioned was behavior - based conflict, including incompatible behavioral

expectations between work and home life. The authors compared the time based and

strain based sources of work - life conflict and operationalized long working hours and

work load.

Authors also found that work overload was the strongest predictor of full - time

employees’ work - life conflict. Work hours, their fit with preferences, and control over

work scheduling also demonstrated small to moderate associations with work - life

conflict. Moreover they found that work - life conflict increased with long working hours,

higher workloads and less flexibility. Work overload was found to be the strongest

predictor of work - life conflict. Work overload was the strongest predictor of conflict

among men as compared to women. Instead of work hours fit with preference, the length

of work hours was the strongest predictor of work - life conflict.

Authors concluded that the factors that sustained or hampered a healthy work -

life relationship were multifaceted, and likely to differ depending on an individual life

circumstances, values and priorities. Moreover authors concluded that employers had to

develop work - life policies, procedures and interventions that were concerned with work

time and workload demands, which result in organizational benefits like decreased

turnover.

Authors suggested implications for the government and private sector

organizations that were stepped to reduce long or unsafe working hours. Those


implications also remain important to worker well - being and HR parishioners. They

mentioned that organizations have to manage the work overload issues for the betterment

of employees.

Thiagarajan, Chakrabarty and Taylor (2006) used a questionnaire to collect the

data from 150 single parents for pretest study in the U.S. to examine the reliability and

validity of 13 - items Reilly's Role Overload Scale. Out of 136 responses authors only

used 120 for data analysis. Later on a complete study was carried out among 535 single

parents resulting in 381 responses. Single parent families were found to be more at risk to

face role overload as single parents have to perform all the roles by themselves by

utilizing the same time and energy to accomplish multi - tasks relating to work and

family life. Single parents in the United Sates were found to be the outcome of divorce,

separation or death of a spouse or the partners may not have been ever married.

Authors mentioned in their research that as the number of children and the hours

worked increased, the time available for balancing work and family life decreased and

ultimately signaled the presence of increased role overload. Authors also mentioned that

with the increase in the age of single parents the time taken to manage their work and

family life also increased which resulted in less role overload. They found income and

education unrelated to role overload.

Authors noted that single mothers were more exposed to role overload than single

fathers as they had less social and economic resources and rewards. Scores from the six

items discussed above were found to be more reliable and valid measure of role overload.

Authors assessed the uni - dimensionality of Reilly’s (1982) role overload scale and

noted that the scores obtained from a shortened version of Reilly’s scale seemed to be a

reliable and valid measure of role overload in single parents. Authors suggested that

researchers should use 13-item scale to assess the uni-dimensionality of their measure

before using the summated scores for theory testing.

Joag, Gentry and Ekstrom (1991) investigated the impact of wife’s home and job

goals on the ways to reduce overload. They employed a 10 page questionnaire to collect

the data from wives. Authors retrieved 185 responses out of 230 resulting in 80.4 %

response rate. The questionnaire investigated from the wives the perceived role overload

and the ways to reduce that overload. Authors found that strong job goals and heavier


work roles were not related to the purchase of time saving products after controlling age

and income. They also found some differences among wives’ job and home goals and

work roles with respect to role overload and in the use of strategies to reduce that

overload. They revealed that one’s home goals were inversely related to one’s job goals

and to the amount of time spent on the job.

Roles and goals and perceived role overload were also found to be related to

wife’s age. Older wives worked less and they had weaker career goals and stronger home

goals. Wive’s income was related strongly to the work goals and weaker to the home

goals. After keeping wive’s age, income, education, and presence of children and total

household income constant the authors revealed that home goals and job goals were

positively related to the level of perceived role overload. They also found direct

relationship between the hours worked and the role overload. The wives who worked

more hours per week were more likely to get help from family members and to buy time -

saving products, and they were less interested in reducing the time spent on the job. They

were not ready to seek external help, minimize travel time, or postpone home

responsibilities. Working wives were more likely to discuss pressures with close friends

than those working less.

Furthermore the authors found that the more the wife worked the less time each

spouse spent on the family finances. It might be due the fact that both the husband and

the wife earned and there were less financial burdens felt and those who worked more

had less time for leisure.

Moreover, they found that the working wives form the low social group got more

help for house work from their family members as compared to non – working wives.

Wives who belonged to the higher social group were likely to have dinner outside home.

They had less time for leisure, and were also having less time for house work. Authors

suggested that work roles and goals should be investigated in more detail.

Conley and Woosley (2000) stated that strain is one of the causes of role overload

that is caused by the pressures to work more and more. Heavy workload affected the

quality of work and gave rise to the feeling that one may not be able to get finish ones

work within a given period of time.


Fu and Shaffer (2001) examined the determinants of work and family on family to

work interference and family to work interference. The sample consisted of 800

employees of a Honk Kong University both academic and administrative staff. The

researches found out that parental demand and hours spent on household work were

important determinants of family to work interference. Role conflict, role overload and

hour spent on paid work were the factors which determined work to family interference.

The researchers also revealed that there was no effect of martial status on work life

conflict but gender was having significant relationship with work-life conflict. Female

experienced more family to work conflict (family to work interference) and male in

contrast experienced more work to family conflict. Spouse support was found to have a

negative moderating effect on family to work conflict. While supervisor support and

coworker support were found to have a moderating effect on work - to - family conflict.

Ilies, Schwind, Wagner, Johnson, De Rue, and Ilgen (2007) also noted that role overload

led to work - to - family conflict.

2.1.3. Role overload and job satisfaction

Excess work loads are predictors of several severe individual and work outcomes, one of

which includes job dissatisfaction (Pienaar, Sieberhagen & Mostert, 2007). Home (1998)

explored the extent to which life situations, institutional supports, and perceived demands

and support systems predicted role conflict, overload and contagion by collecting data

from 443 women who were doing jobs and had families and were enrolled in adult

education, social work or nursing.

After using multiple regression authors revealed that lower income increased the

role overload. Perceived intensity of students’ demands was the strongest predictor of

conflict, overload and contagion. Family and job demands were other predictors of

conflict, overload and contagion. Authors concluded that the use of distance education

eased the role conflict and contagion. Moreover, they suggested that adult educators

should emphasize the increased financial support and distance education.

Pearson (2008) tested a relationship of role overload, job satisfaction, leisure

satisfaction, and psychological health among 155 full time employed women. The author

revealed that role overload was negatively correlated with psychological health, job


satisfaction, and leisure satisfaction. Job satisfaction and leisure satisfaction were

positively correlated with psychological health. After applying stepwise regression

analyses the author found out that role overload was the strongest predictor of

psychological health and that job satisfaction and leisure satisfaction, respectively, added

significantly to the prediction equation.

Jones et al. (2007) selected a sample of sales people who were expected to

experience some degree of role overload, because of the high - pressure nature of their

jobs. The authors noted that role overload had displayed inconsistent relationships with

many job attitudes, turnover intentions, and performance measures. The authors

highlighted that work experience could explain the inconsistent findings, because

experienced salespeople might cope better with feelings of role overload.

Koustelios, Theodorakis and Goulimaris (2004) examined role conflict, role

ambiguity, and job satisfaction among Greek employees. They investigated the extent to

which role conflict and role ambiguity predicted job satisfaction. Their research found

that role conflict and role ambiguity were significant predictors of job satisfaction. The

authors found role conflict and role ambiguity related to specific aspects of job

satisfaction that are job itself and supervision. With regard to job satisfaction, the

physical education teachers were satisfied with their job itself, supervision, working

conditions, and organization as a whole. They were found to be dissatisfied with their

salary, and promotional opportunities.

Yousef (2002) selected a sample of 361 employees in a number of organizations

in the United Arab Emirates (UAE) and investigated the mediating role of job satisfaction

between job stressors such as quantitative role overload, qualitative role overload, and

lack of career development and various facets of organizational commitment such as

affective, continuance, and normative. After employing path analysis the author revealed

that quantitative role overload directly and negatively influenced job satisfaction and

affective commitment and found out that lack of career development was a source of

stress that directly and negatively influenced job satisfaction. The author suggested that

job satisfaction mediated the influences of quantitative role overload on different facets

of organizational commitment.


2.1.4. Role overload and life satisfaction

Multiple roles create stress due to over work resulting in time shortage and require more

time to accomplish non - work (paid work) activities. This shortage of time and non -

accomplishment of activities tends to generate life dissatisfaction.

Perry-Jenkins et al. (2007) examined the effects of work hours, work schedules

and role overload on depressive symptoms and relationship conflict among working class

couples. Relationship conflict is one of the factors of life satisfaction. They considered a

sample of 132 dual - earner, working - class couples who were interviewed 05 times

while experiencing the transition to parenthood for the first time. Transition to

parenthood means the employees who got married and were going to have a child in near

future.

After using multilevel modeling analyses authors revealed that working evening

or night shifts was related to higher levels of depressive symptoms. For mothers, working

rotating shifts predicted relationship conflict. Increase in role overload was positively

related to both depression and conflict; working a non-day shift explained difference in

the level of depression and conflict in addition to role overload.

Moreover authors revealed that in mothers, depressive symptoms decreased, after

the birth of the baby but increased with the passage of time and in fathers there was no

change found with respect to depressive symptoms. Authors also found an increase in the

relationship conflict among mothers and fathers in the first year of having a baby. But for

mothers the conflict increased at first (in the beginning of the year) and then it started

decreasing at the end of the year.

Working a non - day shift schedule and relationship conflict were found to

increase the levels of depressive symptoms in parents. Moreover, role overload was

found to increase the relationship conflict. Authors found out that one’s own role

overload significantly predicted higher depressive symptoms. They found no relationship

of mediating role of role overload and effects of shift work on depressive symptoms.

The authors concluded that working evening and night shifts predicted both

mothers and fathers levels of depressive symptoms, whereas mothers’ rotating shift

increased conflict and role overload did not mediated the effects of shift work on the

outcomes. Work shift groups experienced the overload in the same manner.


Authors suggested that there was a need to explore how life changes when

couples had nonstandard and/or alternating work schedules especially when mothers

work non - day shifts, which must affect depression and conflict? They also argued that

the changes should be explored that occur for couples past the first year and as more

children are born. Moreover, researchers should explore that how couples cope with shift

work schedules and family life.

Evandrou and Glaser (2004) investigated the relationship of multiple role

responsibilities and a range of indicators of quality of life, including material resources,

health and engagement in social activities. They found poor quality of life among parents

having job responsibilities and multi - roles of childcare, which reduced job satisfaction

and increased the work to life conflict.

Other researchers found that role conflict, role overload and hours spent on paid

work are factors associated with work to family interference. The researchers also

revealed that there is no effect of martial status on work - life conflict. They found gender

having significant relationship with work - life conflict. Female experienced more family

to work conflict (life dissatisfaction) (family to work interference) and male in contrast

experienced more work to family conflict (job dissatisfaction). Supervisor support and

coworker support were found to have a moderate effect on work to family conflict (Fu &

Shaffer, 2002).

2.1.5. Work - life balance and job satisfaction

Schermerhorn et al. (2002) defined work - life balance as making sure that the demands

of the job (paid work) have a sensible fit with one’s personal life and non - work

responsibilities.

Malik, Saleem and Ahmad (2010) examined the relationship of job satisfaction,

Work - Life Balance (WLB), turnover intentions and burnout level among 175 MBBS

qualified doctors in Pakistan. By employing Pearson’s correlation and multiple regression

the authors found that the doctors who were better able to manage their work and life

responsibilities had low burnout levels and experienced more job satisfaction that

encouraged only a very small number of doctors to leave their jobs. Moreover by


employing independent sample t - test they revealed that female doctors were more

satisfied than their male counterparts.

The authors concluded that work - life balance was the major contributor towards

job satisfaction and female doctors were more satisfied with their jobs as compared to

their male colleagues. It means that work - life balance helps to produce/increase job

satisfaction. Malik et al. suggested that the hospital management should provide the male

doctors with the economic benefits, autonomy, recognition and prestige to enhance job

satisfaction among them.

Calvo - Salguero, Carrasco - González and Salinas - Martínez de Lecea (2010)

analyzed the moderating role of gender and of the salience of family and work roles in

the work - to - family conflict and general job satisfaction among 162 workers from a

Spanish public organization.

The authors, by using, regression analysis found the moderating effect of gender

on the relationship between work - to - family conflict and job satisfaction. Women

showed a lower level of job satisfaction than men. However, the salience of the family

and work roles were found to have no moderating effect on the aforementioned

relationship, neither in the case of men nor in women.

Rehman, Khan, Ziauddin and Lashari (2010) explored the relationship between

work rewards and job satisfaction with moderating effect of age differences among 84

full time employees of FESCO (Faisalabad Electric Supply Company, Pakistan). The

authors revealed that job rewards proved to be strong predictor of job satisfaction. Job

satisfaction was strongly related to extrinsic rewards for employees than intrinsic

rewards. The age differences had moderating effect on job satisfaction as it increased

with rise in age.

Asadullah and Fernández (2008) examined the determinants of various aspects of

job satisfaction in UK with an emphasis in gender differences and the presence of work -

life balance practices. The authors found that WLB practices were important

determinants of intrinsic and extrinsic aspects of job satisfaction, although they improved

the well - being of males and females alike, thereby reducing gender differences only

slightly.


The relevance of work - life balance practices applied to satisfaction with the

work itself, satisfaction with pay and satisfaction with the degree of influence over the

job (autonomy). Similar pattern was found in two separate cross-sections of the working

population in the UK, indicating that in the course of the 6 years that separated the 1998

from the 2004 surveys work - life balance practices remained significant while the gender

gap in job satisfaction dropped to a half for reasons other than firm characteristics.

The authors concluded that there were factors other than firm characteristics

driving the gender gap in job satisfaction in UK and more work was needed to understand

better a phenomenon that was not reproduced in other European countries.

Hughes and Bozionelos (2007) studied the work - life balance as a source of

dissatisfaction. The qualitative study was conducted among 20 bus drivers employed full

time in a UK based transport company. The findings indicated that work - life balance

issues were of importance to the bus drivers. The problems caused by inability to balance

work and non - work life were identified by the bus drivers as the main cause of job

dissatisfaction which included job turnover and absenteeism in their job. Moreover they

identified few other sources of dissatisfaction and withdrawal behaviors such as treatment

by the management and pay.

Cabrita and Heloísa (2006) studied the job satisfaction in European countries in a

survey conducted by “European Foundation for the Improvement of Living and Working

Conditions.” The survey investigated conceptual and methodological issues in the study

of job satisfaction. The survey results examined the levels of job satisfaction among

workers, as well as identifying the relationship between specific factors relating to work

and job satisfaction.

The researchers found that job autonomy appear as having a strong and

unambiguous link with job satisfaction. Employees were found to have higher job

satisfaction while having more autonomy. The authors also revealed that work - life

balance was positively related to job satisfaction. Workers with more flexibility in their

working time and with a better work - life balance were more satisfied with their jobs. On

the other hand, work - life conflict was found to be negatively correlated with job

satisfaction. There was no significant relationship found between long working hours and

job satisfaction.


Butt and Lance (2005) explored the relationship between teacher workload, job

satisfaction and work - life balance, within the context of the future modernization of the

whole school workforce. They revealed that teachers perceived themselves to be

negatively effected by increased workload. The authors also found that job satisfaction of

teachers was effected by accountability. Few of the remedies suggested by the teachers to

increase job satisfaction were increased levels of re - sourcing, staffing and better

working conditions. Authors also revealed from the study that highly motivated people

often gain satisfaction from their work and choose to work long hours. Authors

concluded by suggesting that the project needed to consider the long-term perspective for

policy - making regarding work - life balance and job satisfaction.

Schermerhorn et al. (2002, p. 54) stated that development of organization (via

provision of such facilities that help in maintaining or enhancing productivity) was a

planned change that was designed to improve the overall effectiveness of organizations.

That included a set of tools which were used in achieving and maintaining high levels of

productivity.

In a case discussed in their book Schermerhorn et al. (2002) stated that companies

that treat their people right get enormous dividends, high rates of productivity, low rates

of turnover. Companies that treat their people poorly experience the opposite, and end up

complaining about the death of loyalty and the scarcity of talent.

White et al. (2003) studied the effects of high performance practices and long

working hours on work life balance. They analyzed the data from national survey of

British employees in 1992 and 2000. Their research revealed that long working hours

were the main source of work life conflict. Besides long working hours, their research

found many other factors related to work life conflict. The appraisal system and

compensation packages (components of job satisfaction) related positively to WLB

among male and female employees.

According to them the intensity of work - life conflict was gender specific. The

male employees encountered more work - to - family conflict while working in groups

whereas, female encountered with more family - to - work interference when they worked

in a group as female had to ignore their personal commitments to meet the expectations

of other group members. The researchers suggested that the problem of work life conflict


could be minimized by flexible working hours and personal discretion which means

achieving good balance between work and family activities.

Ezra and Deckman (1996) conducted an Ordinary Least Square Regression on the

data of 1991 federal employee’s survey of USA to explore that how the use of family

friendly policies affected federal worker’s satisfaction with their job and work life

balance. They found that satisfaction with work/life balance practices were a major

component of employee’s job satisfaction. Using family friendly policies for example,

flexible time and on site childcare emerged to help employees especially working

mothers, who had dual demand of better work and family life.

Oswald (2002) studied the job satisfaction and work - life balance in US and

Europe. The researcher found that US was on the top of the list in the countries where

employees suffered from work - life conflict. The author mentioned that 85% of

Americans reported that they needed more time with their families (work to family

interference). The highly qualified people experienced more work - life conflict which

resulted in job dissatisfaction. The researcher also highlighted that the job satisfaction in

the US work force was decreasing. It was 56% in 1970s and 52% in 1980’s and 47% in

1990’s.The researcher also revealed that men experienced more work to family

interference than women in US. Job satisfaction was not statistically related to gender.

Steijn (2004) explored the question that to what extent job satisfaction in the

Dutch public sector was influenced by the use of HRM practices? The researcher used a

survey carried out by the Dutch Ministry of Interior in 2001, covering 14,212 public

sector workers. After using stepwise Ordinary Least Squares Regression Analysis

authors revealed that job, organizational, and HRM related variables were found to be

more important than personal demographic factors in explaining differences in job

satisfaction. They also found that individual characteristics had a little effect on job

satisfaction and HRM practices had a positive effect on job satisfaction and Dutch public

sector workers, intrinsic work aspects were a major determinant of job satisfaction.

Authors concluded that if workers feel better supported in their careers, and if

more HRM practices were used, overall job satisfaction was influenced positively.

Authors suggested that advanced operationalization of the use of HRM practices and


other elements of high-performance work systems were needed to investigate this effect

more fully in public sector in Greece.

Hancer and George (2003) examined job satisfaction of restaurant employees

working in non - supervisory positions. The researchers concluded that it might be true

that restaurant workers like their jobs, but there were some facets of satisfaction that

could be improved to increase overall job satisfaction. Restaurant managers had the

opportunity to pay more attention to those employees with lower levels of satisfaction.

Supervisory practices and company policies might have to be re-examined to identify

those practices and policies which contribute to employee dissatisfaction. Managers

might attempt to give more recognition and status to the employees as well as authority to

make decisions related to the performance of their jobs. The opportunity to perform a

variety of jobs and to use more of their abilities and creativity might also be encouraged.

They also suggested that compensation is another issue that had to be solved by the

development of incentive programs (WLB programs) and the opportunity to receive

bonuses based on performance. That might help to increase the level of satisfaction.

Foley et al. (2004) evaluated the level of job satisfaction by employing Index of

Work Satisfaction (IWS) among a convenient sample of school nurses practicing in

California. Out of 448 respondents 229 responded to the second edition of IWS resulting

in 67% response rate. The majority of the sample was found to be dissatisfied with their

jobs while examining overall job satisfaction.

IWS measured the nurses’ present level of satisfaction. The nurses rated

autonomy as the most satisfying component of job satisfaction followed by interaction,

organizational policies, professional status, pay and task requirements. Autonomy and

interaction was rated the most valued job components. Authors concluded that school

nurses were relatively dissatisfied with pay, which show that school nurses enjoy and

value professional autonomy more than monetary benefits.

Ju, Kong, Hussin and Jusoff (2008) stated that for the maintenance of employee

satisfaction and increase in employee commitment it is essential for the organizations to

increase employee benefits.


2.1.6. Work - life balance and life satisfaction

Better reconciliation of work and family life is increasingly recognized as stimulating

employment growth and having a probable impact on demographic renewal in the

developed as well as the developing countries. Lowering the conflict between the role of

mother and the role of worker may contribute to an improvement in general life

satisfaction and well-being (e.g., Argyle 1989). Balancing competing demands of work

and family life under growing individual aspirations and expectations makes

reconciliation an important component of life satisfaction and quality of life. Labor

market developments since the mid-1980s have made reconciliation between work and

family more and more challenging.

Pressures on increasing flexibility in employment status, working hours and

mobility as well as a rising uncertainty in job and professional careers contribute to an

increase in tensions between work and family life.

Adekola (2010) examined two aspects of work - family interfaces, such as, work

interference with family and family interference with work in Nigerian business

executives. The author revealed that job related factors such as career salience (the

psychological identification with work role), hours of work and work involvement were

largely associated with work interference with family for both male and female

executives. Only one family related factor (number of children) was found to have

dominating effect on family interference with work for women executives.

Omar (2010) noted that there are three major categories of work - life policies

supporting employees to balance their work and non - work lives, these are,

• Flexible work options (e.g. flexible hours, non-standard work)

• Specialized leave policies (e.g. career break schemes, parental leave)

• Dependent care benefits (e.g. child care referral, subsidized childcare).

Rego and Cunha (2009) explored the effects of perceptions of opportunities on

learning and personal development (a part of WLB policies) which predicted five

dimensions of affective well - being (AWB). The five predictors of well - being were

pleasure, comfort, placidity, enthusiasm, and vigor (life satisfaction). They also examined

that how this relationship was moderated by the perceptions of work - family

conciliation. Authors collected a sample comprising of 404 individuals and revealed that:


(1) both the perceptions of opportunities for learning and personal development and

perceptions of work - family conciliation predicted AWB, the happier individuals were

having higher perceptions on both variables; (2) both variables interacted in predicting

AWB, in such a way that perceptions of high opportunities for learning and personal

development might not lead to higher AWB if work - family conciliation was low. They

found a non linear relationship between the perceptions of opportunities for learning and

personal development and AWB for individuals with perceptions of low work-family

conciliation, by using Post hoc analysis.

Karimi (2009) examined the gender differences in the experience of work - family

interference and perceived job - life satisfaction among 387 Iranian male and female

employees working in different organizations (96% response rate).

After applying t - test and Multiple Regression Analysis using EQS 6.1., she

revealed that Iranian male and female employees experienced similar interference in their

work family domains although they spent different numbers of hours at their workplace.

The results of her study revealed that work - to - family interference had significant and

negative effect on job - life satisfaction among male employees. She also revealed that

for female employees, working hours and family - to - work interference had even more

significant and negative effects on their job - life satisfaction. Work - to - family

interference was greater than family - to - work interference for both men and women

employees.

She revealed that male and female experienced the work family interface in the

same manner without having remarkable differences but for male employees work - to -

family interference had more impact on their perceived satisfaction from their lives or

jobs, whereas for female employees working hours and family - to - work interference

had a more significant effect on their job or life satisfaction.

She concluded that female employees would benefit from a decrease in family - to

- work interference. The company - wide family - friendly programs and flexible working

hours could assist female employees to integrate their work and family responsibility,

which would in turn result in a work environment that promoted employee mental health

and, generally, positive attitudes toward life. Moreover she suggested that family -


friendly programs could help male employees learn how to manage the demands between

work and family domains.

Cunningham and Rosa (2008) examined the moderating effect of proactive

personality on the relationship between controllable work and non - work stressors (i - e;

time - based work - family interference) and job/life satisfaction. The authors noted that

moderated multiple regression analyses for 133 professionals revealed a significant

interaction between time-based family interfering with work and proactive personality

predicting life satisfaction. No other interactions between proactive personality and other

forms of work - family interference were observed. The authors highlighted that benefits

of proactive personality might only emerge when personal control over occupational

stressors could be exercised.

Moore (2007) studied the managers and workers in an Anglo-German

Multinational Corporation (MNC), focusing on how each group attempted to maintain an

acceptable work - life balance. After a two year long research conducted by in-depth

interviews, participant - observation, the researcher revealed that the company's work -

life balance initiatives focused on the managers, and the managers presented greater

loyalty to the company, the workers were better able to achieve work - life balance. None

of the groups displayed a more positive attitude to their work. Moreover the managers

focused more on achieving status and the workers on personal satisfaction (life

satisfaction). Her findings challenged statement that flexible working practices were good

for work - life balance, that managers were better able to maintain a good work - life

balance than workers and that the development of an appropriate work - life balance

policy helped in confirming company loyalty and positive attitudes to work. A Meta -

analysis by West (2000) concluded downsizing had negative effects on the well - being

and commitment of the employees working in the organizations.

Moore (2007) noted that work - life balance is fast becoming issues of the current

employment prospect. Currently there is a shift from “work - family balance” to “work -

life balance” to reflect the fact that non - work demands in people’s lives not necessarily

limited to family only. A good work - life balance is when employees having the ability

to fulfill both work and other commitments such as family, hobbies, art, travelling,

studies etc.


Mauno, Kinnunen and Ruokolainen (2006) noted that a supportive work - home

(WH) culture was related to positive work outcomes, such as higher job satisfaction and

commitment and lower levels of physical complaints, thus underlining the importance of

WH culture for worker well - being.

Saraceno, Olagnero, and Torrioni (2005) used the 2003 EQLS data to verify

whether the variables they found essential for defining the work - family balance such as

gender and household status as well as the country (or country group) of residence are

related to individuals' satisfaction with family life. The authors found no clear

relationship and concluded that although individuals with young children perceive the

greatest difficulties in combing paid employment and taking care of children, these

difficulties did not result in any clear differences in satisfaction with one's own family

life.

Francis (2004) determined the prevalence of work - family conflict and supportive

organizational values experienced by male civil engineers and the interrelationship

between supportive culture and work and non - work experiences. The author collected

data via self administered questionnaire among 500 civil engineers and retrieved back

only 93 responses resulting in 19.3% response rate.

The author revealed that male civil engineers experienced moderate levels of

work - family conflict but did not perceived their organizations supportive in respect of

employee needs to balance work and personal life. Moreover the author also noted that

the civil engineers who reported supportive work environment also reported higher levels

of organizational commitment, greater job and life satisfaction, lower levels of work -

family conflict and lower intentions to quit. The engineers who reported more supportive

culture also reported higher level of life satisfaction and higher levels of mental health

and well - being. The author suggested that to achieve a supportive culture, change is

must but starting from top level and training of middle managers and supervisors might

also be considered.

Stewart (2003) explained the role of life coaching in helping individuals to restore

the balance between their lives and the work of organizations. He has mentioned the

ways in which life coaching could help people to balance their work, home, leisure and

personal development.


The work - life balance campaign launched in March 2000 was aimed to convince

employers of the economic benefits of work-life balance and of the need for the

introduction of flexible working arrangements in UK government employees. The

Management Today Survey was conducted to collect the data by The Work Foundation

formerly the Industrial Society.

The author mentioned that women were quicker to take up flexible working

arrangements than men and 93% of men got a feeling of accomplishment from their job.

The author revealed a change in generation attitude in British men. Young men were

found to have a different approach to home and family as compared to their older

generation. The author concluded that success of life coaching was one of the factors

causing balance or imbalance.

While looking at the organizational costs associated with absenteeism occurring

specifically as a result of role overload and work - life imbalance were estimated at

approximately CA$11 billion per year (Duxbury & Higgins 2003) and the turnover of

skilled workers who quit their work due to not enough work - life balance had been

estimated to cost British organizations approximately GB£126 million per year (Equal

Opportunities Commission 2005).

Stewart, Donald and Grant-Vallone (2001) explored the effects of work - family

conflict on the well - being of a diverse sample of 342 non - professional employees from

the greater Los Angeles area. They collected data at two points in time, and employed a

rigorous research design. The authors controlled the effects of self - report bias by

considering social desirability bias, and by collecting data from self - reports and co-

workers reports. They revealed that work - family conflict predicted employee well -

being over and above social desirability bias.

Their analyses were consistent for both self - reports and co - workers reports.

Moreover they found that work - family conflict was a longitudinal predictor of

employees’ positive well - being. They also found that both cross-sectional and

longitudinal analyses were consistent across self - reports and co - worker reports.

Adams (1996) developed and tested a model based on the relationship between

work and family that included variables from both the work - family conflict and social

support literatures. The model related bi - directional work-family conflict, family


instrumental and emotional social support, and job and family involvement to job and life

satisfaction. The author collected the data from 163 workers who were living with at least

01 family member. The author revealed that relationships between work and family could

have an important effect on job and life satisfaction and that the level of involvement the

worker assigned to work and family roles was associated with that relationship. The

author suggested that the relationship between work and family could be simultaneously

characterized by conflict and support. Higher levels of work interfering with family

predicted lower levels of family emotional and instrumental support. Higher levels of

family emotional and instrumental support were found to be associated with lower levels

of family interfering with work.

2.1.7. Work - life balance and employee retention

Society has become knowledge based where human capital is considered a key resource

and indispensible to the survival of businesses. Increasingly, organizations are competing

for the best and talented employees (Porter, 2001). Organizations of the current era

recognize that an important element in business management practices is the motivation

and retention of employees who survive the organizational restructuring, downsizing,

consolidation, reorganizing or re - engineering initiatives (Clarke, 2001). The loss of

needed talent is costly because of the resultant bidding up of market salaries for

experienced hires to replace them; the costs of recruiting and assimilating new talent; the

lost investment in the talent development; and the hidden cots of lost productivity; lost

sales opportunities and strained customer relationships (Eskildsen & Nussler, 2000).

Malik, Gomez, Ahmad and Saif (2010) examines a sample of 204 doctors and

reveals that the doctors who are better able to manage work and life activities are more

satisfied with their jobs and have intentions to retain their jobs.

The authors suggest that the retention of employees with the same organization

saves the organization from incurring costs of hiring and training their employees which

proves to be a source of overheads reduction for the organizations.

Levin-Epstein (2006) notes that flexibility with work schedules and access to paid

leaves help workers meet both their job and caring responsibilities. Being able to juggle


effectively between work and non - work activities improves job satisfaction that

enhances job retention.

Previous research studies have revealed that work life policies include flexible

working hours, training, breaks from work and arrangements of better work support

(Maxwell, 2005). Organizations adopting and implementing such practices better manage

their employees and keep them for longer time periods.

Cole and Flint (2005) explored the perceptions of fairness including the fairness

of the procedures used to determine pay, distributive justice and procedural justice,

relating to employee benefits. The authors conducting a survey of benefits plan

participants among managers, professionals, administrative/clerical staff, and technical,

sales, maintenance and plant workers in seven different Canadian organizations such as a

university, a national retail chain, a heavy equipment manufacturer, a computer hardware

manufacturer, a food products manufacturer, a consumer products manufacturer and a

fashion retailer. Questionnaires were distributed among 1,600 employees and received

back from 497 employees resulting in 31% response rate based on random sampling

technique.

The questionnaire covered five sections including perceptions of fairness

regarding employee life and health insurance benefits and their pension plan. Specific

questions were asked about the knowledge of actual coverage under these insurance and

pension benefits, understanding of the above mentioned plans. Specific questions about

employee participation in plan design and amendment and about appeals of benefit

decisions and the last section covered the demographic information on age, gender,

family status, and annual earnings.

After using correlation and regression analysis the authors found that fairness in

employees benefits were a source of enhancement of the concept among employees that

company benefits were distributed fairly that increased benefit satisfaction among

employees and resulted in the enriched hiring process and employee retention. Moreover

the authors identified that perceptions of fairness in the workplace had an affect on

organizational commitment, management satisfaction, pay satisfaction, leadership

evaluation, job performance, job satisfaction and intent to quit.


Employee understanding of health insurance was found to be greater than

understanding of life insurance, which was in turn greater than understanding of

retirement plans and two thirds (63%) of participants reported that they did not

understand their pension plan. Regarding health care benefits authors found out that,

higher paid participants had significantly higher perceptions of distributive justice than

lower paid participants and participants with dependents perceived health care benefits as

fairer than those without dependents.

The authors concluded that the provision of detailed employee benefit,

communication material to employees, and the opportunity for employees to participate

in employee benefit plan design, were related to increased perceptions of procedural

justice regarding benefit plans. Moreover the authors suggested that further research

would help to identify which benefits had perceptions of justice.

Lockwood (2003) notes that work - life balance programs can be a useful tool for

employee retention for the organization but many organizations overlook these and not

implementing work - life balance programs properly results in the loss of talented human

capital.

Work - life balance programs are implemented by organizations to ease

individuals to manage the interface between their paid work and other life activities

(Lobel & Kossek, 1995). Work - life balance programs include services like on - site day

care for children or emergency daycare, flexible working hours and parental leave.

Researchers noted such programs enhancing recruitment and reduce absenteeism and

turnover (Greenhaus & Parasuraman, 1999). Providing employees with work - life

balance opportunities is one of the ways for the organizations to recruit and retain

employees by providing them with flexibility and resources in order to help them

combine work and family life more conveniently and organizations employing larger

percentages of women are the ones which achieve more productivity gains from such

programs (Konard & Mangel, 2000).

Jamison (2003) examined the ways to reduce turnover and increase retention

among volunteers in non - profit organizations in US in the light of Herzberg’s two -

factor theory. Twenty items survey was distributed among the volunteers who worked in

the agencies that were partners in the Community Human Service Partnership in Leon


County, Florida. A total of 232 questionnaires were distributed and 133 questionnaires

were returned, producing a 57% return rate. But the final usable questionnaires were 119

resulting in the final response rate of 51%.

The factors that motivated employees to remain in the organization and

responsible for their overall satisfaction were found to be training, orientation,

communication, interpersonal relationship, direct service, equitable treatment, skill

development, challenging task, personal growth, decision making, feedback and

evaluation, recognition and reward.

The three factors effecting volunteer’s retention and turnover were pre - service

training, in - service training and challenging assignments. The management of any

organization could manipulate all these factors. If an organization offered opportunities

of training as a part of work - life balance and challenging assignments as a source of

motivation of employees that resulted in employee retention and otherwise these factors

were responsible for employee turnover. Author found the findings of his study

consistent with Herzberg’s (1972) two - factor theory and have suggested that

organizational factors and the task itself were linked to satisfaction, satisfaction came

form the task itself and if the work was not challenging or failed to provide the

opportunities for growth then the satisfaction would no more be there.

The organizational factors are responsible for the volunteers’ turnover. The author

suggests that the volunteer administrators can better develop a structure in which

adequate training programs, that are pre-service and in-service, achieve the dual purposes

of improving volunteers’ abilities to do their tasks and conveying an understanding and

commitment to the agencies’ missions and at the same time volunteer assignments that

combine routine work with challenging assignments that result in retention with the same

organization. Moreover author has suggested that the organizations that adopt pre -

service and in - service programs result in more employee productivity by utilizing the

skills and abilities and ultimately results in satisfaction and retention with the same

organization.

Wagar (2003) examined the relationship of employee’s intention to leave the job

and the human resource management activities in an organization. Author has found out

that the employees working in organizations, which have refined human resource


management activities, are less intended to leave the organization even for the coming

two years.

Author also mentioned that the older workers, who worked with the organization

for a longer period of time, were also less likely to leave the organization. The HR

practices which compelled the employees to remain with the organization included

employee recognition in terms of merit - based promotion and individual merit pay. Other

HR practices included sharing information with employees, use of problem solving

groups and training in employee involvement. The employees who remained with the

organization were found to be the best employees of an organization.

Employee decision to remain with the organization is effected by the

organizational policies including work and life balance policies and practices because the

conflict between work and life generates dissatisfaction that affects employee

performance and family life (life satisfaction). Many organizations implement work life

balance policies to minimize these tensions but still considerable improvements and

extensive initiatives are needed to ensure a better balance (Deery, 2008).

Burke (2000) examined the relationship between organizational supporting work -

life balance and the experiences of 203 male managers. The author revealed that

managers reporting organizational values supportive of work - life balance also reported

working fewer hours, less job stress, greater work involvement, lower intentions to quit,

greater job and life satisfaction. The research also revealed that organizational values

which support work - life balance have significant work and personal consequences for

men. When such organizational values were present, managerial and professional men

experienced higher family satisfaction and job satisfaction, generally greater life

satisfaction and additional emotional and physical well - being.

Deery and Shaw (1999) explored the existence of a turnover culture in the hotel

industry. The authors investigated the relationship of organizational culture and employee

turnover behavior within the hotel industry. Data collected from non - supervisory staff at

the four Melbourne - based properties of a hotel chain were analyzed using cluster

analysis. Authors considered two concepts for the study that were absence culture in an

organization and Organizational Cultural Profile (OCP) using a questionnaire among non

- supervisory hotel employees. The response rate for the questionnaire survey was 43 %


with 221 questionnaires. The seven clusters identified by the authors were employee

work attitude, job rewards, socialization, work culture, job mobility, work goals and

turnover culture.

The factors identified by the authors responsible for the employee turnover were

influence of peer, stress including role ambiguity and conflict, work overload, and

resource inadequacy, lack of organizational promotion opportunity and the external

opportunities of gaining a good job.

The turnover culture in the hotel industry was due to the lack of management and

organizational support that result in flaring stress among employees and therefore the

employee desire to leave the organization. The authors emphasized the presence of

organizational socialization programs and the reward systems to be improved by the

organizations to retain the employees for a longer period of time and to enhance work

culture instead of turnover culture.

2.1.8. Work - life balance and organizational commitment

Organizations concerned about their employees invest more on employees. Besides

compensation non - monetary rewards such as provision of work - life balance

opportunities and recognition are also important to retain the employees. Recognition

from managers, team members, peers and customers enhance commitment among

employees (Walker, 2001).

Noor (2009) noted that organizational citizenship behavior becomes one of the

important factors enhancing the organizational effectiveness. The author explored the

importance of OCB of universities teachers of Pakistan as the outcome of organizational

commitment. The author examined the impact of training & development opportunities,

work - life policies and empowerment practices on organizational commitment among

160 universities teachers of Pakistan through questionnaires. The author revealed that

training & development opportunities, work - life policies and empowerment practices

had significant positive relationship with organizational commitment in - turn

organizational commitment impacts positively in enhancing the organizational citizenship

behavior of the teachers.


Work and family benefits include flexible schedules, parental leave, childcare

information and childcare assistance on organizational commitment. The researchers

found that employees having access to work - life policies showed appreciably greater

organizational commitment and expressed lower intention to leave their jobs so work -

life policies are positively and significantly related to organizational commitment (Noor,

2009; Dockel, Basson, & Coetzee, 2006).

Kinnie, Hutchinson, Purcell, Rayton and Swart (2005) studied the links between

employees' satisfaction with HR practices and their commitment to the organization.

They studied three groups of employee (i.e.) professionals, line managers and workers.

The managers were found to be satisfied with career opportunities, rewards and

recognition, involvement, communication and work - life balance. Important HR

practices explaining the commitment of professionals were performance appraisal,

rewards and recognition, involvement, communication, openness and work - life balance.

For workers rewards and recognition, communication, openness and work - life balance

were significant. The research revealed that the company efforts to help employees

achieved a balance between work and home life was linked to the commitment of

employees in all three groups.

Sturges and Guest (2004) explored the relationships between work - life balance,

work - non - work conflict, hours worked and organizational commitment among a

sample of graduates who worked for five large UK organizations, in the early years of

their career. The research was conducted in three - time phase. The data first collected a

month before the graduates started their work. The second set of data was collected by

the same groups of graduates after six months of their job, and third time after one and a

half year of their job.

Their research revealed that graduates seek work - life balance; their concern for

career success draws them into a situation where they work increasingly long hours and

experience an increasingly unsatisfactory relationship between home and work. The

research found long working hours, the state of the psychological contract and

organizational commitment as the main causes of work - non work conflict.

The research also highlighted the role of organizations’ policy and practice in

helping to manage the relationship between work and non - work and the development of


organizational commitment through support for younger employees’ lives out-of-work

and effective management of aspects of the psychological contract.

Gumbus and Johnson (2003) attributed the improvement to many work - life

initiatives aimed at a corporate culture based on performance and employee commitment.

Many organizations have successfully adopted an employee - friendly environment by

integrating specialized work arrangements including flexible work hours, telecommuting

and family leave assistance to support employees in creating a better work - life balance.

2.1.9. Job satisfaction and employee productivity

Employee productivity is an important indicator of organizational efficiency. Employee

productivity is the time an individual is physically present at a job and is “mentally

present” or efficiently functioning while doing a job. Companies must address both of

these issues in order to maintain high worker productivity, and this may occur through a

variety of strategies that focus on employee satisfaction, health and morale (Goetzel &

Ozminkowski, 2002). The importance of employee satisfaction, however, corresponds to

the area of productivity analysis (Reynolds & Biel, 2007).

Malik, Saif, Gomez, Khan and Hussain (2010) while exploring a sample of

working women suggest that the satisfaction of employees and the support at work places

help in enhancing productivity, which should be the ultimate objective of any

organization.

Malik, Ahmad, Saif and Safwan (2010) conducted a research study in a sample of

450 layoff survivors to examine the relationship of organizational commitment, job

satisfaction and productivity and reveals that job satisfaction is the stronger predictor of

layoff survivors’ productivity as compared to organizational commitment. Although both

variables, job satisfaction and organizational commitment, are positively related to layoff

survivor’s productivity. Moreover they also note that pay satisfaction and job authority

are the strong predictors of overall job satisfaction.

The authors suggest that to keep employees satisfied and committed family

supportive practices might be used that help in enhancing productivity and reducing

turnover because job satisfaction has its implications for job related behaviors such as

productivity, absenteeism and turnover.


Chen, Chang and Yeh (2006) examined the effects of career development

programs on Research and Development (R & D) personnel by investigating the

relationship between the quality of working life, job satisfaction and productivity.

Authors characterized their study by its integration of career stages and career

development programs, formulating different career development programs to meet the

different career stages of R&D personnel. Authors used a sample of R&D personnel in

the high-tech industry in the Hsinchu Science - based Industrial Park (HSIP). They have

collected the data by mail from 1300 employees but 367 questionnaires were used to

analyze the data resulting in 28.2 % response rate.

After using MANOVA and regression analysis authors revealed that a higher

level of satisfaction with career development programs produce correspondingly higher

levels of quality of working life, job satisfaction, professional development and

productivity. Moreover they found that development programs which were more career -

challenge oriented had a greater impact on the quality of working life, job satisfaction,

professional development and productivity.

Sigala (2004) noted that people have made attempts to identify satisfactory

productivity - monitoring procedures, but those approaches have been heavily criticized

and no generally accepted means of productivity measurement exist.

Shikdar and Das (2003) measured worker satisfaction and productivity in a

fishing industry under different conditions including production standards, performance

feedback and monetary incentive. Authors found that the participative standard and

performance feedback condition affected the worker satisfaction - productivity

relationship. Authors found a positive correlation between worker satisfaction and

productivity and production standards with feedback generally improved worker

satisfaction and productivity. Monetary incentive further improved worker performance

but added no incremental satisfaction gain. The addition of production standards,

performance feedback and monetary incentive affected worker satisfaction and

productivity. They also revealed that the worker satisfaction improved when employees

were provided with the participative standards with feed back, which motivated them to

work hard.


Roelofsen (2002) quantified the relationship of level of comfort that effected

employee productivity working in offices. The author conducted a pilot study among 170

people in six office buildings and revealed that there was a clear relationship between job

stress, job dissatisfaction and the indoor environment. Moreover he has mentioned that a

productivity increase of 10 per cent was observed following improvements to the indoor

environment. Moreover after using regression analysis the author revealed that the indoor

environment had the greatest effect on productivity with respect to job stress and job

dissatisfaction.

Schermerhorn et al. (2002) suggest that one way of achieving the high

performance is well - being (via provision of work - life balance facilities) of the whole

work force, including all levels of management. The achievement of high performance is

possible by high levels of job satisfaction among employees. This reveals that when the

people are treated well at work, there is a likelihood that they would response positively

and as desired at work.

2.1.10. Life satisfaction and employee productivity

Researchers have extensively studied the concept of “well - being” of human beings. The

researchers have categorized well - being into two parts that is, objective well - being and

the subjective well - being. The objective well - being is often known as ‘psychological

well - being’. It is based on the external perspectives, exploring human potential and

fulfillment and is more theoretical in nature (Robbins & Kliewer, 2000). Whereas, the

subjective well - being is based on the individual’s internal perception of happiness and

life satisfaction (Keyes, Shmotkin & Ryff, 2002), that is satisfaction of employees mostly

with non work domains. Life satisfaction of employees includes judgment of the

individuals’ past, current and future overall satisfaction and/or satisfaction from the

specific aspects of their life. The facets of life include work, family, health, leisure, and

financial conditions. Moreover the aspects of individual life satisfaction also includes the

individuals’ affective states (i – e) feeling pleasant or unpleasant (Robbins & Kliewer,

2000). Subjective well - being is considered as ‘life satisfaction’ for the current study.

Telic theories (Diener, 1984) stated that individual’s subjective well - being (life

satisfaction) increased when their goals and needs were realized. It is a general


conception that when people make progress towards their goals, they generally tend to

react positively. On the contrary people generally tend to react negatively when they fail

to achieve their goals. One of the researcher suggested that people experiencing high

subjective well - being perceive their goals as being more important and are generally

more likely to achieve success.

Life satisfaction remained the area of interest for the researchers of health related

issues. They often examined the relationship of life satisfaction and health related areas

(Eng, Coles, Heimberg & Safren, 2005; Tamini & Far, 2009; Hyun & Jenny, 2006),

which in - turn are related to the productivity of individuals (Stein & Kean, 2000;

Wittchen, Fuetsch, Sonntag, Muller & Liebowitz, 1999). The researchers revealed that

health problems such as social anxiety disorder leads to reduced productivity in the

workplace. Other researchers found that life satisfaction is caused by rich mental health

and poor mental health made life dissatisfaction (Tamini & Far, 2009).

Some writers also mentioned that the people being provided with treatment and

having good health were experiencing better life satisfaction (Eng, Coles, Heimberg &

Safren, 2001) and ultimately resulted in improved productivity.

Tamini and Far (2009) investigated mental health and life satisfaction among

randomly selected sample of students in Iranian and Indian Universities. They used t -

test to analyze data. The authors revealed that there were meaningful differences with

respect to mental health as well as life satisfaction. Other researchers examined the

relationship between life satisfaction, loneliness, general health and depression and found

life satisfaction having negative and significant correlation with social attitudes,

loneliness and depression (Viren, Tomas, Dhachayani, Thambu, Kumaraswami, Debbi, &

Adrian, 2007). Their study mentioned that the people having better mental health are

generally more satisfied with their lives.

2.1.11. Employee retention and employee productivity

Employee retention and productivity of workforce are the essential ingredients of the

organizational success and better performance. Organizations may differ in prioritizing

the human resources. The organizations can not forget the value of a qualified, motivated,

stable, and responsive team of employees (Huselid, 1995) for achieving high productivity


and competitive advantage. The service firms can only retain the intellectual capital by

hiring and keeping good employees (McShane & Glinow, 2005) who can serve the

demands of the customers. Employee retention and productivity are crucial issues

discussed in human resource management and development.

Employees in an organization have played the role of an asset and their departure

could have a considerable effect on the execution of the organization’s business plans and

may ultimately be a foundation for decline in productivity. As such, employee retention

was important to the long - term growth and success of the company (Fatt, Sek Khin &

Heng, 2010).

Evidence is available in the earlier researches that employee turnover has the

financial and psychological consequences for the people leaving the organization and for

the people remaining (survivors) in the organization. There is often more work pressures

and unsettled work practices for the people remained in the organization (Proudfoot,

Corr, Guest & Dunn, 2009).

The benefits of employee retention include saving the direct and indirect costs.

The remaining employees (survivors) in an organization have indirect cost implications

including reduced morale, pressure on the staff, cost of learning and the social capital loss

(Dess & Shaw, 2001) moreover turnover of employees has negative effect on the

remaining employees that include disruption of group socialization processes and

increased internal conflict (North, Rasmussen, Hughes & Finlayson 2005). According to

Shaw, Gupta and Delery (2005) a negative relationship of workers performance and

turnover is evident.

2.1.12. Organizational commitment and employee productivity

Fatt, Sek Khin and Heng (2010) note that committed employees tend to perform beyond

the call of duty to meet customers’ needs and are highly motivated to work at their best

by utilizing their abilities.

Various other researches revealed that the employees of service sector

organizations (educational institutes) who were highly committed continued their

involvement with their current institutions and they also put high level of efforts and

showed high performance for their institutions (Chughtai & Zafar, 2006).


Raymond and Flannery (2002) reviewed a possible approach to enhance

productivity by considering the employee’s psychological contract with the organization.

That is, the personal expectations of employees about their employment. The authors

found that an awareness of employee psychological contracts can assist administrators

and supervisors in enhancing organization productivity and improving the individual

employee’s quality of life at work.

Bhatti and Qureshi (2007) stated that the employee participation might affect

employee’s job satisfaction, employee productivity, employee commitment and these all

could create comparative advantage for the organization. For this reason the authors

tested the relationship among employee participation, job satisfaction, productivity and

commitment of employees. The authors revealed that employee participation was not

only an important determinant of job satisfaction but it also had a positive effect on

employee commitment and employee productivity. Moreover the authors found a positive

association between organizational commitment, job satisfaction and employee

productivity. They suggested that increasing employee participation was a long - term

process, which demanded both attention from management side and initiative from the

employee side, ultimately helping in enhancing productivity.

Ugboro (2006) noted that if survivors’ affective commitment was enhanced it

could be expected that that was positively affected morale, sense of job security and

productivity. Fatt, Sek Khin and Heng (2010) analyzed the impact of organizational

justice including distributive justice and procedural justice on job satisfaction of

employees, turnover intentions and organizational commitment. The authors revealed a

significant and positive relationship showing that the basis of an employee’s job

satisfaction and organizational commitment was within the application of both

distributive and procedural justice, and that supported a significant negative relationship

to turnover intention.

The authors concluded that managers and business organization in Malaysia

should devise strategies that consider work factors including distributive and procedural

justice to improve the management of HR development. The use of these strategies would

help in inducing positive behaviors among employees, and hence achieve effectiveness

and high productivity in the organization. The authors suggested that it was vital for the


organization to provide training and education to their managers as a source of

organizational justice. These strategies would effect the motivation and commitment of

their employees.

Satisfied employees were important as they believed that the organization would

offer them successful future in the long run and cared about the quality of their work;

consequently they proved to be more committed to the organization, had higher retention

rates and were inclined to have higher productivity (Ishigaki, 2004).

Employee organizational commitment is beneficial for the organization as a

means of reducing absenteeism rate and turn over ratio and enhancing organization

productivity (Jernigan, Beggs & Kohut, 2002). Importance of organizational commitment

can not be ignored because it is linked to absenteeism, work effort and turnover (Joiner &

Bakalis, 2006). According to Boon and Arumugam (2006) culture of the organization and

management practices should be examined in order to maintain high level of

organizational commitment, because high commitment is examined as the essential

component of organizational and employee relations (McCabe & Garavan, 2008). It is the

responsibility of an organization to explore the ways to increase the commitment (Liu,

2007).

2.2. Summary of the literature review

Research on the effects of downsizing has focused on global, organizational and the

individual levels. However, this research, conducted at the individual level, focuses

specifically on the after effects of downsizing on the survivors of the organization.

Downsizing refers to activities undertaken by management to improve the efficiency,

productivity, and competitiveness of the organization by reducing the workforce size.

The researchers across the globe have explained the types of response one can expect

from survivors of organizational downsizing. The possible attitudes and behaviors due to

downsizing are of particular interest to managers, because managers have to inevitably

face a workforce at least partially staffed with survivors of downsizing activities. The

purpose of this research is to give a better understanding of the after effects of

downsizing on survivors. This is accomplished by systematically analyzing the responses

of layoff survivors and examining the relationship of several variables.


The literature review for the present study covers a variety of important areas

central to the current study. It covers the literature available on the relationship of the

variables included in the model. Mostly the literature review is arranged in the

descending order with respect to the year of the study.

Although the researcher found very limited research studies concerning layoff

survivors but the attempt has been made to find the relevant literature supporting the

model. In particular, this chapter mentions the relationships of the variables, which the

researchers have tested in different parts of the world.


Chapter 3

Organizational Background and Theoretical Framework

Organizational background

Operational definitions

Theoretical background of the proposed model

Hypothesis


Chapter 3

Organizational Background and Theoretical framework

In this chapter the researcher highlights the organizational background of the

organizations comprising the population, operational definitions of the concepts used,

theoretical framework and the hypothesis developed for the study.

3.1. Historical Background of the Organizations.

The organizations which have recently laid - off their employees by offering them with

the schemes like Voluntary Separation Scheme and Golden Hand Shake include Pakistan

Telecommunication Company Limited (PTCL), with approximately 29,000 layoffs

(Kiani, 2007) and Habib Bank Limited (HBL), with approximately 11,350 layoffs

(Ghausi, 2004; Bashar, 2001). Pakistan Telecommunication Company Limited (PTCL) is

the largest telecommunication company in Pakistan. The company provides telephony

services to the nation and holds the status of backbone for country's telecommunication

infrastructure (despite arrival of other telecom companies such as, Telenor and China

Mobile).

The company consists of around 2000 telephone exchanges across country

providing largest fixed line network. Global System for Mobile communication (GSM),

Code Division Multiple Access (CDMA) and Internet are other resources of PTCL,

making it a big organization. The Government of Pakistan sold 26% shares and control of

the company to Etisalat in 2006. The Government of Pakistan retained 62% of the shares

while the remaining 12% are held by the general public.

With new administration, the company has undergone different changes like

offering Voluntary Sepration Scheme (VSS), aimed at reducing the workforce,

restructuring, introducing Billing and Customer Care Software (B & CC) etc. Other

change made by the company was the change of brand identity (logo) that presents

PTCL's new face after privatization. PTCL is now having greater focus on customer

satisfaction and aimed at bringing advancements in telecom industry of Pakistan.

Habib Bank Limited (HBL) head-quartered in Habib Bank Plaza, Karachi,

Pakistan, is the largest bank in Pakistan. The bank has a network of more than 1450


branches in Pakistan and 55 branches across the world. It has a domestic market share of

more than 40%. It dominates the commercial banking sector with a major market share in

inward foreign remittances (55%) and loans to small industries, traders and farmers.

After the independence of Pakistan in 1947, Habib Bank established its

headquarters at Pakistan’s first capital, Karachi. HBL gave first commercial bank

services to the newly formed Islamic Republic of Pakistan. HBL was nationalized in

1974. On June 13, 2002 Pakistan's Privatization Commission granted the Aga Khan Fund

for Economic Development (AKFED) rights to 51% of the shareholding in HBL, against

an investment of PKR 22.409 billion (USD 389 million).

Habib Bank offers a number of banking services to its customers including

Commercial, Corporate, Investment, and Retail Banking, Treasury, and Islamic Banking.

The privatization of the bank resulted in the layoff of almost 11,350 employees in the

year 2001, under Golden hand Shake scheme.

3.2. Operational Definitions

The current study uses the following operational definitions of different concepts from

the existing literature:

Downsizing can be defined in the context of Pakistani organizations as an

involuntary and intentional cut down in the number of employees for the purpose of

improving organizational performance. It is different than voluntary turnover that

employees choose to leave the organization themselves. Layoff survivors are the people

affected by downsizing and they experience heavy workloads due to absorbing the

responsibilities of their co - workers who were laid off (Fong & Kleiner, 2004, and Virick

et al., 2007). Layoff survivors remain with the organization after the completion of the

downsizing process (Virick et al., 2007; Brockner et al., 2004; Kerman & Hanges, 2002).

Layoff survivors are responsible for carrying out the organizational operations and future

profitability of the organizations. Survivors are prone to working difficulties such as,

shortage of resources and may become unproductive when they face increased workloads

and job responsibilities (Gandolfi, 2008).

3.2.1. Post - layoff perceived work load increase


For the current study post layoff perceived workload increase for layoff survivors is

defined as an impression (thinking) of addition in the amount of work assigned to or

expected from a person in a given time period.

Perceived work overload reflects a situation in which an individual thinks has too

much to complete in an insufficient span of time (Frone, Russell & Cooper, 1992). The

current study considers the perceived workload as mentioned by Elloy and Smith (2003)

and defines the post layoff perceived workload increase as the extent to which the layoff

survivors have feeling that they have to accomplish too many tasks with in the available

resources.

3.2.2. Role overload

In this study the role overload of layoff survivors is defined as too much work expected

from layoff survivor as compared to others. Role overload has been measured by asking

questions about people’s feelings on whether they can finish work given to them during a

specific period of time that is a work day.

Quantitative work load arises when there are too much tasks to perform in a

limited time span. Yet, qualitative work overload occurs when the work requirements go

beyond worker’s intellectual competence and skills (Dasgupta & Kumar, 2009). For the

current study only quantitative role overload is considered.

Role Overload (RO) measures the extent to which job demands are more than the

available resources (personal and workplace) and the extent to which the individual is

capable of accomplishing workloads (Osipow, 1998).

According to Kahn et al. role overload become visible when a person must

perform a wide variety of tasks within a given time limits (Kahn, Wolfe, Quinn, Snoek,

& Rosenthal, 1964). Role refers to the actual tasks that an individual (layoffs survivor)

has to perform.


3.2.3. Work - life balance

Work - life balance for layoff survivors is defined as creating a productive work culture

where the potential for tensions between work and other parts of people’s lives is

minimized (Malik, Saleem & Ahmad, 2010). These are the working practices that are

adopted by an organization to ensure and aim to support the needs of layoff survivors in

achieving a balance between their work and home lives.

Work relates to the notion of work done at workplace for which layoff survivor

has been paid. Life refers to the activities in a personal life that is out of work. Such as

time spent with friends, family members (relatives, children, parents), study, sports,

hobbies, etc. it also includes the work for which employee is not paid.

Balance does not mean an equilibrium or equal distribution of time between work

and personal life activities. In fact it means the satisfactory level of involvement or fit

between the work and non - work tasks. It differs from individual to individual. Culture

refers to the values, antidotes and believes of layoff survivors that the organization will

take care of them. It is basically achieving the overall harmony in life (Clarke, Koch &

Hill, 2004).

3.2.4. Job satisfaction

Job satisfaction of layoff survivors is defined as an enjoyable or positive emotional state

resulting from their job. Satisfaction means a feeling of pleasure because one has

something or has achieved something. Job satisfaction is an added response to a specific

job or various aspects of it (Ahmed et al., 2010). It is the degree to which people like

their jobs (Malik, Saleem & Ahmad, 2010).

Enjoyable means an individual likes his/ her work and do not gets bored soon

from his/ her work and feels comfortable at work. Minnesota Satisfaction Questionnaire

(MSQ) is employed for data collection. The definitions of the constructs of Minnesota

Satisfaction Questionnaire (MSQ) are as follows:-

a. Activity: Being able to keep busy all the time.

b. Independence: The chance to work alone on the job.

c. Variety: The chance to do different things from time to time.

d. Social status: The chance to be “somebody” in the community.


e. Supervision–human relations: The way my boss handles his men.

f. Supervision–technical: The competence of my supervisor in making

decisions.

g. Moral values: Being able to do things that don’t go against my

conscience.

h. Security: The way my job provides for steady employment.

i. Social service: The chance to do things for other people.

j. Authority: The chance to tell other people what to do.

k. Ability utilization: The chance to do something that makes use of my

abilities.

l. Company policies and practices: The way company policies are put into

practice.

m. Compensation: My pay and the amount of work I do.

n. Advancement: The chances for advancement on this job.

o. Responsibility: The freedom to use my own judgment.

p. Creativity: The chance to try my own methods of doing the job.

q. Working conditions: The working conditions.

r. Coworkers: The way my coworkers get along with each other.

s. Recognition: The praise I get for doing a good job.

t. Achievement: The feeling of accomplishment I get from the job.

3.2.5. Life satisfaction

Life satisfaction refers to the satisfaction with the activities outside of paid work. The

activities included outside of work include the interaction with friends and household,

family and community, study affairs, hobbies etc.

Life satisfaction of layoff survivors is defined as the layoff survivors’ experiences

in the important life areas such as life, school, job, family, etc. which create positive

feelings and are more in number than the experiences that create negative feelings

(Diener, 2000).


3.2.6. Organizational commitment

The operational definition of the organizational commitment of layoff survivors refers to

sense of belongingness to the organization. It is the degree to which the layoff survivors

feel devoted to their organization (Spector, 2000).

3.2.7. Employee retention

It is an employee deliberate willingness to stay with the organization (Udechukwu &

Mujtaba, 2007). Generally employees who are happy with their work tend to remain with

the same organization. In other words it is the ability of an organization to keep the

employees which are helpful to the organization.

3.2.8. Employee productivity

For the current study the researcher considered subjective productivity. The operational

definition of layoff survivor’s productivity states that productivity is what an individual

can accomplish with material, capital and technology. Productivity is mainly an issue of

personal manner. It is an attitude that an individual must continuously improve (Japan

Productivity Centre, 1958 (from Bjo¨rkman, 1991)). For the current study layoff

survivors productivity comprises of autonomy at job, meeting time demands and

efficiency of the survivors.

Job autonomy refers to job independence. How much freedom and control

employees have to perform their job, like schedule their work, make their own decisions

rather than to take instructions or determine the means to accomplish the goals (Ali,

2009). Autonomy is the freedom and independence to do one’s job (De Cenzo &

Robbins, 1994). Job autonomy is the amount of job related independence, initiative and

freedom either permitted or required in the daily work routine (Stamps & Piedmonte,

1986).

Meeting time demands refers to the time taken by the layoff survivor to complete

the required task whereas work efficiency refers to the efforts of layoff survivors to

accomplish tasks in a given time period.


Figure 3.1 given below represents the theoretical model for the relationship of the

variables used for the current study.

3.3. Proposed model.

WLI

RO

WLB

JS ER OC LS

EP

WLI Work load increase LS Life satisfaction

RO Role over load OC Organizational commitment

WLB Work - life balance ER Employee retention

JS Job satisfaction EP Employee productivity

Figure 3.1. Illustration by figure of hypothesis.

Labor costs contribute a major expenditure for most of the employers, that is why

many employers are interested in finding ways to minimize staffing levels (Heiler,

Pickersgill & Briggs, 2000) at the same time they try to maximize or at least maintain


employee productivity. Motivated by the desire to improve performance and competitive

advantage, many organizations have implemented organizational restructuring,

downsizing, new workplace enterprise agreements, technologies and methods of work, all

which have had profound impacts on employee workloads (O’Donnell, 1997).

Downsizing, an intentional reduction in the workforce by an organization (Sronce

& McKinley, 2006), generally has a number of harmful physical and psychological

consequences. Downsizing brings with it the higher levels of workload for the people

who remain in the organization after downsizing that in-turn leads to increase in role

overload due to shortage of the heads to work. Brockner, Spreitzer, Mishra, Hochwarter,

Pepper & Weinberg (2004), Fong & Kleiner (2004), Virick et al. (2007), Grunberg et al.

(2000), Guiniven, (2001), Robbins, (1999), Budros, (1999), Cameron, (1994), Freeman,

(1994) and Kane, (1999) carried out researches about the layoff survivors and revealed

different results. Previous studies have explored the effects of downsizing and have found

that downsizing and job insecurity have negative effect on survivors’ well - being

(Hartley et al. 1991; Ashford, 1988).

Maximum variables included in the model play the role of dependent variable as

well as an independent variable. As the model examines the relationship of one variable

on the other that ultimately leads to maintain the productivity among layoff survivors. It

is apparent that the survivors expect more workload after layoff and when they reach

their workplaces they actually experience the same. While dealing with high workloads

the survivors may become over fatigued and lose their productivity which harms the

overall operations of the organizations. At this moment provision of work - life balance

opportunities to the survivors may help them to be comfortable while at work and sustain

their productivity.

One to one relationship is discussed by the support of the available literature.

3.3.1. Post layoff perceived work load increase and role overload.

Excessive workloads are frequently used to describe employment conditions in

the human service industries (Kahn & Byosiere, 1992). Macdonald (2003) highlighted

that most of the workload constructs are related to the workload associated with the

performance of particular tasks rather than whole job.


The literature identified that perceived workload increase is associated with role

overload. The employees who experience more workload are more likely to experience

role conflict, role ambiguity and role overload or any one of them. Moreover, excessive

workload is also responsible for the reduced job and life satisfaction and it has the

negative relationship with work - life balance too (Virick, et al., 2007; Adebayo, 2006;

Kim & Wright, 2007; Butt & Lance, 2005; Skinner & Pocock, 2008). Work stress is

responsible to reduce the productivity among employees (Holmes, 2001).

One of the Swedish study reported that due to downsizing employee workload

increased by twenty percent which resulted in dramatically increased sick leaves

(Lindberg & Rosenqvist, 2005). Moreover the authors suggested that the workload must

be maintained adequate to keep employees under positive stress and motivated. In the

light of these findings it is necessary to maintain a necessary level of workload but not

leading to role overload, creating negative stress.

3.3.2. Role overload and work - life balance.

Multiple roles are seen to deplete energy and contribute to role overload and

stress (Goode, 1960). Virick et al. (2007) argue that role overload is related to reduced

work - life balance that in - turn results in reduced job satisfaction and life satisfaction.

The employees who are better able to balance their roles can have greater well - being

(Stephen & Shelley, 2009). Role overload is also associated with employee’s depressive

symptoms and relationship conflict which means lower work- life balance and life

satisfaction (Perry-Jenkins et al., 2007).

Role overload is inversely related to age and positively related to the number of

children and the hours worked (Thiagarajan, Chakrabarty & Taylor, 2006). Role conflict,

role overload and hours spent on paid work are the main factors affecting work to family

interface (Fu & Shaffer, 2002). Long working hours are one of the signals of role

overload and a source of work - life conflict (White et al., 2003). Workers suffering from

role conflict, role ambiguity and role overload are more likely to experience reduced job

satisfaction and organizational commitment (Lambert & Hogan, 2008).

Individual occupying work roles and perceiving more workload than they can

handle would experience negative emotions, fatigue and tension which have a positive


effect on work - family conflict. A Malaysian study about female physicians reported that

physicians experienced a considerable intensity of work - family conflict due to an

increase in the workload (Ahmad & Baba, 2003). If workload prevailing among

physicians hampers their balance of work and life activities, it is necessary to examine

this relationship among other work groups like layoff survivors.

3.3.3. Role over load and job satisfaction.

Decker and Borgen (1993) found that role overload for counselors was

moderately associated with strain but not associated with job satisfaction. A positive

correlation has rarely been found between role stress and job satisfaction (Tang & Chang,

2010). Consequently, role overload appear to negatively influence job satisfaction.

A study of bank branch managers conducted in Pakistan revealed that role

overload and role conflict directly and negatively effect job satisfaction (Malik, Waheed

& Malik, 2010).

Chou & Robert (2008) integrated two theories of job satisfaction to investigate

relationships among workplace support, role overload, and job satisfaction among 984

direct care workers. They found that job satisfaction varied both within and among

facilities. The authors found that job satisfaction was negatively associated with role

overload and at the same time it was positively associated with institutional support,

supervisor instrumental support, emotional support and coworker emotional support. The

workplace support measures and role overload were separately and independently

associated with job satisfaction.

3.3.4. Role overload and life satisfaction.

According to a study conducted by Cummings (2001) role overload is a frequent

phenomenon among salespeople, with serious consequences on the quality of life. Role

overload in the literature is responsible for the poor quality of life (Evandrou & Glaser,

2004) and affects negatively the quality of work (Conley & Woosley, 2000).

The earlier evidence, available in the literature, confirmed that the workers having

high work loads experienced work - life conflict which was positive related to higher

burnout (Bacharach, Bamberger, & Conley, 1991). Bacharach et al. examined these

relationships among two diverse samples of engineers and nurses. They suggested that


work and non - work domains should be reconsidered because work home relationships

might be dependent upon the way different occupational groups perceive their work

situations. The current study explores the relationship of role overload (work domain)

and life satisfaction (non - work domain) in a different occupational group of layoff

survivors’.

3.3.5. Work - life balance and job satisfaction.

By applying work-life course of actions, an organization can enhance its ability to

respond to demands of customers for better access to services and also the tactics for the

organizations to deal with the revolutionized way in order to satisfy both employees and

employers (Manfredi & Holliday, 2004).

Carr, Boyar and Gregory (2007) reported that when individuals view work as

being more vital to their lives, the negative relationships between work family conflict

(WFC) and organizational attitudes and organizational retention is suppressed.

If an organization is perceived as unsupportive of work – family balance then turnover

intent increases. Non availability of work - life balance practices, deficiency of

opportunities for advancement, uncomfortable work environment, shortage of

encouragement and recognition leads to stress and ultimately results in burnout,

dissatisfaction and finally boosts turnover rate in the organization (Ahmadi & Alireza,

2007; Ahmed et al., 2010).

Work - life conflict causes job dissatisfaction. The consequences of job

dissatisfaction includes physical and psychological distress, decreased level of

productivity and commitment, turnover intention, etc which may harm the employees

commitment to the organization and retention. This can be curbed out via counseling with

employees at work place by the managers (Calvo-Salguero, Carrasco-González, &

Salinas-Martínez de Lecea, 2010).

A good balance between the work roles and non - work (life) roles help

employees get maximum satisfaction. Satisfaction with work - life balance policies and

practices in an organization are associated with employee’s job satisfaction and life

satisfaction (Ezra & Deckman, 1996) and young generation is more likely to worry about

balancing their work and life domains (Charles & Harris, 2007). Work - life balance is


associated with organizational commitment of employees (Kinnie et al., 2005; Brough et

al., 2008), greater job satisfaction (Oswald, 2002; Cabrita & Heloísa, 2006), job

satisfaction and life satisfaction (Hughes & Bozionelos, 2007), family satisfaction and

positive emotional and physical well - being (Burke, 2000) company loyalty and positive

attitudes to work (Moore, 2007), work - life conflict, commitment, productivity, part time

work and turnover/ retention of employees (Sturges & Guest, 2004; Brough et al., 2008).

Psychological well - being was found to have relationship with job satisfaction

(Wright & Bonett, 2007). Better human resource practices result on high level of job

satisfaction and commitment (Appelbaum, Bailey, Berg & Kalleberg, 2000) and use of

specific HR practices enhance workplace trust, job satisfaction, commitment, effort and

perceived organizational performance (Gould-Williams, 2003). Incentive programs,

praise, recognition, and ongoing opportunities for development (WLB practices)

positively affect retention (Krueger & Rouse, 1998).

It is easy to infer from the available findings that work - life balance is related to

greater organizational commitment, higher job and life satisfaction and is a source of

retaining employees in the organizations for a longer period of time. Perry - Smith and

Blum (2000) mentioned that only the presence of work - life balance policies in an

organization is a reflection of higher perceived organizational performance. How these

relationships exist in a group of layoff survivors is examined by applying statistical tests

in this research study.

3.3.6. Work - life balance and life satisfaction.

DeFour & Brown (2006) by using hierarchical multiple regression analyses

revealed that managing home and work life was important to family - life satisfaction.

Work - life balance practices at the forefront of worker welfare policy improve the

wellbeing of the workforce (Asadullah & Fernández, 2008).Changes in work - life

balance practices at the firm or even the national level could inform policy aimed at

improving the well - being of the workforce (Hayward, Fong, & Thornton, 2007).

There is evidence that well-being and satisfaction of workers is on the decline in

Britain (Gardner & Oswald 2002) calling for a better understanding of the possibility of

improving well-being using non-pecuniary factors.


Minimizing the conflict between the role of mother and the role of worker may

contribute to an improved general life satisfaction and well-being (e.g., Argyle, 1989).

Balancing competing demands of work and family life under growing individual

aspirations and expectations makes reconciliation an important component of life

satisfaction and quality of life.

Work - family conflict take place when the demands or expectations linked with

one domain are incompatible with the demands or expectations linked to the other

domain (Calvo-Salguero, Carrasco-González, & Salinas-Martínez de Lecea, 2010).

3.3.7. Work - life balance and employee retention

Various methods adopted by the organizations to retain their employees and

enhance commitment among them include compensation (Parker & Wright, 2000),

Challenging work (Beck, 2001), work relationships (Clarke, 2001), recognition (Davies,

2001), work - life balance (Perry – Smith & Blum, 2000), effective communication

(Gopinath & Becker, 2000). These strategies help organizations to boost retention and

commitment among employees (Beck, 2001). A sense of accomplishment is a strong

motivator for he employees. Employees tend to remain with the organization when they

feel that their capabilities, efforts and performance are recognized and appreciated

(Davies, 2001).

3.3.8. Work - life balance and organizational commitment

Work - life balance practices adopted by the organizations positively effects the

organizational commitment of the employees (Gumbus & Johnson, 2003; Sturges &

Guest, 2004; Kinnie et al., 2005; Noor, 2009; Dockel et al., 2006) that enhances

satisfaction among employees and leads to higher productivity.

At times even only availability of work - life balance practices, regardless of

actual use, proves to produce favorable results in terms of work-related attitudes. For

instance, the availability of organizational resources, including flexible work hours, has

been linked to job satisfaction and organizational commitment for women and other

employees having family responsibilities, regardless of whether or not these resources are

being used (Scandura & Lankau, 1997). Literature is silent about existence of these


relationships among layoff survivors. This study helps to test thee relationship of work -

life balance and organizational commitment in the mentioned group of workers.

3.3.9. Job satisfaction and employee productivity.

Job satisfaction and commitment are primary determinants of employee turnover,

performance, and productivity (Okpara, 2004). Committed and satisfied employees are

normally high performers that contribute towards organizational productivity (Samad,

2007). Job satisfaction is found related to employee productivity (Steijn, 2004).

A decreased level of job satisfaction envisages negative attitudes and behavior in

the work context including absenteeism, external turnover and reduced productivity

(Calvo-Salguero, Carrasco-González, & Salinas-Martínez de Lecea, 2010).

3.3.10. Life satisfaction and employee productivity.

Satisfaction of employees with their life has favorable effect on employee health

that in - turn improves employee productivity. When needs and goals of employees are

realized they feel more satisfied with their lives and in this situation they generally react

more positively (Diener, 1984).

The evidence is available that health problems such as social anxiety disorder

leads to reduced productivity in the workplace and life satisfaction is caused by rich

mental health and poor mental health makes life dissatisfaction (Tamini & Far 2009).

Since very little is known about this relationship in the past, the present study will

help to affirm the relationship of life satisfaction and layoff survivors productivity in a

developing country in Asia.

3.3.11. Employee retention and employee productivity.

Many organizations are facing challenging environment and strive to retain core

employees. This is especially true in the knowledge based society where human capital is

considered a key resource and important for the survival of businesses. That’s why the

businesses are competing for the best talent employees (Porter, 2001).

New paradigm companies recognize that an important element in business

management practices is the need to successfully motivate and retain high talent


employees who survive organizational restructuring, downsizing, consolidation,

reorganizing, or re - engineering initiatives (Clarke, 2001).

The loss of needed talent may result in the lost productivity (Eskildsen & Nussler,

2000). It is more cost - effective and productive for management to design the work

arrangements to fit the human than it is to force the human to fit the system (Barnet &

Hall, 2001).

Abbasi and Hollman (2000) indicate that losing a critical employee for an

organization negatively impacts the innovation, consistency in providing service, and

delivery of services to customers. Francis (2004) reports that staff turnover has specific

expenses related to retraining, recruitment, and lost productivity.

When skilled employees leave an organization, it is likely to curb the company’s

profitability due to increased expenses of recruitment and lost of its competitive

advantage (Griffeth & Hom, 2001; Walker, 2001; Eskildsen & Nussler, 2000).

3.3.12. Organizational commitment and employee productivity.

Francis (2004) noted that affective commitment have been associated with higher

levels of productivity and a more positive work attitude.

Organizations are facing vital challenges resulting from restructuring,

reengineering and downsizing. The need for factors that predict organizational

commitment has become more crucial. Organizational commitment is one of the factors

that lead to healthy organizational climate, increased morale, motivation and

productivity. Organizational commitment is a key area for research within the studies of

industrial/organizational psychology (Salami, 2008; Adebayo, 2006)

Employee productivity is affected by workload (Holmes, 2001), role overload

(Tarafdar et al., 2007), work-life balance (Brough et al., 2008), job satisfaction (Shikdar

& Das, 2003), employee retention (Fatt, Sek Khin & Heng, 2010), organizational

commitment (Raymond & Flannery, 2002; Ugboro, 2006) and downsizing (Yu & Park,

2006).

Employee productivity is related to downsizing (Yu & Park, 2006), skills and

workforce development, and economic performance, organizational performance and

training (Giles & Campbell, 2003), role overload (Tarafdar et al., 2007), job stress, job

http://www.jmis-web.org/cgi-bin/gencontrib.pl?Monideepa++Tarafdar+1138



dissatisfaction and the indoor environment (Roelofsen, 2002), impact of labor (the

number of employees) and capital (number of rooms available for sale) (Brown & Dev,

2000), organizational climate and competitive strategy (Neal, West & Patterson, 2005),

job loss and participation (Forde, Slater & Spencer, 2006), Protestant Work Ethic (PWE)

(Firestone, Garza & Harris, 2005), career development programs including quality of

working life and job satisfaction (Chen, Chang & Yeh, 2006).

3.2. Hypothesis.

The hypotheses developed for the study in the light of literature are as follows. The

hypotheses are aimed to highlight the cultural aspect of many of the issues among layoff

survivors such as, perceived workload increase, role overload, work - life balance, job

satisfaction, life satisfaction, retention of layoff survivors in the same organization,

organizational commitment, and ultimately employee productivity.

Hypothesis 1. Post - layoff perceived workload increase is positively related to role

overload of layoff survivors after downsizing in a developing country, Pakistan.

Hypothesis 2. Role overload is negatively related to work - life balance of layoff

survivors after downsizing in a developing country, Pakistan.

Hypothesis 3. Role overload is negatively related to job satisfaction of layoff survivors

after downsizing in a developing country, Pakistan.

Hypothesis 4. Role overload is negatively related to life satisfaction of layoff survivors

after downsizing in a developing country in Asian region.

Hypothesis 5. Work - life balance is positively related to job satisfaction of layoff


Hypothesis 6. Work - life balance is positively related to life satisfaction of layoff



Hypothesis 7. Work - life balance is positively related to retention of layoff survivors


Hypothesis 8. Work- life balance is positively related to organizational commitment of

layoff survivors after downsizing in a developing country, Pakistan.

Hypothesis 9. Job satisfaction is positively related to productivity of layoff survivors after

downsizing in a developing country, Pakistan.

Hypothesis 10. Employee retention is positively related to productivity of layoff


Hypothesis 11. Organizational commitment is positively related to productivity of layoff


Hypothesis 12. Life satisfaction is positively related to productivity of layoff survivors


Hypothesis 13. There is a significant difference in means of various variables between the

two groups (PTCL and HBL) of layoff survivors in a developing country, Pakistan.

Table 3.1 summarizes the hypothesized relationships of the variables of interest and

theoretical support available in the literature in descending order.


Table 3.1

Hypothesized Relationships and Theoretical Support

Hypothesized Relationships Theoretical support

H1: WLI – RO (Bashir & Ramay, 2010; Dasgupta & Kumar, 2009;

Nadeem & Abbas, 2009; Dasgupta & Kumar, 2009;

Virick et al., 2007; Yao, Wang & Zhang, 2007;

Fields, 2004; Lee et al., 2001; Bliese & Castro,

2000; Temple, Warm, Dember, Jones, LaGrange &

Matthews, 2000; Shultz, Quick, Quick, Nelson &

Hurrell, 1997; Marini et al., 1995; Dember, Warm,

Nelson, Simon, Hancock & Gluckman, 1993; Rizzo

et al., 1970).

H2: RO – WLB (Tang & Chang, 2010; Skinner & Pocock, 2008;

Thiagarajan, Chakrabarty & Taylor, 2006; Fu &

Shaffer, 2002; Conley & Woosley, 2000; Shreekant,

James & Karin, 1991).

H3: RO – JS (Pearson, 2008; Jones et al., 2007; Athanasios,

Nicholas & Dimitris, 2004; Yousef, 2002; Home,

1998).

H4: RO – LS (Perry-Jenkins et al., 2007; Evandrou & Glaser,

2004).

H5: WLB – JS (Malik, Saleem & Ahmad, 2010; Rehman, Khan,

Ziauddin & Lashari, 2010; Calvo-Salguero,

Carrasco-González & Salinas-Martínez de Lecea,

2010; Asadullah & Fernández, 2008; Ju, Kong,

Hussin & Jusoff, 2008; Hughes & Bozionelos,

2007; Cabrita & Heloísa, 2006; Butt & Lance,

2005; Steijn, 2004; Foley et al., 2004; Hancer &

George, 2003; White et al., 2003; Schermerhorn et

al., 2002; Oswald, 2002; Ezra & Deckman, 1996).

H6: WLB – LS (Adekola, 2010; Omar, 2010; Karimi, 2009; Rego

& Cunha, 2009; Cunningham & Rosa, 2008;

Moore, 2007; Saraceno et al., 2005; Francis, 2004;

Stewart, 2003; Stewart, Donald & Grant-Vallone,

2001; West, 2000; Adams, 1996; Argyle, 1989).

H7: WLB – ER (Malik, Gomez, Ahmad & Saif, 2010; Deery, 2008;

Cole & Flint, 2005; Lockwood, 2003; Jamison,

2003; Wagar, 2003; Konrad & Mangel, 2000;

Greenhaus & Parasuraman, 1999; Deery & Shaw,

1999)


H8: WLB – OC (Noor, 2009; Kinnie, Hutchinson, Purcell, Rayton &

Swart, 2005; Dockel et al., 2006; Sturges & Guest,

2004; Gumbus & Johnson, 2003; Walker, 2001)

H9: JS – EP (Malik, Ahmad, Saif & Safwan, 2010; Malik, Saif,

Gomez, Khan & Hussain, 2010; Chen, Chang &

Yeh, 2006; Sigala, 2004; Shikdar & Das, 2003;

Goetzel & Ozminkowski, 2002; Roelofsen, 2002;

Schermerhorn et al., 2002).

H10: ER – EP (Fatt, Sek Khin & Heng, 2010; Proudfoot, Corr,

Guest & Dunn, 2009; McShane & Glinow, 2005;

North, Rasmussen, Hughes & Finlayson 2005;

Shaw, Gupta & Delery, 2005; Dess & Shaw, 2001;

Huselid, 1995).

H 11: OC – EP (Fatt, Sek Khin, & Heng, 2010; Bhatti & Qureshi,

2007; Ugboro, 2006; Ishigaki, 2004; Raymond &

Flannery, 2002).

H12: LS – EP (Tamini & Far, 2009; Viren et al., 2007; Hyun &

Jenny, 2006; Eng, Coles, Heimberg & Safren, 2005;

Keyes, Shmotkin & Ryff, 2002; Robbins &

Kliewer, 2000; Stein & Kean, 2000; Wittchen,

Fuetsch, Sonntag, Muller & Liebowitz, 1999;

Diener, 1984).

Source: Hypothesized relationships and theoretical support available in the literature.


Chapter 4

Research Methodology

Pilot study.

o Population

o Sample

o Instrument

o Procedure

o Results and conclusion.

Main study.

o Objectives

o Sampling design

o Instruments

o Data collection

o Statistical methodology

o Confirmatory factor analysis


Chapter 4

Research Methodology

This chapter explains the methodology used for the study. This is done in two phases. In

the first phase, a pilot study is conducted to pre-test the instruments used and in the

second phase the main study is explained and elaborated. The study has undergone the

following two phases.

4.1. Pilot study.

The research design for the pilot study is meant for the following reasons.

1. To develop a complete research design to be followed for the main study.

2. To check the reliabilities of the scales adopted for the measurement of variables

included in the model.

3. To improve the sentence structure and phrasing of items of the questionnaire, if

needed.

4. To observe the respondents’ reaction to the 5 – point Likert type scale

including readability and understandability of the questions asked and to get the

useful feedback.

4.1.1. Target Population.

The population of the pilot study is comprised of the layoff survivors who are still doing

jobs in the selected organizations that are Pakistan Telecommunication Company Limited

and Habib Bank Limited. These two organizations have laid - off their employees by

offering them schemes like Voluntary Separation Scheme (VSS) and Golden Hand Shake

(GHS) respectively. The employees considered for the study are those who are still

working in the organizations and have not chosen to leave their organizations by

accepting any of the schemes offered by the organizations.

4.1.2. Sample.

The researchers generally go for sampling for two main reasons (Adèr, Mellenbergh &

Hand, 2008) firstly, to reduce the costs related to the collection of data about a population


by collecting data from a subset instead of the whole population and secondly due to the

dynamic nature of the population. In the dynamic nature the individuals making up the

population may change overtime. Few other authors stated that the advantages related to

the sampling are lower cost, fast data collection and for small data sets possibility of

ensuring the homogeneity, accuracy and the quality of data (Kumar, 2005; Chaudhary &

Kamal, 2004; Sekaran, 2003) .

The participants of the pilot study are a convenience sample from the two

organizations including the employees from top level management, middle management

and the first level management. A total of 175 questionnaires were distributed among the

employees in different cities mainly including Peshawar, Rawalpindi and Islamabad. Out

of 175 distributed questionnaires, 106 questionnaires were returned resulting in 60.5%

response rate. Six incomplete and carelessly filled questionnaires were removed before

carrying out the analysis to improve the reliability and validity of the measures and

results. The final response rate was 57.1%. Out of 100 respondents 41 belonged to the

Peshawar region, 46 belonged to the Islamabad region and 13 respondents belonged to

the Rawalpindi region. Out of the total sample size 45 respondents were from HBL and

55 were from PTCL.

4.1.3. Instrument.

A 100 - items questionnaire is employed for the data collection. Westberg (2004, p. 95)

elaborates the survey method of data collection may be used for research purpose

including descriptive and explanatory research. By using survey the researchers dig out

information by written set of questions or an interview. The responses are then

summarized in a quantifiable form and generalizations are made to the larger population.

Another researcher states that a large number of data collection is possible by using

surveys in limited time and budget (DeVaus, 2002). Kumar (2005) states about using the

questionnaire that it is less expensive way of data collection and increases the likelihood

of obtaining accurate information from the respondents because it provides greater

anonymity.

The instrument used for the current study mainly comprised of three parts. The

instruments are developed in the light of previous research studies carried out by different


researchers across globe. The part wise description of the instrument is discussed as

follows.

4.1.3.1. First part

The first part served as the cover letter describing the objectives of the research

study, along with the instructions to complete the questionnaire.

4.1.3.2. Second part

The second part attempts to measure the demographic variables for the pilot

study. The variables included are the name of the organization in which the respondent

works, the gender of the respondents, the educational qualifications they have, the marital

status, management level at which they work and the number of dependents (children

and/or elders) they have. The following discussion provides the details of the remaining

part.

4.1.3.3. Third part

The third part measures the employees’ responses about post - layoff work load

increase, role overload, work - life balance, job satisfaction, life satisfaction,

organizational commitment, employees’ retention and employee productivity. The

instrument to measure the responses is developed after going through the previous

researches. The instrument is designed according to the Pakistan organizational

environment and the research settings.

To get the genuine responses few minor changes have been introduced in the

questionnaire to make it more simple and understandable. To do this a panel of 10 PhDs,

from different disciplines like Economics, Psychology, Management Sciences, and

Sociology have been consulted and their opinion is sought for the questionnaire

developed. As a result the questions are restructured to make them simpler as the first

language of the respondents is not English.

All the items of the questionnaire used are assessed on the 5 - point rating scale

(Likert scale) for the variables included in the model. Items are listed to get responses in

a convenient way with out any distraction. For this reason the serial numbers for the

items are assigned with respect to the name of the variable (i.e.) the serial numbers for the


post - layoff perceived work load increase are assigned as WLI - 1 To WLI - 8, where

WLI stands for Work Load Increase. Similarly all other variables are assigned serial

numbers with respect to their respective variable name.

Post - layoff perceived workload increase

Post - layoff perceived workload increase is assessed on an eight item scale (item

WLI - 1 to WLI - 8) by adopting the items from three different scales to cover maximum

dimensions of the variable. Previously the scales have been developed by Price and

Mueller (1981), Kim and Lee (2007) and Bolino and Turnley (2005). The tool contains

08 items (item WLI - 1 to WLI - 8) whereas, four items are adopted from Price and

Mueller (1981), three items from Kim and Lee (2007) and one item from Bolino and

Turnley (2005). The scale developed by Price and Mueller (1981) and modified by

Iverson (1992) is based on 5 - point Likert scale where 1 - represents ‘strongly disagree’

and 5 - represents ‘strongly agree’. The possible total score for the measure ranged from

8 to 40, where high scores indicated a higher level of workload on the job. None of the

items included are reverse coded. All the items are averaged and used for analysis.

On the recommendation of the panel of eight PhDs some changes are introduced

to the instrument. The statement “I never seem to have enough time to get everything

done at work” is rephrased as “I feel that I never have enough time to get everything done

at work” (item - WLI2). The other statement “I feel my work load is ------- (1 = never too

heavy, 2 = seldom too heavy, 3 = sometimes too heavy, 4 = often too heavy, 5 = almost

always too heavy’ is rephrased as “I feel my work load is always too heavy” (item -

WLI5). The next statement “How do you feel about the amount of work you’re expected

to do? ______ “ (1 = very dissatisfied, 2 = dissatisfied, 3 = neither dissatisfied nor

satisfied, 4 = satisfied, 5 = very satisfied)” is rephrased into “the amount of work I am

expected to do never allows me to do a good job” (item - WLI6). The other statement “It

often seems like I have too much work for one person to do. ____ (1 = strongly disagree,

2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = strongly agree)” is rephrased

into “I feel that I have too much work for one person to do” (item - WLI8). None of the

statements used are negatively worded.


Role overload

Role overload is assessed by using 13 items (item RO - 1 to RO - 13) originally

developed by Reilly (1982). The scale is based on 5 - point Likert scale where 1 -

represents ‘strongly disagree’ and 5 - represents ‘strongly agree’. The scores can range

from 13 to 65, with the higher score indicating greater role overload. The scores for

overload are obtained by summing the scores for each respondent. The possible total

score for the measure ranges from 13 to 65, where high scores indicate a higher level of

role overload on the job. Later on the scores are averaged by using compute command in

the Statistical Package for Social Sciences (SPSS) for the final analysis of the study. The

few minor changes introduced to the statements are; “I do not ever seem to have any time

for myself” is rephrased as “It seems that I do not have any time for myself” (item -

RO6). The language of the statement is made simple to increase the understandability of

the respondents. The statement means that an employee while at work do not have time to

look after his/her personal affairs. The statement “I have to overextend myself in order to

be able to finish everything I have to” is rephrased into “sometimes I have to overextend

myself in order to be able to finish everything I have to” (item - RO9). The next

statement rephrased is “I find myself having to prepare a priority list to get done all the

things I have to do otherwise I forget” into “I have to prepare a priority list to get all

things done, otherwise I forget” (item - RO11).

Work - life balance

Work - life balance is assessed on a five item scale (item WLB - 1 to WLB - 5)

developed by Hill et al., (2001) and employed by Malik, Saleem and Ahmad (2010).

Items are assessed on a five point Likert scale, 1 - representing ‘strongly disagree’ to 5 -

representing ‘strongly agree’. When averaged lower scores mean lower balance and the

higher scores mean higher balance between work and life of the layoff survivors. The

total possible scores for the measure, while summing, range from 5 to 25, where high

score indicate a higher level of work - life balance. The sentences of the questionnaire to

assess work - life balance are restructured and made easy in terms of wordings and rating

scale on the recommendation of the panel.


The changes introduced to the instrument include the restructuring of the

sentences to rate the items on the same five point Likert type scale. The changes are;

“how easy or difficult is it for you to balance the demands of your work and your

personal and family life (5 - point scale: very easy to very difficult)?” is rephrased into “It

is very easy for me to balance the demands of work and personal and family life” (item –

WLB1). The statement “I have sufficient time away from my job at IBM to maintain

adequate work and personal/family life balance (5 - point scale: strongly agree to strongly

disagree).” It is rephrased into “I have sufficient time away from my job at my

organization to maintain adequate work and personal/family life balance” (item - WLB2).

The next statement is “When I take a vacation, I am able to separate myself from work

and enjoy myself (5 - point scale: strongly agree to strongly disagree)”. No change is

made in this statement (item - WLB3). The next statement “All in all, how successful do

you feel in balancing your work and personal/family life (5 - point scale: extremely

successful to extremely unsuccessful)?” is restructured into “All in all I feel completely

successful in balancing my work and personal and family life” (item - WLB4). The last

item of the original scale “How often do you feel drained when you go home from work

because of work pressures and problems (5 - point scale: never to almost always)?” is

restructured into “I always feel drained when I go home from work because of work

pressures and problems” (item - WLB5). None of the items included in the scale are

negatively worded.

The major work - life balance facilities/options provided to the layoff survivors

included paid maternity leave for female employees, emergency leave, paid annual leave,

provision of adequate time to complete a specific task, job sharing with colleagues (social

support) etc. These facilities are identified in a meeting with the management of both

organizations that is HBL and PTCL.

Life satisfaction

Life satisfaction is assessed by using “Satisfaction With Life Scale” (SWLS)

having five item (LS - 1 to LS - 5) and being developed by Diener et al., (1985). SWLS

assesses the global life satisfaction instead of assessing facets of life satisfaction. Items

are assessed on a five point Likert scale, 1 - representing ‘strongly disagree’ to 5 -


representing ‘strongly agree’. The scores are averaged. The least score represent lower

satisfaction and the higher score represent higher satisfaction with life. Some minor

changes introduced to the statements include “if I could have my life over, I would

change almost nothing” replaced with “if I have another chance in life I will change

nothing” (item – LS5). The possible total score for the measure, when summed, ranged

from 5 to 25, where high scores indicate a higher level of satisfaction with life. All the

items of SWLS are in positive direction.

The SWLS is examined for reliability and sensitivity, and has shown strong

internal reliability. SWLS has been used by the researchers for cross - cultural studies and

it has been produced in different languages including, French, Dutch, Russian, Korean,

Hebrew, and Chinese (Pavot & Diener, 1993).

Organizational commitment

Commitment is loyalty to a social unit. The social unit may include an

organization, a sub - system of an organization, or an occupation. Most of the researchers

have focused on the organizations rather than sub - systems or occupations (Price, 1997).

Organizational commitment (affective, continuance and normative) is assessed on a five

point Likert scale developed by Meyer and Allen (1997). All the 18 items (OC - 1 to OC

- 18) are selected (6 - items each) to assess affective, continuance and normative

commitment. The possible total score for the measure, when summed, ranges from 18 to

90, where high scores indicate a higher level of commitment to the organization.

Affective commitment refers to a sense of belonging and emotional attachment to

the organization whereas continuance commitment refers to the perceived costs of

leaving the organization. The normative commitment refers to the perceived obligation to

remain with the organization.

Items are assessed on a five point Likert scale, 1 - representing ‘strongly disagree’

to 5 - representing ‘strongly agree’. The lower score depicts least commitment and the

higher depicts the higher commitment. No changes are introduced to the scale.


Employee retention

Employee retention is assessed on a four itemed scale (ER - 1 to ER - 4)

developed by Cammann et al., (1979). Items are assessed on a five point Likert scale, 1 -

representing ‘strongly disagree’ to 5 - representing ‘strongly agree’. The scale is

previously used by the different researchers such as Dalessio, Silverman, and Schuck,

(1986), Griffeth, Hom, and Gaertner (2000), Lambert, Hogan and Barton (2001), Mathieu

and Zajac (1990) and Mueller and Wallace (1992). Participants are asked to indicate the

likelihood that they would remain and would not leave the organization in the near future.

The total possible score for the measure ranges from 4 to 20, where high scores indicate a

higher intention to remain with the organization.

The scores obtained are averaged for the final analysis. The lower score

represents the least interest to remain with the organization and the higher scores

represent the higher interest to remain with the organization. The scale is worded so

simple that the researcher felt no need to introduce changes or rephrase the original scale.

Employee productivity

Sigala (2004) notes that people have made attempts to identify satisfactory

productivity - monitoring procedures, but these approaches have been heavily criticized

and no generally accepted means of productivity measurement exist.

The scale for employee productivity is developed with a focus on the job

autonomy of layoff survivors, meeting the time demands and work efficiency of the

layoff survivors. Layoff survivors are asked to fill the questionnaire keeping in mind the

available work - life balance facilities/ practices.

The job autonomy scale (EP - 1 to EP - 8) developed by Morgeson and Humphrey

(2006) is used to measure the level of employees’ autonomy on the jobs they hold. The

autonomy includes three interrelated aspects centered on freedom in work scheduling,

decision making and work methods. The total possible score for the measure ranges from

8 to 40, where high scores indicate a higher level of autonomy on the job. On the panel’s

recommendations, the sentence structure for all the items is improved. For example the

item ‘The job allows me to plan how I do my work’ is altered to ‘My job allows me to

plan how I do my work’.


On the recommendation of the panel items for meeting the time demands and

efficiency are developed from the Work Limitations Questionnaire (WLQ) developed by

Lerner et al. (2001). Only four items (EP - 9 to EP - 12) are used to assess time demands

as a part of assessing productivity. The possible total score for the measure ranges from 4

to 20, where high scores indicate a higher level of meeting the demands on the job.

Five items for the work efficiency are developed form the study by Tangen

(2005). The scale is used to assess work efficiency (EP - 13 to EP - 17) as a part of

employee productivity. On the recommendation of the panel two items are added to the

available scale that are “I do not put my work off till tomorrow, what I can do today” and

“I can effectively handle my work within the available given resources” to assess the

effectiveness of the layoff survivors. The total possible score for the measure ranged from

05 to 25 for efficiency and 02 to 10 for effectiveness, where high scores indicate a higher

level of efficiency and effectiveness. The scores are averaged before using for the final

analysis.

Job satisfaction

Job satisfaction is assessed using Minnesota Satisfaction Questionnaire (MSQ)

short form having 20 items (item JS1 to JS20) developed by Weiss et al., (1967). This

scale is employed for the data collection because the other scales (e-g. Brayfield & Rothe,

1951, Dunham & Herman, 1975, Quinn & Staines, 1979, and Ironson et al., 1989),

emphasize on measuring the global satisfaction whereas the scale developed by Weiss et

al. (1967) provides dimensional/facet measures for satisfaction. The items are rated at

five point likert type rating scale where 1 - represented ‘strongly dissatisfied’ and 5 -

represented ‘strongly satisfied’. The items for assessing job satisfaction of layoff

survivors are listed in the end of the questionnaire because all other items of the

questionnaire are assessed on a five point Likert scale ranging from 1 = ‘strongly

disagree’ to 5 = ‘strongly agree’ whereas the scale for job satisfaction is rated at 1 =

‘strongly dissatisfied’ to 5 = strongly satisfied’. The total possible score for the measure

ranged from 20 to 100, where high scores indicated a higher satisfaction with the job.

The MSQ consists of three subscales including intrinsic satisfaction scale,

extrinsic satisfaction scale and the global satisfaction scale. The intrinsic satisfaction


scale comprises of 12 items (item number JS1, JS2, JS3, JS4, JS7, JS8, JS9, JS10, JS11,

JS15, JS16, and JS20), extrinsic satisfaction scale comprises of 06 items (item number

JS5, JS6, JS12, JS13, JS14, and JS19) and global or general satisfaction comprises all

items (JS1 to JS20).

4.1.4. Procedure.

Participants are approached in their respective organizations/offices that is

different branches of Habib Bank Limited and regional offices of Pakistan

Telecommunication Company Limited, either by the researcher or through research

facilitators. The research facilitators are working with participants at middle management

positions in the organizations. They are asked to collect data from their respective

organizations only. In some cases the top managers are requested to gather responses

form their subordinates and colleagues for the research study. The researcher had detailed

sessions with them on subject matter and had trained them on how to instruct the

respondent to fill in the questionnaire, how to explain the items asked and how to check

the completeness of the data collection tool.

After the researcher developed a good understanding with the participants, they

were asked to fill in the second part which contained demographic variables and respond

to each statement in the third part of the questionnaire about the way they feel, think or

act in their lives or organizations by encircling the number that most appropriately

matched their answer, by using the given scale. To promote the importance of genuine

responses, participants were assured of confidentiality in collection and use of data and

accordingly data was collected anonymously, no personal information were asked

(respondent’s name, salary etc). The participants were also allowed to take time in

completing the questionnaire.

The alpha reliabilities are shown in the table 4.2 and are compared with the

reliabilities that the earlier researchers found in their studies. Although all the scales have

been used by the different researchers at different places world over, even then it is

deemed necessary to carryout a pilot study to confirm the reliability and validity of the

scales. This is done because now these scales are used in a less developed country like

Pakistan.


4.1.5. Results and conclusion.

The main purposes of the pilot study include the checking of reliability of the scale used

for the study and to gauge the suitability/understandability of the items asked. The

analysis for the pilot study is conducted using the following.

4.1.5.1. Demographics and respondent’s profile is shown in table 4.1.

4.1.5.2. Data screening.

4.1.5.3. Chronbach’s alpha and Guttman’s Split-Half coefficients for the variables

used to check the reliabilities of the scales.

4.1.5.4. Improvement of the instrument.

4.1.5.1. Demographics and respondent’s profile

The demographic and respondent’s profile is presented in the table 4.1

Table 4.1

Demographic and respondent’s profile

Variable Category Frequency Percentage

Organization HBL 45 45.0

PTCL 55 55.0

Job Experience 1 – 5 years 17 17.0

6 – 10 years 40 40.0

11 – 15 years 34 34.0

16 years or above 09 09.0

Job Status Top Management 22 22.0

Middle Management 52 52.0

First level Management 26 26.0

Gender Male 86 86.0

Female 14 14.0

Marital Status Unmarried 30 30.0

Married 70 70.0

Age 20 – 29 years 05 05.0

30 – 39 years 35 35.0

40 – 49 years 49 49.0

50 – 59 years 11 11.0

Education Matriculation 02 02.0

Higher Secondary 16 16.0

Graduation 19 19.0

Masters 60 60.0

Doctorate 03 03.0

Dependent Children Nil 49 49.0

1 – 3 45 45.0

4 – 6 06 06.0

Dependent Elders Nil 48 48.0

1 – 3 52 52.0

4 – 6 00 00.0

Source: Data from pilot study.


The total number of the respondents is 100. Out of which 45 layoff survivors

(45.0%) belong to Habib Bank Limited where as 55 (55.0%) belong to Pakistan

Telecommunication Company. Out of 45 HBL employees 09 (20%) are from top

management, 23 (51.1%) from middle management and 13 (28.9%) are from first level

management. The number of male respondents from HBL is 40 (88.9%) and female

respondents are 05 (11.1%). Whereas out of 55 PTCL employees 13 (23.6%) are from

top level management, 29 (52.7%) from middle management, and 13 (23.6%) are from

first level management. The male respondents are 46 (83.6%) and the female respondents

are 09 (16.4%). Top level managers have either Masters degree (86.3%) or Doctorate

degree (13.7%). Few (9.61%) of the employees working at middle level management

have higher secondary education. Most of the employees at this level are Graduates

(25.0%) or holding Masters degree (65.3%).

4.1.5.2. Data screening

The data is screened to make it more reliable such that it has been entered in the

data sheet correctly and properly. It also shows that the data for the analysis is normally

distributed. Normal distribution of the data for the analysis is essential. The data is

screened by converting all the scores for the variables into standardized scores and also

removed the uni-variate outliers having Z - scores more than + 3. Outliers are the cases

that have data values that are very different from the data values for the majority of cases

in the data set (Best & Kahn, 2003). The outliers have been removed by using rule of

thumb that is, if the sample size is small, having 80 responses or less, a case is an outlier

if its standard score is + 2.5 and if the sample size is larger than 80 responses, a case is an

outlier if its standard score is + 3.0 or beyond. Moreover skewness and kurtosis of the

data have been checked to ensure the normality that resulted in the acceptable range of

values.

4.1.5.3. Chronbach’s alpha and Guttman’s Split-Half coefficients

Reliability is the degree of consistency of results and the extent to which the

measurements are predictable and accurate (Kumar, 2005). Reliability of a measure is an

indication of stability and consistency and it helps to assess the goodness of a measure. A

measure is said to be reliable to the extent that it is measuring a variable consistently


(Best & Kahn, 2003). Chronbach’s alpha and the split - half reliability coefficient have

been calculated for the individual scales to confirm the internal consistency and the

reliability of the scales used.

The values of Chronbach’s alpha and Guttman split – half coefficient range from

0.70 to 0.95 for all the scales. A value of 0.70 or higher is generally considered to

indicate adequate reliability (Nunnally, 1978).

Reliabilities as high as .70 or more have been recommended by certain experts

(Bakeman & Gottman, 1986). The alpha values along with the number of items for the

main variables are presented in Table 4.2. Alpha scores for these variables range from .60

to .95. Therefore all the scales are internally consistent.

Table 4.2

Reliability Statistics of Scales

Constructs/ Number of Chronbach’s Alpha Guttman Split- Half

Variables Items Coefficients Coefficient

Workload Increase 08 0.82 0.83

Role Overload 13 0.95 0.95

Work Life balance 05 0.72 0.76

Job Satisfaction 20 0.70 0.64

Life Satisfaction 05 0.86 0.85

Employee Retention 04 0.86 0.77

Organizational Commitment 18 0.85 0.83

AOC 06 0.88 0.87

COC 06 0.72 0.73

NOC 06 0.70 0.69

Employee Productivity 19 0.66 0.81

AUTO 09 0.74 0.62

TIME 05 0.67 0.63

EFCY 05 0.64 0.84

Source: Data from pilot study.

The reliability of the total scale consisting of 92 items is 0.89. The analysis thus

shows the internal consistency and reliability of the scales.

4.1.5.4. Improvement of the instrument.

The final purpose of the pilot study has been to improve the questionnaire in

terms of its visibility, flow and comprehension by respondents. The same panel of PhDs


was consulted in this regard. Taking into account the respondents’ educational level,

language barrier and other factors, the panel recommended some changes in terms of

sentence structure, phrasing of items and replacement of difficult words. Finally, the

rating scale was repeated on each page to secure true and quick responses.

4.2. Main Study.

The second phase of the research comprises of the main study.

4.2.1. Objectives.

The objectives of the main study primarily include the testing of the proposed

model (figure 3.1). The other objectives included have been explained in chapter 1,

section 1.4 of the current study.

4.2.2. Sampling design.

The target population for the main study remains the same as of pilot study that is

the layoff survivors who are working in the two organizations operating in Pakistan, that

is, Pakistan Telecommunication Company Limited (PTCL) and Habib Bank Limited

(HBL). No study like the present one has been conducted on layoff survivors in Pakistan.

For this study the researcher employed stratified random sampling, to select a

sample, for the main study. A sample is said to be stratified random sample if it is

selected from a population which has been split into a number of non - overlapping

sectors (Chaudhary & Kamal, 2004). Various researchers have recommended and given

preference to stratified random sampling over a simple random sampling design (Zaheer,

2009; Sekaran, 2003; Shajahan, 2004; Chaudhary & Kamal, 2004) because of the more

efficiency, low cost, greater accuracy and better coverage. Stratified random sampling is

used when variations among strata are greater than the variations within strata and

information about same parts of the population is desired (Chaudhary, & Kamal, 2004).

Sekaran (2006) proposes that, sample size lager than 30 and less than 500 are

appropriate for most researches, where samples are to be broken into sub - samples such

as, male/females, juniors/seniors, etc., a minimum sample size of 30 for each category is

essential. Moreover, in multivariate research (including multiple regression analysis), the


sample size should be several times (preferably ten time or more), as large as the number

of variables in the study. The researcher determined the sample for the current study

keeping in mind all the rules of thumb proposed.

The researcher obtained the information about current employees (layoff

survivors) from Habib Bank Limited and Pakistan Telecommunication Company Limited

and implemented a proportionate stratified random sampling to select a sample for the

current study. The total number of layoff survivors currently working in the two

organizations, is 41,922. The layoff survivors working in PTCL are 29,106 (PTCL, 2009)

where as the layoff survivors working in HBL are 12,816 (Habib Bank Limited, 2009).

The three approaches to determine a sample size may be employed which include

using a census for a small population, using a sample size of a similar study and using

published tables (Israel, 1992). As no study of similar kind was available the researcher

determined the overall sample size of layoff survivors by consulting the following table

(table 4.3) presented by Jeff, (2001) and Sekaran, (2006).

Table 4.3

Table for Finding a Base Sample Size

+/- 5% Margin of Error

Variability/ Sample size

Population 50% 40% 30% 20% 10%

100* 81 79 63 50 37

125 96 93 72 56 40

150 110 107 80 60 42

175 122 119 87 64 44

200 134 130 93 67 45

225 144 140 98 70 46

250 154 149 102 72 47

275 163 158 106 74 48

300 172 165 109 76 49

325 180 173 113 77 50

350 187 180 115 79 50

375 194 186 118 80 51

400 201 192 120 81 51

450 212 203 124 83 52

500 222 212 128 84 52

600 240 228 134 87 53

700 255 242 138 88 54

800 267 252 142 90 54

900 277 262 144 91 55


1,000 286 269 147 92 55

2,000 333 311 158 96 57

3,000 353 328 163 98 57

4,000 364 338 165 99 58

5,000 370 343 166 99 58

6,000 375 347 167 100 58

7,000 378 350 168 100 58

8,000 381 353 168 100 58

9,000 383 354 169 100 58

10,000 385 356 169 100 58

15,000 390 360 170 101 58

20,000 392 362 171 101 58

25,000 394 363 171 101 58

50,000 397 366 172 101 58

100,000 398 367 172 101 58

a) This table assumes a 95% confidence level, identifying a risk of 1 in 20 that actual

error is larger than the margin of error (greater than 5%).

b) Base sample size should be increased to take into consideration potential non-

response.

c) A five percent margin of error indicates willingness to accept an estimate within

+/- 5 of the given value.

d) When the estimated population with the smaller attribute or concept is less than

10 percent, the sample may need to be increased.

e) The assumption of normal population is poor for 5% precision levels when the

population is 100 or less. The entire population should be sampled, or a lesser

precision accepted.

The sample can also be determined using three criteria to select the appropriate

sample size such as, the level of precision, also known as sampling error, that is the range

in which the true value of the population is estimated to be. Its range is generally

expressed in percentage points, the level of confidence generally known as risk that is

based on ideas covered under the Central Limit Theorem. The key idea expressed in the

Central Limit Theorem is that when a population is repeatedly sampled, the average value

of the attribute obtained by those samples is equal to the true population value. In

addition, the values obtained by these samples are distributed normally about the true

value, with some samples having a higher value and some obtaining a lower score than

the true population value. In a normal distribution, approximately 95% of the sample

values are within two standard deviations of the true population value (e.g., mean), and

the degree of variability, that is the distribution of attributes in the population (Miaoulis

& Michener, 1976; Israel, 1992). The more heterogeneous a population, the larger the


sample size required to obtain a given level of precision and the less variable (more

homogeneous) a population, the smaller the sample size.

For the purpose of stratification the researcher divided the population mainly into two

strata on the basis of organizations. Later the researcher further stratified the population

on the basis of number of layoff survivors in each province of Pakistan. The strata were

made in the light of distribution of the total population. Later the researcher distributed

the questionnaires on the proportionate basis with respect to the strata made. The strata

for the population included the layoff survivors working in Punjab, Sindh, Bluchistan,

Khyber Pakhtoonkhawh and the Federal regions for each organization. 25% sample was

gathered from each stratum. Table 4.4 shows the stratification of the population.

Table 4.4

Distribution of respondents among the provinces

Organization/Province No. of %age of Sample 25%

Employees Employees proportion Sample

Habib Bank Limited

Punjab 6,867 16 1,098 275

Sindh 2,196 05 110 28

Bluchistan 324 01 04 01

Khyber Pakhtoonkhwah 1,683 04 67 17

Federal 1,746 04 70 18

Pakistan Telecommunication

Company Limited

Punjab 9,265 22 2,038 510

Sindh 7,550 18 1,359 340

Bluchistan 1,443 04 58 15

Khyber Pakhtoonkhwah 9,360 22 2,059 515

Federal 1,488 04 60 15

Total 41,922 100 6,923 1,734

Source: Annual reports of HBL and PTCL.

4.2.3. Instruments.

One of the common forms of survey research is a cross - sectional design. It

involves the collection of data from a sample drawn from a specified population at a

specific point in time and is particularly useful for exploratory and descriptive researches

(Babbie, 2001). It is commonly used to assess the frequency with which people perform


certain behaviors, or assess the number of people having particular attitudes or beliefs

(Visser et al., 2000). Cross - sectional surveys are also used to assess the relations

between variables (Reis & Judd, 2000).

The instruments used in the present study to assess layoff survivors’ responses are

the same as that of the pilot study. Minor changes have been introduced in terms of

making the language simple and understandable in the light of discussion made in the

presence of ten PhD doctors.

4.2.4. Data collection

For the present study the researcher gathered data from the layoff survivors

through structured questionnaire. One of the popular forms of survey research is cross -

sectional design and is used to collect data from a sample drawn from a specified

population at a specific point in time. Moreover it is considered useful for exploratory

and descriptive studies (Babbie, 2000). It provides the opportunity to examine the

relationship between variables (Reis & Judd, 2000). The questionnaires were distributed

among 1,734 (25% of the sample population) layoff survivors as per distribution given in

table 4.4. The response rate resulted in 25.9%. Other researchers who have conducted

research studies on layoff survivors reported the response rate as low as 13.0 percent

(Virick et al., 2007), 38.5 percent (Malik, Ahmad, Saif & Safwan, 2010), 26.17 percent

(Farrell & Mavondo, 2005).

4.2.5. Statistical methodology.

The researcher employed Confirmatory Factor Analysis (CFA) and Path Analysis,

Structural Equation Modeling (SEM) to analyze the gathered data to examine the

relationship of the variables and to test the model in a sample of layoff survivors.

A structural equation modeling (SEM) analysis for the current study is undertaken

using the AMOS statistical program, Version 16.0. The researcher selected SEM keeping

in mind the several advantages over regression modeling, such as, SEM offers more

flexible assumptions (particularly allowing interpretation even in the face of multi-co

linearity). It offers use of confirmatory factor analysis to reduce measurement error by

having multiple indicators per latent variable. Better model visualization through its


graphical modeling interface, the desirability of testing models overall rather than

coefficients individually, the ability to test models with multiple dependents, the ability to

model error terms, and the ability to test coefficients across multiple between-subjects

groups are among other advantages of SEM.

4.2.6. Confirmatory factor analysis

The results of the confirmatory factor analysis for each construct are given in this section.

CFA allows researchers to test hypothesis about a specific factor. Factor analysis was

developed in psychometrics. Currently it is used in in behavioral sciences, social

sciences, marketing, product management, operations research, and other applied

sciences. It helps in dealing with large quantities of data.

Confirmatory Factor Analysis pursues to determine if the number of factors and

the loadings of measured (indicator) variables on them conform to what is expected on

the basis of pre-established theory. Indicator variables are selected on the basis of prior

theory and factor analysis is used to see if they load as predicted on the expected number

of factors. The researcher's a priori assumption is that each factor (the number and labels

of which may be specified a priori) is associated with a specified subset of indicator

variables. A minimum requirement of confirmatory factor analysis is that the researcher

hypothesizes beforehand the number of factors in the model, but usually also the

researcher will posit expectations about which variables will load on which factors. The

researcher seeks to determine, for instance, if measures created to represent a latent

variable really belong together.

Chinna (2009) suggests that the confirmatory factor model is carried out to check

construct validity by employing the maximum likelihood method. The confirmatory

factor analysis (CFA) technique is based on the comparison of variance - co - variance

matrix obtained from the sample to the one obtained from the model.

http://en.wikipedia.org/wiki/Psychometrics

http://en.wikipedia.org/wiki/Social_sciences

http://en.wikipedia.org/wiki/Social_sciences

http://en.wikipedia.org/wiki/Marketing

http://en.wikipedia.org/wiki/Product_management

http://en.wikipedia.org/wiki/Operations_research

http://en.wikipedia.org/wiki/Data

http://en.wikipedia.org/wiki/Indicator_variable

http://en.wikipedia.org/wiki/Indicator_variable


Confirmatory Factor Analysis for Perceived Workload Increase Construct- Single factor

.88

W L I

WLI8WLI7WLI6WLI5WLI4WLI3WLI2WLI1.75.821.00

.58

e8.52

e7.34

e6.57

e4.28

e3.59

e2.33

e1.66

e511111 11 1

.88.96.84.85.96

Figure 4.1 show single factor analysis for layoff survivors’ perceived workload increase.

Layoff survivors’ perceived workload increase (WLI) is assessed by using eight

items (WLI1 – WLI8) and based on results of the CFA (see Figure 4.1), WLI constructs

indicate a good fit with χ2 statistic of 21.380 (degrees of freedom = 20, p = 0.375 which

is p > 0.001), with the χ2/df ratio having a value of 1.069 that is less than 3.0. Joreskog

and Sorbom (1993) suggested that it should be between 0 and 3 with smaller values

indicating better fit. The goodness of fit index (GFI) is 0.989, adjusted goodness of fit

index (AGFI) is 0.979, comparative fit index (CFI) is 0.997, and Tucker-Lewis

coefficient (TLI) is 0.996. These scores are very close to 1.0 where a value of 1.0

indicates perfect fit (Bentler, 1992). The next set of fit statistics focus on the root mean

square error of approximation (RMSEA) which is 0.012. Browne and Cudeck (1993)

proposed that values lower than 0.08 indicates good fit, and values higher than 0.08

represent reasonable errors of approximation in the population.

With regard to factor loadings, maximum standardized coefficient estimates are

positive. These are considered good when are above the acceptable level of 0.30 (greater

than 0.30 shows non satisfactory convergent validity) with p - value < 0.001.

R-squared value (0.33, 0.59, 0.28, 0.57, 0.66, 0.34, 0.52 and 0.58) indicates the

percentage of variation in each indicator (WLI1, WLI2, WLI3, WLI4, WLI5, WLI6,

WLI7 and WLI8), that is explained by the factor WLI. From this result, it is noted that

WLI4 presents the best indicator for this construct which is 0.66 followed by WLI7 with

the value of 0.59, and lowest indicator is WLI6 (0.28).


Confirmatory Factor Analysis for Role Overload Construct- Single factor

.88

R O

RO1 RO2 RO3 RO4 RO5 RO6 RO7 RO8 RO9 RO10 RO11 RO12 RO13

.29e11

.58e21

.72e31

.28e41

.64e51

.66e61

.56e71

.33e81

.30e91

.61e101

.34e111

.55e121

.55e131

.77 .72 .92 .81 .79.82 .98 .97 .831.00 .95 .92 .83

Figure 4.2. Shows single factor analysis for layoff survivors’ role overload.

Role Overload of layoff survivors (RO) is measured by thirteen items and the

results of CFA (see Figure 4.2), RO constructs indicate a good fit with χ2 statistic of

56.389 (degrees of freedom = 65, p = 0.768 which is p > 0.001), with the χ2/df ratio

having value of 0.867. The goodness of fit index (GFI) is 0.981, adjusted goodness of fit

index (AGFI) is 0.973, comparative fit index (CFI) is 0.952, and Tucker-Lewis

coefficient (TLI) is 0.954. The scores closer to 1.0 are good fit indicators where a value

of 1.0 indicates perfect fit. The root mean square error of approximation (RMSEA) is

0.000, the value less than 0.08 indicates good fit.

By looking at factor loadings, maximum standardized coefficient estimates are

positive. These are considered good if they are above the acceptable level of 0.30, with p-

value < 0.001.

R-squared value (0.29, 0.58, 0.72, 0.28, 0.64, 0.66, 0.56, 0.33, 0.30, 0.61, 0.34,

0.55 and 0.55) indicates the percentage of variation in each indicator (RO1, RO2, RO3,

RO4, RO5, RO6, RO7, RO8, RO9, RO10, RO11, RO12 and RO13), that is explained by

the factor RO. The results show that RO3 (0.72) presents the best indicator followed by

RO6 (0.68), and lowest indicator is RO4 (0.28). The items having highest values

represent the “I need more hours in the day to do all the things which are expected of me”

and “There are times when I cannot meet everyone’s expectations.” as the best indicators


for layoff survivors role overload. Therefore, these thirteen items can measure the

construct “layoff survivors’ role overload (RO)”.

Confirmatory Factor Analysis for Work - Life Balance Construct- Single factor

.84

W L B

WLB1 WLB2 WLB3 WLB4 WLB5

.31

e11

.55

e21

.31

e31

.49

e41

.27

e51

1.00 .86 .80 .95.95

Figure 4.3. Shows single factor analysis for work life balance.

Work - life balance (WLB) is presented by five items. The results of CFA show

that (see Figure 4.3), WLB constructs indicate an excellent fit with χ2 statistic of 1.446

(degrees of freedom = 05, p = 0.919 which is p > 0.001), with the χ2/df ratio having a

value of 0.289. The goodness of fit index (GFI) is 0.979, adjusted goodness of fit index

(AGFI) is 0.976, comparative fit index (CFI) is 0.966, and Tucker-Lewis coefficient

(TLI) is 0.967. The scores show good fit indicators. The root mean square error of

approximation (RMSEA) is 0.000, the value less than 0.08 indicates good fit.


positive (1.000, 0.865, 0.951, 0.797 and 0.951). The values above 0.30 are considered

good, with p-value < 0.001.

R-squared value (0.31, 0.55, 0.31, 0.49, and 0.27) indicates the percentage of

variation in each indicator (WLB1, WLB2, WLB3, WLB4 and WLB5), that is explained

by the factor WLB. The results show that WLB2 (0.55) presents the best indicator

followed by WLB4 (0.49), and lowest indicator is WLB5 (0.27). The items having

highest values represent the “I have sufficient time away from my job at my organization

to maintain adequate work and personal/family life balance” and “I always feel drained

when I go home from work because of work pressures and problems” as the best


indicators for layoff survivors work life balance. Therefore, these five items can measure

the construct “work life balance (WLB)”.

Confirmatory Factor Analysis for Life Satisfaction Construct- Single factor

.83

L S

LS1 LS2 LS3 LS4 LS5

.29e11

.33e21

.50e31

.25e41

.62e51

.99 .78 .90 .811.00

Figure 4.4. Shows single factor analysis for life satisfaction.

Layoff survivors’ life satisfaction (LS) is presented by five items (LS1 – LS5).

The results of CFA show that (see Figure 4.4), LS constructs indicate an excellent fit with

χ2 statistic of 3.480 (degrees of freedom = 05, p = 0.626 which is p > 0.001), with the

χ2/df ratio having a value of 0.696. The goodness of fit index (GFI) is 0.997, adjusted

goodness of fit index (AGFI) is 0.991, comparative fit index (CFI) is 0.966, and Tucker-

Lewis coefficient (TLI) is 0.965. The scores closer to 1.0 are good fit indicators. The root

mean square error of approximation (RMSEA) is 0.000, the value less than 0.08 indicates

good fit.


positive. The values above 0.30 are considered good, with p-value < 0.001.

R-squared value (0.29, 0.33, 0.50, 0.25, and 0.62) indicates the percentage of

variation in each indicator (LS1, LS2, LS3, LS4 and LS5), that is explained by the factor

life satisfaction (LS). The results show that LS5 (0.62) presents the best indicator

followed by LS3 (0.50), and lowest indicator is LS4 (0.25). The items having highest

values represent the “If I have another chance in life, I will change nothing” and “I am

satisfied with my Life” as the best indicators for layoff survivors life satisfaction.


Therefore, these five items can measure the construct “layoff survivors’ life satisfaction

(LS)”.

Confirmatory Factor Analysis for Job Satisfaction Construct- Single factor

.86

J S

JS4 JS5 JS6 JS7 JS8 JS9JS10JS11JS12JS13JS14JS15JS16JS17JS18JS19

JS20

JS3JS2

JS1

.35e11

.58e21

.30e31

.58e41

.65e51

.34e61

.52e71

.56e81

.58e91

.59e101

.72e111

.27e121

.63e131

.65e141

.57e151

.33e161

.31e171

.62e181 .34

e191 .56e201.84 .97 .77 .87 .79.77 .73 .94 .83 .80 .83.99 .98 .84

.97.931.00

.85.96.89

Figure 4.5. Shows single factor analysis for layoff survivors’ job satisfaction.

Layoff survivors’ job satisfaction (JS) is presented by twenty items (JS1 – JS20).

The results of CFA show that (see Figure 4.5), JS constructs indicate not really a good fit

with χ2 statistic of 87.735 (degrees of freedom = 70, p = 0.167 which is p > 0.001), with

the χ2/df ratio having a value of 1.253. The goodness of fit index (GFI) is 0.967,

adjusted goodness of fit index (AGFI) is 0.959, comparative fit index (CFI) is 0.987, and

Tucker-Lewis coefficient (TLI) is 0.986, which show a good model fit. The root mean

square error of approximation (RMSEA) is 0.000, the value less than 0.08 indicates good

fit.

By looking at factor loadings, standardized coefficient estimates are positive. The

values above 0.30 are considered good, with p-value < 0.001.

R-squared value (0.35, 0.58, 0.30, 0.58, 0.65, 0.34, 0.52, 0.56, 0.58, 0.59, 0.72,

0.27, 0.63, 0.65, 0.57, 0.33, 0.31, 0.62, 0.34 and 0.56) indicates the percentage of

variation in each indicator (JS1 through JS20), that is explained by the factor job

satisfaction (JS). The results show that JS11 (0.72) presents the best indicator followed

by JS5 (0.65) and JS14 (0.65), and lowest indicators are JS12 (0.27) and JS3 (0.30). The

items having highest values represent the “Satisfaction with the chance to do something

that makes use of my abilities”, “Satisfaction with the way my boss handles his/her


workers” and “ Satisfaction with the chances for advancement on this job” as the best

indicators for layoff survivors job satisfaction. The items having lower ratings are

“Satisfaction with the way company policies are put into practice” and “Satisfaction with

the chance to do different things from time to time”.

Confirmatory Factor Analysis for Employee Retention Construct- Single factor

.85

E R

ER4ER3ER2ER1

.751.00

.26

e11

.34

e21

.34

e31

.55

e41

.93.99

Figure 4.6. Shows single factor analysis for employee retention.

Employee retention (ER) is presented by four items (ER1 – ER4). The results of

CFA show that (see Figure 4.6), ER constructs indicate an excellent fit with χ2 statistic of

2.802 (degrees of freedom = 02, p = 0.246 which is p > 0.001), with the χ2/df ratio

having a value of 1.401. The goodness of fit index (GFI) is 0.977, adjusted goodness of

fit index (AGFI) is 0.975, comparative fit index (CFI) is 0.969, and Tucker-Lewis

coefficient (TLI) is 0.968. These scores are closer to 1.0 and show a good fit. The root

mean square error of approximation (RMSEA) is 0.030, the value less than 0.08 indicates

good fit.


positive (1.000, 0.995, 0.928 and 0.752). The values above 0.30 are considered good,

with p < 0.001.

R-squared value (0.26, 0.34, 0.34 and 0.55) indicates the percentage of variation

in each indicator (ER1, ER2, ER3 and ER4), that is explained by the factor employee

retention (ER). The results show that ER4 (0.55) presents the best indicator followed by


ER2 (0.34) and ER3 (0.34), and lowest indicator is ER1 (0.26). The items having highest

values represent the “I would hate to quit this job”, “I will most probably look for a new

job in the near future” and “I plan to stay in this job for at least two to three years” as the

best indicators for layoff survivors’ retention in the same organization. Therefore, these

four items can measure the construct “layoff survivors’ retention in the organization

(ER)”.

Confirmatory Factor Analysis for Organizational Commitment Construct- Single factor

.70

O C

OC2 OC3OC4 OC5OC6OC7 OC8 OC9OC10OC11OC12OC13OC14OC15OC16OC17OC18OC1

.53e11

.47e21

.48e31

.49e41

.62e51

.67e71

.45e61

.66e81

.60e91

.61e101

.62e111

.60e121

.57e131

.55e141

.42e151

.65e161

.57e171

.63e181

.83 .87 .89 .85 .53 .65.54 .59 .92 .60 .67 .85 .86.941.00 .95.92.81

Figure 4.7. Shows single factor analysis for organizational commitment.

Organizational commitment (OC) is presented by eighteen items (OC1 – OC18).

The results of CFA show that (see Figure 4.7), OC constructs indicate not really good fit

with χ2 statistic of 143.210 (degrees of freedom = 135, p = 0.298 which is p > 0.001),

with the χ2/df ratio having a value of 1.061. The goodness of fit index (GFI) is 0.939,

adjusted goodness of fit index (AGFI) is 0.923, comparative fit index (CFI) is 0.970, and

Tucker-Lewis coefficient (TLI) is 0.966. The scores closer to 1.0 are good fit indicators

where a value of 1.0 indicates perfect fit. The root mean square error of approximation

(RMSEA) is 0.042, the value less than 0.08 indicates good fit.


positive. The values above 0.30 are considered good, with p-value < 0.001. The

researcher decided to remove the items having negative values.

R-squared value (0.53, 0.47, 0.48, 0.49, 0.62, 0.45, 0.67, 0.66, 0.60, 0.61, 0.62,

0.60, 0.57, 0.55, 0.42, 0.65, 0.57 and 0.63) indicates the percentage of variation in each


indicator (OC1 through OC18), that is explained by the factor organizational commitment

(OC). The results show that OC7 (0.67) presents the best indicator followed by OC8

(0.66) and OC16 (0.65), and lowest indicator is OC15 (0.42). The items having highest

values represent the “At present, staying with my organization is a matter of necessity as

much as desire.”, “It would be very hard for me to leave my organization right now, even

if I want to.” and “This organization deserves my loyalty.” as the best indicators for

layoff survivors’ organizational commitment. Therefore, all these items can measure the

construct “layoff survivors’ organizational commitment (OC)”.

Confirmatory Factor Analysis for Employee Productivity Construct- Single factor

.88

E P

EP4 EP5 EP6 EP7 EP8 EP9 EP10EP11EP12EP13EP14EP15EP16EP17EP18EP19

EP3EP2EP1

1.00.87 1.04.98 .98 1.01.92 1.08 1.01.92 .86 .84 .911.08.66 .931.00.63

.99

.32e11

.35e21

.55e31

.30e41

.33e51

.28e61

.32e71

.25e81

.32e91

.27e101

.46e111

.44e121

.47e141

.44e131

.32e151

.56e161

.29e171

.29e181 .54

e191

Figure 4.8. Shows single factor analysis for employee productivity.

Employee productivity (EP) is presented by nineteen items (EP1 – EP19). The

results of CFA show that (see Figure 4.8), EP constructs indicate not really good fit with

χ2 statistic of 220.132 (degrees of freedom = 152, p = 0.000 which is p < 0.001), with the

χ2/df ratio having a value of 1.448.

However, the goodness of fit index (GFI) is 0.951, adjusted goodness of fit index (AGFI)

is 0.938, comparative fit index (CFI) is 0.992, and Tucker-Lewis coefficient (TLI) is

0.991. The scores closer to 1.0 are good fit indicators where a value of 1.0 indicates

perfect fit. The root mean square error of approximation (RMSEA) is 0.032, the value

less than 0.08 indicates good fit.


positive for items but there are few having values more than one such as, EP4, EP7, EP9,

EP10, EP15 and EP18. The values greater than one show that the cases are “Heywood” in


nature. The “Heywood cases” are the correlations estimated to be greater than one and

variances, less than zero. It appears that maximum likelihood estimation methods seem to

be particularly prone to producing Heywood cases (Boomsma & Hoogland 2001)

whereas the values above 0.30 are considered good, with p-value < 0.001.Given less

usefulness of Heywood cases, it was decided to remove these from the questionnaire.

Although there is no general consensus on the treatment of Heywood cases in

SEM literature. One of the ways to treat these cases is to “ignore the problem”

(Kolenikov, Bollen & Savalei, 2006). Few of the causes of Heywood cases include the

extreme observations that are the outliers (Bollen, 1987), non – convergence and under-

identification (Boomsma & Hoogland, 2001), empirical under-identification (Rindskopf,

1984) and sampling fluctuations (Anderson & Gerbing, 1984).

After removing the Heywood cases the results of the CFA indicate that (see

Figure 4.9) EP constructs indicate comparatively a good fit with χ2 statistic of 87.385

(degrees of freedom = 65, p = 0.034 which is p > 0.001), with the χ2/df ratio having a

value of 1.344.

The goodness of fit index (GFI) is 0.970, adjusted goodness of fit index (AGFI) is

0.958, comparative fit index (CFI) is 0.995, and Tucker-Lewis coefficient (TLI) is 0.994.

The scores closer to 1.0 are good fit indicators where a value of 1.0 indicates perfect fit.

The root mean square error of approximation (RMSEA) is 0.028, the value less than 0.08

indicates good fit.

.88

E P

EP3 EP5 EP6 EP8 EP11 EP12EP13EP14 EP16EP17 EP19EP1 EP2

.32e11

.35e21

.54e31

.32e51

.28e61

.24e81

.46e111

.45e121

.46e131

.46e141

.54e161

.29e171

.53e191

.98.881.00 .98 .93 .91.86 .83 .92 .67 .94 .64.99

Figure 4.9. Shows single factor analysis for employee productivity after removal of

items.


R-squared value (0.32, 0.33, 0.54, 0.32, 0.28, 0.24, 0.46, 0.45, 0.46, 0.48, 0.54,

0.29 and 0.53) indicates the percentage of variation in each indicator that is explained by

the factor employee productivity (EP). The results show that EP3 (0.54) and EP16 (0.54)

presents the best indicator followed by EP11 (0.46), EP13 (0.46) and EP14 (0.46), and

lowest indicator is EP8 (0.24). The items having highest values represent the “My job

allows me to plan how I do my work.”, “I efficiently handle the workload” and therefore,

all these items can measure the construct “layoff survivors’ productivity (EP)”.

The results of confirmatory factor analysis provide support for the questionnaire

comprising these items can be used for final data collection from the layoff survivors.

The analysis based on the data collected from the layoff survivors and by using the same

questionnaire is presented in the next chapter.


Chapter 5

Analysis and results

Demographics and organizational profile of the respondents

Normality and reliability Measurements

Confirmatory Factor Analysis (CFA)

Structural Equation Modeling (SEM)

Independent Sample t – test (difference HBL & PTCL)


Chapter 5

Analysis and Results

The results are based on the responses retrieved from layoff survivors from the two

organizations operating in Pakistan. The organizations had adopted the policy of

restructuring resulting in the emergence of layoff survivors.

5.1. Demographics and organizational profile of the respondents.

Table 5.1

Demographic and organizational profile of respondents

Variable Category Frequency Percentage

Organization HBL 255 56.7

PTCL 195 43.3

Gender Male 379 84.2

Female 71 15.8

Age 20 – 29 years 60 13.3

30 – 39 years 222 49.3

40 – 49 years 141 31.3

50 – 59 years 27 06.0

Education Matriculation 02 00.4

Higher Secondary 35 07.8

Graduation 123 27.3

Masters 277 61.6

Doctorate 03 00.7

Others 10 02.2

Job Status Top Mgt. 91 20.2

Middle Mgt. 241 53.6

First Level Mgt. 114 25.3

Others 04 00.9

Source: Results from the main study.

Table 5.1 summarizes the demographic and organizational profile of the respondents

The respondent ages range from 20 to 59 years. The respondents from Habib Bank

Limited (56.7%) took more interest in responding to the questionnaire as compared to the

layoff survivors of Pakistan Telecommunication Company Limited. Majority of the

respondents are male (84.2%) and are Masters degree holders (61.6%) and working at


middle level management (53.6%). Other demographic information related to

respondents can be seen from table 5.1.

5.2. Normality and Reliability Measurements

Normality and reliability tests are employed keeping in mind the prerequisites for the

factor analysis and Path Analysis, SEM. Uni - variate outliers are detected by using SPSS

15.0. All the variables are converted into standardized scores for detection of outliers.

The skewness and kurtosis statistics for all variables stand well with in the

acceptable range of +2. The results of the skewness and kurtosis confirm the symmetry of

the sample distribution (SPSS Inc., 1998). This can be seen from table 5.2 below.

Table 5.2

Uni - Variate Statistic for Shape of Distribution

Construct/ Variables Skewness Kurtosis

Perceived workload increase -1.960 1.656

Role overload -1.872 1.556

Work life balance 1.033 1.074

Job satisfaction 1.164 1.240

Life satisfaction 1.985 1.860

Employee retention 1.959 1.705

Organizational commitment 1.080 1.012

Employee productivity 1.230 1.352

Source: Results from main study.

The researcher re-confirmed the reliabilities of the measures used by examining

Chronbach’s alpha coefficients and Guttman Split- Half coefficients. Table 5.3 shows the

reliability coefficients. Cronbach’s alpha is a test reliability technique that requires only a

single test administration to provide a unique estimate of the reliability for a given test.

Cronbach’s alpha is the average value of the reliability coefficients one could obtain for

all possible combinations of items when split into two half-tests. Cronbach’s alpha

reliability coefficient normally ranges between 0 and 1. However, there is actually no

lower limit to the coefficient. The closer Cronbach’s alpha coefficient is to 1.0 the greater

the internal consistency of the items in the scale (Gliem & Gliem, 2003). George and

Mallery (2003) provide the following rules of thumb: “_ > .9 – Excellent, _ > .8 – Good,

_ > .7 – Acceptable, _ > .6 – Questionable, _ > .5 – Poor, and _ < .5 – Unacceptable” (p.

231).


When using Likert - type scales it is imperative to calculate and report Cronbach’s

alpha coefficient for internal consistency reliability for any scales or subscales one may

be using. The analysis of the data then must use these summated scales or subscales and

not individual items. If one does otherwise, the reliability of the items is at best probably

low and at worst unknown. Cronbach’s alpha does not provide reliability estimates for

single items.

Keeping in view the above mentioned rule of thumb for Cronbach’s alpha

coefficients it is clear that all the scales included in the current study meets the minimum

criteria to be acceptable.

Table 5.3

Reliability Statistics of Scales

Constructs/ Number of Chronbach’s Alpha Guttman Split- Half

Variables Items Coefficients Coefficient

Workload Increase 08 0.82 0.83

Role Overload 13 0.95 0.95

Work Life balance 05 0.72 0.76

Job Satisfaction 20 0.70 0.64

Life Satisfaction 05 0.86 0.85

Employee Retention 04 0.86 0.77

Organizational Commitment 18 0.85 0.83

AOC 06 0.88 0.87

COC 06 0.72 0.73

NOC 06 0.70 0.69

Employee Productivity 13 0.86 0.81

AUTO 06 0.74 0.62

TIME 04 0.77 0.63

EFCY 03 0.84 0.84

Source: Data from main study.

5.3. Confirmatory Factor Analysis (CFA)

Confirmatory Factor Analysis tests whether measures of a construct are consistent with a

researcher’s understanding of the nature of that construct (or factor) or not. As compared

to exploratory factor analysis, where all loadings are free to vary, CFA allows for the

explicit constraint of certain loadings to be zero.

CFA is also used while keeping in mind as a first step to assess the proposed

measurement model in a Structural Equation Model. Many of the rules of interpretation


regarding assessment of model fit and model modification in Structural Equation

Modeling apply equally to CFA. CFA is distinguished from Structural Equation

Modeling by the fact that in CFA, there are no directed arrows between latent factors. In

the context of SEM the CFA often is called 'the measurement model', while the relations

between the latent variables (with directed arrows) are called 'the structural model'

(Asparouhov & Muthén, 2009; Brown, 2006).

Before employing SEM, a confirmatory factor analysis is used to assess the

soundness of the measurement properties of the conceptual model using “fit” statistics

calculated from comparing its factor structure with sample data. The researchers who

have used SEM in their research studies (Chinna, 2009; Zakuan, Yusof, Saman, &

Shaharoun, 2010) also carried out CFA before applying SEM. On the confirmation of the

model fit the researcher may go for testing a structural model. The confirmatory factor

model is needed to confirm construct validity by using the Maximum Likelihood Method.

The Maximum Likelihood Method, also known as Maximum Likelihood Estimation is a

standard approach to parameter estimation and inference in statistics (Myung, 2003). It is

the method that finds the most likely value for the parameter based on the data set

collected and is used for fitting a statistical model to data and providing estimates for the

parameters included in the model.

Confirmatory factor analysis (CFA) undertakes the comparison of variance-

covariance matrix obtained from the sample to the one obtained from the model (Zakuan,

et al., 2010).

The problematic items are removed parsimoniously to prevent any substantial

threat to the content validity of a latent factor (Kelloway, 1995). The present study thus

makes an effort to balance increased model fit and content validity. The results of CFA

are summarized in table 5.4.

http://en.wikipedia.org/wiki/Structural_Equation_Modeling

http://en.wikipedia.org/wiki/Structural_Equation_Modeling


Table 5.4

Summary of the factor analysis and model fit is given below

Variable χ2 χ2/df p GFI AGFI CFI TLI RMSEA

Ratio value

WLI 21.380 1.06 0.375 0.969 0.979 0.987 0.996 0.012

RO 56.389 0.86 0.768 0.981 0.973 0.952 0.954 0.000

WLB 1.446 0.28 0.919 0.979 0.976 0.966 0.967 0.000

JS 87.735 1.25 0.167 0.967 0.959 0.987 0.986 0.000

LS 3.480 0.69 0.626 0.957 0.961 0.956 0.955 0.000

ER 2.802 1.40 0.246 0.968 0.975 0.969 0.968 0.030

OC 143.210 1.06 0.298 0.939 0.923 0.970 0.966 0.042

EP 87.385 1.34 0.034 0.970 0.958 0.965 0.974 0.028

Source: Results from the main study.

The results of CFA are discussed in detail in chapter 4, section 4.2.6. All the variables

included in the model have positive factor loadings and meet the required criteria for the

model fitness to be considered for further analysis. The scores of GFI, AGFI, CFI, TLI

closer to one presents a good fit for the model. The CFA conducted for the current study

meets the required criteria.

5.4. Structure Equation Modeling (SEM)

Structural equation models are generally used in social, behavioral, and biological

sciences (Kolenikov, Bollen, & Savalei, 2006). Structural Equation Model is an efficient

and convenient analytical method that has improved upon, and superseded, other tools of

analysis such as multiple and multivariate regression, or recursive path analysis.

Multivariate regression has a number of limitations mainly including it does not allow

researcher to explore any relationships amongst the dependent variables, nor easily

distinguishes between latent and observed variables. It also assumes that the indicators

are measures without error and in the formation of the composite using unit weights. It

also assumes that each indicator contributes equally to the composite (Holme - Smith,

1999).

SEM is helpful in overcoming all the problems mentioned above. The main aim

of the SEM is to estimate relationships among dependent variables, with co - variances as

the main statistic, and explain the patterns among latent constructs. Latent constructs are

the factors defining the observed variable (Reisinger & Turner, 2000). The SEM can


differentiate between latent and observed variables. It can also estimate the nature of

measurement error associated with the observed variables and also allows unequal

weightings for the multiple indicators of a latent construct (Holmes - Smith, 1999).

While in the case of exploratory and confirmatory factor analysis models, for

example, contain only the measurement part, while path diagrams can be viewed as an

SEM that only has the structural part.

SEM is based on two important approaches. Firstly, it considers the causal

processes under study and represents it by a series of structural (regression) equations

that indicates the strength of the relationships between constructs. Secondly, it tests the

global plausibility of a proposed model (Kline, 1998), the structural relations can be

modeled pictorially, using diagrammatic views and directional arrows, to show a clear

conceptualization of the theories under consideration (Byrne, 2001). The researcher test

the hypothesis by examining the standard regression weights that provide estimates of the

bivariate relationship after controlling for all other variables thus provide a clear picture

of the relationship (Virick et al., 2007).

The major concepts in the application and evaluation of SEM techniques are

discussed below.

Before applying SEM let us consider the assumptions first.

Adequate sample size (200 is commonly accepted as sufficient).

Data level. Interval data are assumed by default. If ordinal data are used, the

researcher must use appropriate methods (ex., Bayesian estimation in AMOS,

poly-choric correlation in LISREL), or justify the metricity of ordinal measures

(as through multidimensional scaling, showing similar results for ordinal and

metric treatment of ordinal variables). It must be acknowledged, however, that

some publishers apply more lenient standards and accept use of ordinal variables

treated as interval in SEM, just as they do in regression procedures.

Multivariate normality. As a rule of thumb, data may be assumed to be normal if

skew and kurtosis is within the range of +/- 1.0 (some say +/- 1.5 or even 2.0)

(Schumacker & Lomax, 2004: 69).


Missing values should be reported as absent, otherwise the method of data

imputation should be discussed, or alternatively, the possible bias due to dropping

cases with missing values should be analyzed.

Outliers should be discussed along with the implications for their inclusion or

exclusion.

Estimation. Type of estimation method selected should be justified, especially if it

is not the default (maximum likelihood). For instance, lack of multivariate

normality may lead the researcher to use weighted least squares.

Software. Mention which computer program was used to compute estimates.

5.4.1. Survey related new terms

The structural equation modeling process

It comprises of two steps that are, validating the measurement model and fitting the

structural model. The validation of the measures is accomplished mainly through

confirmatory factor analysis, while for examining the fitness of the structural model path

analysis is used with latent variables. One has to create a model on the basis of theory.

Every variable in the model is considered as a latent one which is measured through

multiple indicators. Numerous indicators are developed for each model, with a view to

winding up with at least two and preferably three per latent variable after confirmatory

factor analysis. Based on adequate representative sample, generally more than hundred

observations, factor analysis (common factor analysis or principal axis factoring, not

principle components analysis) is used to establish that indicators seem to measure the

corresponding latent variables, represented by the factors. The researcher proceeds only

when the measurement model has been validated. Two or more alternative models (one

of which may be the null model) are then compared in terms of "model fit," which

measures the extent to which the co-variances predicted by the model correspond to the

observed co-variances in the data. "Modification indexes" and other coefficients may be

used by the researcher to alter one or more models to improve fit.


Latent variables

These are the unobserved variables or factors or constructs which are measured by

means of their respective indicators. Latent variables include dependent, mediating, and

independent variables.

Exogenous variables

These are generally known as independents with no prior causal variable (though

they may be correlated with other exogenous variables), portrayed by a double-headed

arrow. In fact it is customary to assume that exogenous variables are correlated

(connected by a double-headed covariance arrow) unless there is theoretical reason for

not doing so. If two exogenous variables are joined by a covariance arrow, there cannot

also be a straight (regression path) arrow, nor can one have a covariance arrow

connecting an exogenous variable to an endogenous variable. Exogenous constructs are

sometimes denoted by the Greek letter ksi.

Endogenous variables

These are known as mediating variables (variables which are both effects of other

exogenous or mediating variables, and are causes of other mediating and dependent

variables), and pure dependent variables. Endogenous variables are on the receiving end

of single-headed straight arrows indicating a regression path and implying a causal

relationship. The path to the endogenous variable may come from an exogenous variable

or another endogenous variable. Endogenous constructs are sometimes denoted by the

Greek letter eta. Variables in a model may be "upstream" or "downstream" depending on

whether they are being considered as causes or effects respectively. The representation of

latent variables based on their relation to observed indicator variables is one of the

differentiating qualities of SEM.

Goodness of fit test

This determines whether the model being tested should be accepted or rejected.

These overall fit tests do not establish that particular paths within the model are

significant. If the model is accepted, the researcher will then go on to interpret the path


coefficients in the model ("significant" path coefficients in poor fit models are not

meaningful). AMOS offers 25 alternate goodness-of-fit measures. There is no consensus

on choosing goodness-of-fit measures among methodologists. Jaccard and Wan (1996:

87) recommend use of at least three fit tests, one from each of the first three categories

below, so as to reflect diverse criteria. Kline (1998a: 130) suggested at least four

goodness-of-fit measures including, chi-square; GFI, NFI, or CFI; NNFI; and SRMR.

There is difference of opinion among methodologists on just which fit indexes to report

but all have agreed on not considering all of them.

Model chi-square

It is also known as chi-square fit index, discrepancy, likelihood ratio chi-square,

chi-square goodness of fit, discrepancy function, or simply chi-square. It is the universal

fit test, offered by all computer programs. Model chi-square considers large samples.

AMOS represents model chi-square as CMIN. The chi-square value should be non -

significant if there is a good model fit, as in the illustration below. A significant chi-

square highlights deficiency of satisfactory model fit. That is, chi-square is a "badness of

fit" measure in that a finding of significance means the given model's covariance

structure is significantly different from the observed covariance matrix. If model chi-

square < .05 the researcher's model is not accepted by this criterion. However, because

the model chi-square is so conservative (prone to Type II error), researchers may well

discount a negative model chi-square finding if other model fit measures support the

model. Fit means the ability of a model to replicate the data (i.e., usually the variance-

covariance matrix) (Bollen & Long, 1993).

Goodness-of-fit index (GFI) ranges from 0 to 1 but theoretically can yield

meaningless negative values. A large sample size drives GFI up. It is the percent of

observed co-variances explained by the co-variances implied by the model. Usually, GFI

should be equal to or greater than (.90) for the acceptable model. As GFI often runs high

compared to other fit models, the authors (Schumacker & Lomax, 2004: 82) suggest

using (.95) as the cutoff. The goodness of fit index (GFI), tells about what proportion of

the variance in the sample variance-covariance matrix is accounted for by the model and

should be more than (.90) for a good model (Ingram, Cope, Harju, & Wuensch, 2000).


The comparative fit index (CFI) matches the covariance matrix calculated by the

model to the observed covariance matrix, and compares the null model (covariance

matrix of 0's) with the observed covariance matrix, to estimate the percent of deficiency

of fit which is accounted for by going from the null model to the researcher's SEM

model. CFI and RMSEA are the measures which are least affected by sample size (Fan,

Thompson, and Wang, 1999). CFI fluctuates from 0 to 1 (if outside this range it is reset to

0 or 1). CFI near to 1 indicates a very good fit. CFI is also used in testing modifier

variables (those which create a hetero-scedastic relation between an independent and a

dependent, such that the relationship varies by class of the modifier).

Conventionally CFI equal to or greater than (.90) is advisable to accept the model,

showing that 90% of the co-variation in the data can be reproduced by the given model.

CFI indices compare ones model to the independence model rather than to the saturated

model. The Comparative Fit Index (CFI) is said to be a good index for use even with

small samples. It ranges from 0 to 1, and (.95) or (.90) or higher indicates good fit

(Ingram, Cope, Harju, & Wuensch, 2000). It depends on the average size of the

correlations in the data. If the average correlation between variables is not high, then the

CFI will not be very high (Bollen & Long, 1993). Schumacker & Lomax (2004) reported

that CFI and GFI are considered good if these are greater than .95.

Cheung & Rensvold (2002) examined 20 goodness of fit measures for use when

testing for measurement invariance across multiple groups and recommended the use of

CFI, NCP and GFI, measures being independent of model complexity and sample size

and are un-correlated with model chi-square.

The values of the goodness fit index (GFI) , adjusted goodness of fit index

(AGFI), comparative fit index (CFI), and Tucker-Lewis coefficient (TLI) closer to 1.0

shows a good fit where as, a value of 1.0 specifies ideal fit (Bentler, 1992; Zakuan, et al.,

2010).

Critical ratio

Critical ratios are parameter estimates divided by their corresponding standard

errors. This means that CR > 1.96 indicates a parameter estimate (ex., a regression

coefficient) which is significantly different from 0 at the .05 significance level, if


variables are normally distributed. On this assumption, parameters with CR above more

than 1.96 indicate a significant difference between groups.

Assumptions of using SEM

As a rule of thumb, discrete data (categorical data, ordinal data with < 15 values)

may be assumed to be normal if skew and kurtosis is within the range of +/- 1.0 (some

say +/- 1.5 or even 2.0) (Schumacker & Lomax, 2004).

5.4.2. The analysis

The researcher for the current study, use AMOS (Analysis of MOment Structures)

16.0, to test the proposed model. Amos implements Structural Equation Modeling (SEM)

approach to data analysis which includes the techniques of general linear model and

common factor analysis (Arbuckle, 2007). The error terms (e1 to e8) represent the errors

associated with variables in the model. Figure 5.1 reveals testing of the research model.

The variables included in the model are shown below.


WLI

RO

WLB

JSLS

ER OC

EP

.96

-.88

-.64 -.66

.24 .33.95 .34

.13 .03 .06 .08

.93

e11

.07

e21

.11

e31

.03

e41

.16

e51

.03

e61

.08

e71

.02

e81

Figure 5.1. The results of proposed model tested (SEM/Path Analysis).

WLI Work load increase LS Life satisfaction

RO Role over load OC Organizational commitment

WLB Work life balance ER Employee retention

JS Job satisfaction EP Employee productivity

Figure 5.1 shows the relationship of the variables by using path analysis (structural

equation modeling). The model fitness and other measures used to test the model and

interrelationships of the variables are presented in this section. Table 5.5 shows the model

fitness of the overall model.


Table 5.5

Fit of the Model

Chi – Square p - value GFI AGFI CFI TLI RMSEA

150.472* 0.000 0.928 0.816 0.980 0.961 0.147

*p < 0.05

Table 5.5 shows that the value of chi square (150.472) is significant (p<0.05). The

researcher used measures such as Goodness of Fit Index (GFI), Adjusted Goodness of Fit

Index (AGFI), Comparative Fit Index (CFI) and Root Mean Square Error of

Approximation (RMSEA) to assess fit of the model. Values of GFI (0.928), AGFI

(0.816) and CFI (0.980) are close to 1 which shows the goodness of the model fit

(Zakuan, et al., 2010; Singh-Manoux, Clarke & Marmot, 2002; Sacker, Bartley, Firth &

Fitzpatrick, 2001; Bentler, 1992; Schumacker & Lomax, 2004).

Table 5.6

Hypothesis testing based on Regression Weights

Model Variables β S.E. C.R. p - value Results

Source: Results of path analysis - SEM.

Post layoff perceived workload increase and role overload

Table 5.6 shows that in WLI - RO regression model, the value of regression coefficient

(β = 0.957, 0.000) is significant (p < 0.05) which shows that there is a significant effect of

post layoff perceived workload increase (WLI) on role overload (RO) of layoff survivors.

The hypothesis H1 is therefore accepted. The layoff survivors were expecting some level

RO <--- WLI .957 .013 72.932 0.000 Accept H1

WLB <--- RO -.875 .016 -53.089 0.000 Accept H2

JS <--- RO -.641 .025 -25.940 0.000 Accept H3

LS <--- RO -.658 .036 -18.041 0.000 Accept H4

JS <--- WLB .236 .026 9.012 0.000 Accept H5

LS <--- WLB .331 .039 8.563 0.000 Accept H6

ER <--- WLB .955 .021 46.383 0.000 Accept H7

OC <--- WLB .337 .009 39.109 0.000 Accept H8

EP <--- JS .126 .023 5.395 0.000 Accept H9

EP <--- ER .034 .014 2.461 0.014 Accept H10

EP <--- OC .062 .035 1.763 0.078 Reject H11

EP <--- LS .077 .020 3.887 0.000 Accept H12


of work load increased but in actual it is 95.7% which is near to hundred. It means that

the layoff survivors are facing excessive work load.

Role overload and work - life balance

In RO - WLB regression model, the value of regression coefficient (β = - 0.875, 0.000) is

significant (p < 0.05) which shows that there is a significant negative effect of role

overload (RO) on work - life balance (WLB) of layoff survivors. The hypothesis H2 is

therefore accepted (table 5.6). Layoff survivors experience role overload which has high

negative impact on their ability to balance work and life activities. Its intensity is 87.5

percent which is really high. It shows that their ability to balance their work and life

activities is hampered up to a very extreme.

Role over load and job satisfaction

Table 5.6 shows that in RO - JS regression model, the value of regression coefficient (β =

- 0.641, 0.000) is significant (p < 0.05) which shows that there is a significant negative

effect of role overload (RO) on job satisfaction (JS) of layoff survivors. The hypothesis

H3 is therefore accepted. The results confirm that due to role overload the satisfaction

level of layoff survivors is negatively affected by 64.1 percent. It is clear from the results

that role overload plays a vital role in diminishing layoff survivors’ satisfaction from

work.

Role overload and life satisfaction

In RO - LS regression model, the value of regression coefficient (β = - 0.279, 0.000) is

significant (p < 0.05) which shows that there is a significant negative effect of role

overload (RO) on life satisfaction (LS) of layoff survivors. The hypothesis H4 is therefore

accepted, shown in table 5.6. Similar to the effects that role overload has on layoff

survivors’ job satisfaction it has a negative effect on layoff survivors’ life satisfaction as

well. Although as compared to the previous relationship in the current case its intensity is

low, that is 27.9 percent.


Work - life balance and job satisfaction

In WLB - JS regression model, the value of regression coefficient (β = .236, 0.000) is

significant (p < 0.05) which shows that there is a significant positive effect of work life

balance (WLB) on job satisfaction (JS) of layoff survivors. The hypothesis H5 is therefore

accepted (table 5.6). In contrast to the researchers expectations the intensity of the

perception of work life balance has slightly (23.6 %) effected that job satisfaction of

layoff survivors’ positively. Despite being a resident of a developing country and an

employee of an organization that has undergone layoff in the recent past it is clear from

the results that the layoff survivors’ who believe that they can better manage their work

and life activities are more satisfied from their jobs as compared to others.

Work - life balance and life satisfaction

Table 5.6 shows that in WLB - LS regression model, the value of regression coefficient

(β = .331, 0.000) is significant (p < 0.05) which shows that there is a significant positive

effect of work life balance (WLB) on life satisfaction (LS) of layoff survivors. The

hypothesis H6 is therefore accepted. Again the results confirm that the perception of work

life balance of layoff survivors’ helps them to remain satisfied with their lives up to some

extent that is 33.1 percent.

Work - life balance and employee retention

In WLB - ER regression model, the value of regression coefficient (β = .955, 0.000) is

significant (p < 0.05) which shows that there is a significant positive effect of work life

balance (WLB) on employee retention (ER) of layoff survivors. The hypothesis H7 is

therefore accepted, shown in table 5.6. The layoff survivors who perceive that they are in

a position to balance their work and life affairs are interested to retain their jobs and work

in the same organization. The perception of being balanced has a great impact (95.5 %)

on retention of their jobs in the same organization.

Work - life balance and organizational commitment

Referring to table 5.6 it is evident that in WLB - OC regression model, the value of

regression coefficient (β = .337, 0.000) is significant (p < 0.05) which shows that there is


a significant positive effect of work life balance (WLB) on organizational commitment

(OC) of layoff survivors. The hypothesis H8 is therefore accepted. The results show that

work life balance has a weak positive relationship with layoff survivors’ commitment

with the organization. It is clear that the perception of layoff survivors that they can better

manage their work and life affairs has least impact (33.7%) on their commitment with the

organization. It means that work life balance is weak predictor of layoff survivors’

organizational commitment.

Job satisfaction and employee productivity

On table 5.6 it is shown that in JS - EP regression model, the value of regression

coefficient (β =.126, 0.000) is significant (p < 0.05) which shows that there is a

significant positive effect of job satisfaction (JS) on productivity (EP) of layoff survivors.

The hypothesis H9 is therefore accepted. Unlike the researchers imagination the layoff

survivors’ who are happy with their jobs are least productive. The results show a positive

but very mild (12.6%) relationship of layoff survivors’ job satisfaction and their

productivity. It means that job satisfaction is least responsible for bringing change in the

productivity of layoff survivors in a developing country, Pakistan.

Employee retention and employee productivity

In ER - EP regression model, the value of regression coefficient (β =.034, 0.014) is

significant (p < 0.05) which shows that there is a significant effect of retention (ER) of

layoff survivors with the same organization on productivity (EP). The hypothesis H10 is

therefore accepted (table 5.6). The result of this relationship shows that layoff survivors

are least productive even after retaining their jobs. The result is non significant in nature

and it can be inferred that retention of job does not mean that the employees be

productive while at work. Layoff survivors’ job retention only accounts for 3.4% change

in productivity.

Organizational commitment and employee productivity

In OC - EP regression model, the value of regression coefficient (β =.062, 0.078) is not

significant (p > 0.05) which shows that there is no significant effect of organizational


commitment (OC) of layoff survivors on productivity (EP). The hypothesis H11 is

therefore rejected, presented in table 5.6. The results depict that the commitment of

employees that are layoff survivors has a least concern with their being productive. The

organizational commitment of layoff survivors only accounts for 6.2 percent change in

productivity.

Life satisfaction and employee productivity

In LS - EP regression model, the value of regression coefficient (β =.077, 0.000) is

significant (p < 0.05) which shows that there is a significant positive effect of life

satisfaction (LS) on productivity (EP) of layoff survivors. The hypothesis H12 is therefore

accepted, presented in table 5.6. Layoff survivors who perceive that they are satisfied

with their lives account for only 7.7% change in productivity while at work. It means that

their life satisfaction has very weak effect on their productivity. It is clear that even if

they are satisfied from their life affairs even then they are unable to be productive in an

effective manner.

5.5. Independent sample t - test

The researcher employed the independent sample t – test to examine the differences in

mean scores among layoff survivors of the two organizations with respect to their

perceived workload, role overload, work - life balance, job and life satisfaction,

intentions to remain with the organization, commitment to their organization and

productivity. The results are shown in table 5.7. The results are presented on the basis of

mean scores and the value of significance for the clarity of understanding. The

independent sample t – test is applied on 225 responses from Habib Bank Limited and

195 responses from Pakistan Telecommunication Company Limited, contributing to 450

responses in all.


Table 5.7

Independent sample t – test

Variable Organization N Mean S.D. p - value

WLI HBL 255 3.972 0.837 0.833

PTCL 195 3.920 0.932

RO HBL 255 3.907 0.771 0.928

PTCL 195 3.841 0.845

WLB HBL 255 2.019 0.861 0.003

PTCL 195 3.069 0.607

JS HBL 255 2.208 0.734 0.010

PTCL 195 3.259 0.613

LS HBL 255 2.060 0.848 0.512

PTCL 195 2.112 0.885

ER HBL 255 1.991 0.876 0.601

PTCL 195 2.040 0.928

OC HBL 255 3.178 0.643 0.009

PTCL 195 2.185 0.833

EP HBL 255 1.921 0.899 0.423

PTCL 195 2.003 0.988

Source: Results from the field study.

The results of the independent sample t – test show the differences among layoff

survivors of Habib Bank Limited (HBL) and Pakistan Telecommunication Company

Limited (PTCL) with respect to perceived workload increase (0.833, p > 0.050), role

overload (0.928, p > 0.050), work - life balance (0.003, p < 0.050), job satisfaction

(0.010, p < 0.050), life satisfaction (0.512, p > 0.050), employee retention (0.601, p >

0.050), organizational commitment (0.009, p < 0.050) and productivity (0.423, p >

0.050).

The results indicate that there are no significant differences found with respect to

perceived workload increase, role overload, life satisfaction, employee retention, and

productivity of layoff survivors of the two organizations. The variables having significant

difference include the work - life balance, job satisfaction and commitment of employees

towards their organizations.

The mean scores show that the layoff survivors of PTCL avail more work - life

balance facilities and are more satisfied with their jobs as compared to HBL survivors.

On the other hand the survivors of HBL are more committed to their organization as

compared to PTCL survivors.


Chapter 6

Conclusion and Recommendations

Comparison of results and discussion

Implications of the results

Recommendations

Limitations of the study


Chapter 6

Conclusions and recommendations

The current study is an effort to examine the relationships of various variables in the

context of layoff survivors via path analysis, a part of structural equation modeling, to

examine how these relationships exist after downsizing. The findings are explained in the

light of objectives set for the current examination.

One of the objectives of the study is to examine the relationship of role overload

with layoff survivors work - life balance, job satisfaction and life satisfaction. The

findings indicate that the actual work load increase experienced by layoff survivors is a

clear picture of excessive work loads. The existence of high role overload in the work

place has high negative impact on layoff survivors’ ability to balance their work and life

affairs. The results also confirm that role overload also heavily hampers job satisfaction

of layoff survivors. Similar to the effects of role overload on layoff survivors’ job

satisfaction it has negative effect on layoff survivors’ life satisfaction as well but with

low intensity.

Work - life balance facilities are provided by the organizations to their employees

to comfortably carryout work and non - work activities, another objective of the research

is to analyze whether work - life balance is positively or negatively related to job

satisfaction, layoff survivors’ retention, organizational commitment and life satisfaction.

The perception of work - life balance has slightly effected the job satisfaction of

layoff survivors positively. Moreover, the results affirm that the perception of work - life

balance of layoff survivors’ helps them to remain satisfied with their lives up to some

extent. The layoff survivors who perceived their balancing work and life positive are

interested to retain their jobs and work in the same organization. The perception of being

balanced has a great impact on retention of their jobs. Additionally, it is clear that the

perception of layoff survivors that they can better manage their work and life affairs has

least impact on their commitment with the organization.

Further the objective of the study focused on examining the relationship of layoff

survivors’ retention, organizational commitment, job satisfaction and life satisfaction

with layoff survivors’ productivity.


Unlike the researchers imagination the layoff survivors’ who are happy (satisfied)

with their jobs are least productive. The results show a positive but very mild relationship

between layoff survivors’ job satisfaction and their productivity. It means that job

satisfaction is not mainly responsible for bringing change in the productivity of layoff

survivors in a developing country, Pakistan.

The findings suggest that layoff survivors are least productive even after retaining

their jobs. The result is non - significant which means that retention of job does not mean

that the employees be productive while at work. Moreover, the results depict that the

commitment of layoff survivors that they hold towards their organizations has a least

concern with their being productive. Layoff survivors who perceive that they are satisfied

with their lives account for very little change in productivity while at work.

Additionally the study examined the whether there are any differences of mean

scores among layoff survivors of HBL and PTCL with respect to the perceived workload

increased, role overload, work life balance, job satisfaction, employee retention,

organizational commitment, life satisfaction and productivity.

The results show that the two groups were having significant differences with

respect to work - life balance, job satisfaction and organizational commitment of layoff

survivors. At one side survivors of PTCL are found to be more balanced in their work

and life spheres and at the same time were happy with their jobs as compared to HBL

survivors keeping in view their mean scores. On the other side the survivors of HBL have

shown more commitment with their organizations as compared to PTCL survivors.

The study concludes that reduction in workforce not only results in heavy

workloads but also hampers the balance between making justice to the work and life

spheres. It also results in lowering the life and job satisfaction of layoff survivors but the

provision of work - life balance facilities help in saving the situation. The layoff

survivors feeling that they are better in a position to manage work and life responsibilities

remained satisfied with their jobs and lives as well as try to retain their jobs for a longer

period of time and remain committed to the organizations they are working in. Definitely

when work - life balance has a positive effect on job satisfaction, life satisfaction,

retention and organizational commitment. All these factors contribute positively to their

productivity while at work.


It is thus necessary that the top management of the organizations must carefully

appraise the outcomes of layoffs prior to execution of such plans. Facing tough

economic conditions does not necessarily means work force reduction but the

management of the organizations must concentrate upon increasing the innovativeness of

their employees.

6.1. Comparison of results and discussion

The results of the present study contribute to the base of knowledge by adding the work -

life experiences of layoff survivors in the two giant organizations operating in Pakistan.

Before starting the formal discussion the main research questions addressed in this study

are mentioned below;

What is the effect of role overload on the work - life balance, job satisfaction and

life satisfaction of the layoff survivors?

How work - life balance effects job satisfaction, employee retention,

organizational commitment and life satisfaction of the layoff survivors?

How employee productivity is affected by job satisfaction of layoff survivors,

their retention organizational commitment and life satisfaction in the presence of

layoff survivors’ perception about work - life balance?

The findings regarding the model studied confirm the majority of the hypotheses. The

findings of the present research study are compared to the earlier research studies in the

following manner.

Perceived work load increase and role overload (WLI - RO)

By looking at the results of overall model, it is clear that perceived workload increase has

a strong positive and significant relationship with role overload having β = .957. The

result is consistent with the earlier studies (Virick et al., 2007; Adebayo, 2006; Kim &

Wright, 2007; Butt & Lance, 2005; Skinner & Pocock, 2008). It means that the

expectations of the survivors were right about workloads because they have to absorb the

responsibilities of their co - workers who have been laid off by their organization (Fong

& Kleiner, 2004).


Role overload and work - life balance (RO - WLB)

The results of the current study reveals that role overload has a strong negative and

significant relationship with work - life balance having β = -.875. This finding is in

accordance with the research study conducted by Virick et al. (2007) in a

telecommunication company in the United States. More widely mixed findings in the

literature are found for the relationship of role overload with different variables such as

role overload is associated with employee’s depressive symptoms and relationship

conflict which means lower work - life balance and life satisfaction (Perry-Jenkins et al.,

2007).

Role overload is inversely related to age and positively related to the number of

children and the hours worked (work load) (Thiagarajan, Chakrabarty & Taylor, 2006).

Role conflict, role overload and hours spent on paid work are the main factors affecting

work to family interface (Fu & Shaffer, 2002). Long working hours are one of the signals

of role overload and a source of work life conflict (White et al., 2003). It means that the

location of the survivors does not matter. Even it can be experienced by any of the

survivor working in any organization across the world.

The post layoff workload experienced by the layoff survivors lead to increased

role overloads. On one side it is difficult for the employees to manage high overloads and

on the other it is also difficult for the management of the organizations to redistribute

work among the remaining employees (survivors). So while reducing work force it can be

experienced as one f the major difficulties affecting the operations of the organization.

Role overload, job satisfaction and life satisfaction (RO - JS - LS)

Similarly the role overload of layoff survivors has a negative relationship with job

satisfaction (β = -.641) and life satisfaction (β = -.658) of layoff survivors. The finding

are consistent with earlier research studies which states that workers suffering from role

conflict, role ambiguity and role overload are more likely to experience reduced job

satisfaction and organizational commitment (Lambert & Hogan, 2008) and a positive

correlation has seldom been found between role stress and job satisfaction (Tang &

Chang, 2010). Evandrou and Glaser (2004) states that role overload in the literature is

responsible for the poor quality of life. The orgn\animations must consider this factor


negatively affecting job and life satisfaction of survivors. Training can be one of the tools

to overcome this issue.

Work - life balance, job satisfaction, life satisfaction, employee retention and

organizational commitment (WLB - JS - LS - ER - OC)

Work - life balance has positive relationship with job satisfaction (β = .236), life

satisfaction (β = .331), layoff survivors retention (β = .955) and organizational

commitment (β = .337) of layoff survivors. It means that work - life balance has a

positive effect on the satisfaction of layoff survivors with their work and lives. The work

- life balance practices adopted by the organizations motivate employees to remain with

the organizations and to be more loyal to the organizations. Otherwise the non -

availability of work - life balance practices, shortage of progressing opportunities,

uncomfortable work environment, lack of encouragement and recognition leads to stress,

which ultimately results in dissatisfaction, burnout and finally increased turnover rate

within organization (Ahmadi & Alireza, 2007; Ahmed et al., 2010).

Work - life imbalance causes job dissatisfaction. The consequences of job

dissatisfaction reported in the literature includes physical and psychological distress, low

level of productivity and commitment, turnover intention, etc which may harm the

employees commitment to the organization and retention (Calvo-Salguero, Carrasco-

González & Salinas-Martínez de Lecea, 2010). A good balance between the work roles

and non - work (life) roles help employees get maximum satisfaction. Satisfaction with

work - life balance policies and practices in an organization are associated with

employee’s job satisfaction and life satisfaction (Ezra & Deckman, 1996). Work - life

balance is associated with organizational commitment of employees (Kinnie et al., 2005;

Brough et al., 2008), greater job satisfaction (Oswald, 2002; Cabrita & Heloísa, 2006),

job satisfaction and life satisfaction (Hughes & Bozionelos, 2007).

It is easy to infer from the available findings that work - life balance is related to

greater organizational commitment, higher job and life satisfaction and is a source of

retaining employees in the organizations for a longer period of time and presence of work

- life balance policies in an organization is a reflection of higher perceived organizational

performance.


Job satisfaction, employee retention, organizational commitment, life satisfaction and

employee productivity (JS - ER - OC - LS - EP)

By looking at the productivity of layoff survivors the factors positively related to layoff

survivors productivity are job satisfaction (β = .126), life satisfaction (β = .077),

employee retention with the same organization (β = .034) and commitment of layoff

survivors which they show towards their organizations (β = .062).

The current findings provide support for the available literature which states that

job satisfaction and commitment are the basic determinants of employee turnover,

performance, and productivity (Opkara, 2004). Committed and satisfied employees tend

to be high performers that contribute towards the individual and organizational

productivity. On the contrary low level of job satisfaction predicts negative attitudes and

behavior in the work context, such as absenteeism, external turnover and reduced

productivity (Calvo-Salguero, Carrasco-González & Salinas-Martínez de Lecea, 2010).

Employee retention is critical for the organizations to carryout its operations

successfully other wise it creates serious threats for the organizations. Abbasi and

Hollman (2000) indicated that when an organization loses a critical employee, there is

negative impact on innovation, consistency in providing service to guests may be

jeopardized, and major delays in the delivery of services to customers may occur.

Moreover, Francis (2004) reported that staff turnover has specific expenses related to

retraining, recruitment, and lost productivity.

The findings are consistent with the available literature stating that employee

productivity is affected by workload (Holmes, 2001), role overload (Tarafdar et al.,

2007), work - life balance (Brough et al., 2008), job satisfaction (Shikdar & Das, 2003),

employee retention (Fatt, SekKhin & Heng, 2010), organizational commitment

(Raymond & Flannery, 2002; Ugboro, 2006) and downsizing (Yu & Park, 2006).

Work can have benefits as well as costs (such as stress) for employees. Being

employed in well designed job with manageable workloads can be highly beneficial.

Providing people with financial security and opportunities for physical and mental

activity, personal growth, and a sense of belongingness motivate them to work with

commitment. On the other hand poorly designed work with excessively high or low

workload can have potential ‘wellbeing costs’, ranging from fatigue, discomfort, stress



and job dissatisfaction to serious work related injuries and diseases and even death

(Briner, 2000).

Downsizing has erroneous effect on the productivity of layoff survivors by

increasing perceived workload and role overload. The results of the Structure Equation

Modeling (SEM) show that there is a positive non- significant relationship between post

layoff perceived workload increase and role overload. This in-turn increases the mental

stress that may also leads to health problems. When an employee is working under

stressful work environment there are considerable chances that the employee may

experience dissatisfaction from work. Job dissatisfaction leads to the conflict in

managing work and life (including family and non-family) responsibilities.

Role overload is also an outcome of lack of skilled Human Resources (HR) and

advanced technology. The obsolete technology and non-professional human resources

can hamper effective working.

The study results (-0.88) show a strong negative relationship between role

overload and work - life balance. It has been proved that increase in the role overload

leads to work - life conflict (least work- life balance). Role overload effect the quality of

work that reduces the satisfaction with work and life. Work to family conflict arising out

of role overload can be resolved by supervisors and co-workers at work whereas family-

to-work conflict can be minimized by the support from spouse.

Another finding of the current study is that role overload has a negative

relationship (-0.64) with job satisfaction which shows that increase in role overload is

inversely related the satisfaction of layoff survivors at work.

Role ambiguity and role conflict are the factors increasing job dissatisfaction

resulting in lowering the commitment of layoff survivors. Training and development,

educating employees, time management, role clarity, job description, and technological

advancement can help in reducing role overload hence enhancing satisfaction at work.

The studies have concluded that role overload is also the strongest predictor of

psychological health, work pressure, job satisfaction and turnover intentions.

Life satisfaction includes quality of life, well - being. Throughout the current

discussion the term well - being is used more or less interchangeably with life

satisfaction. An important consideration that needs to be taken into account when


conceptualizing life satisfaction is the point of reference from which the concept is

measured. Life satisfaction is with respect to priorities. Setting priorities in life help

layoff survivors to reduce role overload at work as well as at home.

Shift work can reduce role overload (Perry-Jenkins et al., 2007). Layoff survivors may

also be offered with shift work schedule that ultimately leading to life satisfaction.

Satisfaction with one’s job is the source of his/her productivity (Shikdar & Das

2003). Higher level of satisfaction with career development programs produces higher

levels of quality of working life, job satisfaction, professional development and

productivity (Chen, Chang & Yeh, 2006).

The subjective well - being (life satisfaction) is based on the individual’s internal

perception of happiness and satisfaction (Keyes, Shmotkin & Ryff, 2002). It is a general

conception that when people make progress towards their goals, they generally tend to

react positively which means enhancement in productivity.

People provided with better health facilities as a source of work - life balance

opportunities experience life satisfaction that enhances productivity among them. People

having better mental state (mental health), are more satisfied with their lives and are more

productive.

Employee retention and employee productivity are the essential inputs of

organizational success and better performance. Retention of skilled employees in an

important issue for the organizational success and long term growth (Fatt, SekKhin &

Heng, 2010) so it is clear that omitted and retained employees contribute to the

organizational success.

The committed employees, participating in the organizational activities are

productive which confirms that employee participation was an important determinant of

job satisfaction, employee commitment and employee productivity (Bhatti & Qureshi,

2007).

Increase in employees’ affective commitment helps in building morale of the

employees which increases job security and productivity. Fatt, SekKhin and Heng (2010)

noted that committed employees possibly perform beyond the call of duty to fulfill

customers’ needs and were far more motivated to work to the best of their ability.


6.2. Implications

The research has significant practical importance for institutions, executives and

management of human resource departments. The study has highlighted the after effects

of downsizing by examining the relationship of several variables in a sample of layoff

survivors.

First and the foremost step to be adopted by the organizations is to develop a

comprehensive work - life balance policies and implement those for the betterment of the

layoff survivors. Although the work - life balance practices prevail in both of the

organizations but there is no clear cut definition of those policies. Also there is a need to

implement those developed policies with justice.

The results of the current study also suggest that out of four factors such as, job

satisfaction, life satisfaction, employee retention and organizational commitment, the

employee retention is heavily effected by the availability of work - life balance practices

and job satisfaction effects productivity the most.

The research has shown that due to downsizing customers are negatively affected

by employee cutbacks losing valued contact personnel, suffer from negative survivor

emotions, and experience a deterioration of perceived service quality levels. This has lead

to customer dissatisfaction, decreased loyalty, lower purchase intentions and finally, to a

loss of valued customers. The factors that diminish negative downsizing effects include

satisfaction of the remaining employees (layoff survivors) with their work and non - work

responsibilities, retention of employees by providing them work - life balance

opportunities with justice, enhancing organizational commitment of the layoff survivors

by highlighting the importance of their presence for the organizations etc. This in turn

can lead to increased productivity among them (survivors).

The financial crises have led the organizations to go for downsizing therefore,

increasing pressure on layoff survivors. The organizations need to design friendly HR

policies such as pay for performance, health insurance, flexible working hours and skills

advancement opportunities.

In this scenario the development of work - life balance policies such as, training,

pay for performance, maternity and paternity leaves, educational facilities, flexible


working hours, short and long term loan facilities etc. leads to survivors’ satisfaction and

satisfaction in - turn leads to keep them with the organizations and work even harder.

Adoption of adequate work - life balance opportunities to layoff survivors save

their health which save the survivors from different psychological states such as, shock,

anxiety, stress, disengagement, and depression. Helping employees to overcome stress

and other psychological difficulties is a key to retain layoff survivors loyal to the

organization and keep them productive.

Layoff survivors are the people experiencing heavy workloads, anxiety and

frustration. The provision of employee assistance programs (EAP) incorporated in work -

life balance strategies is effective in decreasing tardiness, absenteeism, and rates of

turnover.

6.3. Recommendations:

Perceived workload, role overload and work - life balance

Workload gives rise to poor decision making and lack of innovation and creativity. That

can be overcome by offering time management, behavioral training and development

opportunities to the employees and skill building approach.

Layoff survivors are the people exposed to high workloads. They can be

compensated by the provision of work - life balance opportunities like flexible work

hours, compensation for over time, on the job training for handling workload.

Layoff survivors should be provided with the up to date technology to cope up

with the overload by achieving efficiency. The technology should cover the professional

and technical needs of the survivors. Role clarity is another tool to overcome overload

resulting in low work to life conflict. This can be achieved by providing clear job

description to each survivor.

Social support can be another factor which can ease the role overload at work

place. The management can provide social gatherings, informal meetings, work sharing

practices and recreational opportunities for layoff survivors to release work stress.

Building time management skills and providing learning opportunities can save the

situation and help layoff survivors to perform efficiently.


Organizations can play a key role in reducing work - family conflict of executives

by introducing direct supportive practices like employee assistance programs (EAP).

These programs can be incorporated in human resource management strategies, since

these programs have been found effective in decreasing tardiness, absenteeism, and rates

of turnover. Additionally these are helpful in reducing the strain - based conflict and

related stress of employees due to work - family interferences can thus be reduced

(Adekola, 2010).

Training and development practices can be one of the most significant ways to

support personnel in gaining new knowledge and skills required to adhere to competitive

standards (Tsai & Tai, 2003).

Role overload, job satisfaction and life satisfaction

Introducing work - life balance practices such as on the job and off the job trainings,

recreational leave, maternity and paternity leave, recreation opportunities at work place

etc. can decrease job dissatisfaction arising out of the workload and turnover intentions.

Organizations should design clear job descriptions leading to role clarity decreasing

ambiguity and depression.

Setting long term and short terms objectives and achieving them also help the

survivors to reduce anxiety and frustration resulting in lowering role overload and

enhancing satisfaction.

Management should provide the layoff survivors with the economic benefits,

autonomy, recognition and prestige to enhance job satisfaction. Work - life balance not

only influences the extrinsic job satisfaction that is satisfaction gained from salary,

benefits and institutional environment also known as hygiene factors (Herzberg et al.

1959, p. 113; Iiacqua & Schumacher, 2001, p. 51) but also the intrinsic job satisfaction

that is the nature of works. Intrinsic job satisfaction factors are also recognized as

motivators (Herzberg et al., 1959, p. 114) include satisfaction with recognition,

satisfaction with achievements and satisfaction with possibility of growth and

advancement and satisfaction with responsibilities a person is holding at work.

Organizations should provide the layoff survivors with autonomy in work and conducive

work environment to enhance their job satisfaction (Butt and Lance 2005).


The appraisal system and compensation packages which are the components of

job satisfaction are related positively to WLC among male and female employees. Work

life balance practices should be offered with justice to all the layoff survivors so that it

may not be a source of dissatisfaction as in the case of bus drivers (Hughes & Bozionelos

2007). So the policies should equally consider each and every person working in an

organization. Five day work week is another way of providing the survivors with work

life balance practices.

The work - life balance strategies adopted by an organization may include flexi

time, telecommuting (communication via computers and internet), child care, elder care,

Leaves (maternity and paternity), job sharing, employee training and assistance

programs, in house store (utility store) services, gym services, prayer places, summer and

Eid – ul – Fitr and Eid – ul - Azha (religious events for Muslims) vacation, etc. All these

WLB opportunities help in getting satisfaction for the survivors and ultimately increase

productivity.

Provision of adequate work - life balance opportunities to layoff survivors can

save their health. These facilities help in saving the survivors from different

psychological states such as, shock, anxiety, stress, disengagement, and depression.

Helping employees to overcome stress and other psychological difficulties is a key to

retain layoff survivors loyal to the organization and keep them productive.

Organizations can help layoff survivors manage better work - life balance by

availing pick and drop service offered by the organization, bank loans (house financing,

education for children, customer financing, etc.) and so on.

Many research studies have found that HRD practices, including work life

balance practices, affect the behavior and attitudes of employees (Guest, 2002; Edgar &

Geare, 2005; Muse & Stamper, 2007). Lee and Bruvold (2003) found that the

investments in training the workforce by the organizations contribute to the formation of

positive perceptions in employees about the organization’s willingness to support their

development. These positive perceptions in-turn help employees to believe in a social

exchange relationship between them and the organization, which makes them act in a

reciprocate manner (Lee & Bruvold, 2003). Employees are more satisfied with their jobs

and more willing to work hard in order to contribute to a higher performance of the


organization (Eisenberger et al., 2001). Introduction of social clubs as a part of work life

balance facilities also help employees to be satisfied and retain in the same organization.

Work - life balance helps to produce/increased job satisfaction (Cabrita & Heloísa

2006; Malik et al., 2010). Job dissatisfaction is a source of work - life conflict (Oswald,

2002). There is a need to provide the layoff survivors with such a friendly environment at

work that they remain committed to the organization and feel satisfied with their work.

Supervisory practices are one of the factors of work life balance that effect employee

satisfaction at work (Hancer and George 2003) and become source of better performance

and productivity.

Among other benefits for layoff survivors subsidized child care facilities can be

offered for female employees specially.

Life coaching can be a better option for balancing work and life of layoff survivors. Life

coaching can be offered at the work place thorough formal and informal means of

learning.

Work to life and life to work interface may have different effects on the work

attitudes of male and female layoff survivors. Supportive work environment is another

predictor of job satisfaction (Gomez, Khan, Malik, & Saif, 2010) and life satisfaction

(Francis 2004). The organizations should provide the layoff survivors with supportive

work environment (including social support from boss and co-workers). This will help

layoff survivors to stay in the same organization.

Personal characteristics and HRM polices have the significant impact on the

layoff survivors job satisfaction. The layoff survivors feeling more supported by the

organizational work - life balance practices are tend to be more satisfied than otherwise.

Organizations should survey and find out the facets of job satisfaction which effect layoff

survivors the most.

Social support provided by survivors can reduce role overload and enhance job

satisfaction so the organizations should build cordial relationships between layoff

survivors through professionalism and effective communication.

Moreover, up to date helping equipment is related to higher job satisfaction (Penz

et al., 2008). This helps survivors to finish work in time because the perception to work

overtime decreases the level of job satisfaction and lack of adequate resources increases


stress and reduces time spent with their families and better working helps them to achieve

life satisfaction because job satisfaction has a direct strong effect on life satisfaction

(Iverson & Maguire, 2000).

The organizations offering family - friendly programs and flexible working hours

could assist layoff survivors to separate their work and family responsibility, which

would in turn result in a work environment that promote employee mental health and

positive attitudes toward life. The organizations offering work - life balance policies may

be gender specific as per requirement of layoff survivors. As Army Welfare Trust (AWT)

in Pakistan has a policy of “no female after sunset’ in the organization. These types of

policies may also help in achieving life satisfaction for layoff survivors.

Time based (time specific) work demands give rise to stress that leads to life

dissatisfaction among layoff survivors. The five predictors of well - being includes

pleasure, comfort, placidity, enthusiasm, and vigor (Rego & Cunha, 2009). The provision

of these characteristics as a part of work - life balance policies may enhance life

satisfaction among layoff survivors.

To achieve a supportive culture, change is must, starting from top level and

training of middle managers and supervisors. The implementation of work - life balance

facilities by the organizations may benefit layoff survivors but for such initiatives to be

successful, the organizations and their employees must deviate from the norm of rigid,

long work hours that exists in these organizations.

Work - life balance, employee retention, organizational commitment

Turnover is a symptom of upcoming huge systematic problems such as ineffective

retention management, the organizations have to make it clear that what make employees

to be committed to the organizations and be productive. The organizations have to

develop policies based on employee care and security and make them feel that

organizations really take care of them (Dobbs, 2001). Same was suggested by the

Hawthorne studies conducted at Western Electric few decades back (Parson, 1992).

Various methods adopted by the organizations to retain their employees and

enhance commitment among them include compensation (Parker & Wright, 2001),

challenging work (Beck, 2001), work relationships (Clarke, 2001), recognition (Davies,


2001), work - life balance (Perry – Smith & Blum, 2000), effective communication

(Gopinath & Becker, 2000).

Organizations should try their level best to keep their employees satisfied to avoid

absenteeism that is the failure of employees to attend their work. The satisfied workers

are willing to attend the work and less likely to keep away from work for un-explained

reasons.

The provision of work - life balance opportunities help layoff survivors to feel the

sense of psychological well - being that in-turn will be a motivation to remain with the

organization.

The adoption of high performance work practices also help in retaining the layoff

survivors. The high performance work practices may include revision of employee

recruitment and selection procedures; pay incentives, performance appraisal systems,

training, education and development that improve the skills, knowledge and abilities of

layoff survivors. All these practices are aimed at enhancing employee motivation to work

with keen interest.

By providing layoff survivors with the jobs which are in line with their

educational background is another way of retaining them for a longer period of time. By

doing this the survivors feel satisfied and be encouraged to work with great zeal.

Time bound contracts by the organization also help retaining the employees. Interesting

work, personnel decisions made on merit, extrinsic rewards including pay, promotion and

security, work - life balance, good relationships with co - workers and supervisors are

other factors enhancing survivors retention.

Interesting work (task) is a source of satisfaction and motivation, for employees

and layoff survivors therefore, they should be provided with such tasks that are

compatible with their education qualifications and experience that will motivate them to

work and remain at their work places.

Ensuring satisfaction with supervision, commitment, low workloads, and feelings

of appreciation help organizations to retain layoff survivors for a longer period of time.

Creating a positive work culture that is top management should make employees feel

important, respected, and valued by listening to their concerns and making them a top


priority. This can help in the increase in retention rate of layoff survivors which leading

to work effectiveness.

Person job fit (P – J fit) that is matching person with the requirements of the job

(Edwards, 1991; Sekiguchi, 2004) is another strategy that organizations can adopt to

retain their valued employees.

Employees generally tend to remain in the organization if they are rewarded well,

therefore, (Mercer, 2003) organizations should make policies based on quality based

performance so that the rewards are distributed with justice. A sense of accomplishment

is a strong motivator for employees. Employees tend to remain with the organization

when they feel that their capabilities, efforts and performance are recognized and

appreciated (Davies, 2001).

From the employee perspective, if the skills specific training is provided to the

employees it helps in increasing productivity. Increase in productivity in-turn tends to

raise a workers wage, thus providing an employee an incentive to stay in the same

organization.

Job satisfaction, employee retention, organizational commitment and productivity

In order to make layoff survivors satisfied and committed to their jobs the organizations

should develop effective motivational strategies at various levels of management

resulting in increased productivity. Organizations should provide the option of job variety

to layoff survivors that lead to job satisfaction and organizational commitment.

The policy makers should take necessary measures for the best possible provision

of intrinsic and extrinsic job rewards to make layoff survivors highly satisfied and

committed.

Loyalty of layoff survivors may be enhanced via satisfaction with pecuniary and

non - pecuniary benefits, co – workers support and supervisor support. The attachment to

the organization can be enhanced via provision of work life balance opportunities and

benefits which are the sources to motivate the employees to work harder. Increased well -

being of layoff survivors prove to be a source of motivation, retention and commitment to

the organization that results in improved productivity.


Flow of in - time information through out the organization also helps employees

to feel satisfied and committed. The layoff survivors if provided with the adequate

information about the organizational policies and benefits may also help in retention and

better performance.

Top management may enhance the commitment among layoff survivors by

mounting employee satisfaction with training, compensation policies and working

conditions including effective communication practices. Furthermore, managers can

enhance organizational commitment by communicating that they value employees’

contribution and that they are concerned about employees’ well being (Iqbal, 2010).

Turnover is a symptom of upcoming huge systematic problems such as ineffective

retention management, the organizations have to make it clear that what make employees

to be committed to the organizations and be productive. The organizations have to

develop policies based on employee care and security and make them feel that

organizations really take care of them (Dobbs, 2001). Same was suggested by the

Hawthorne studies conducted at Western Electric few decades back (Parsons, 1992).

Productivity among layoff survivors may be enhanced via provision of participatory

management practices. Besides pecuniary benefits participatory management practices

enhance satisfaction among workers (Shikdar & Das 2003) and encourage them to work

hard which means increased productivity.

The addition of performance standards, performance feedback and monetary

incentive adds to layoff survivor satisfaction, commitment and productivity. Work

environment including ergonomics effects layoff survivor’s productivity. Ergonomics is

the science of designing the workplace environment to fit the user. Proper ergonomic

design is necessary to prevent repetitive strain injuries, and to enhance performance.

Above all the present study focuses on maintaining the productivity among layoff

survivors where as there could be an assumption of enhancing the productivity of layoff

survivors. This is a known fact (Wagner, 1998) that restructuring of organizations result

in decrease in the productivity of employees.


6.4. Limitations

First, the model presented by the researcher is a first attempt regarding layoff survivors in

Pakistan. Clearly, there is a need to replicate the study among other groups and

organizations.

A cross - sectional survey method, using a questionnaire, is employed in the

current study. The said method is employed keeping in mind the number of reasons such

as, with limited human and financial resources the distribution of questionnaire among

layoff survivors through top managers and moderators is a relatively in - expensive

method of gathering data from layoff survivors over a large geographical area.

One of the crucial concerns of the study is to gain responses at the maximum from

layoff survivors (Fowler, 2002). But response rate has been low as there was no personal

contact, in most situations, with the layoff survivors. So there are chances of not building

rapport with the researcher (Gliner & Morgan, 2000). Bernard (2000) notes that while

using questionnaires it is up to the knowledge and experience of the respondent that how

well he/she interprets it rightly.

The scope of this study is limited to the layoff survivors of two main

organizations of Pakistan therefore findings of the study can be generalized to all the

organizations operating (with reduced work force) in Pakistan but can not be generalized

to the rest of the world.

The relationship of productivity issue is examined through four different

variables. Same can be assessed by a longitudinal study involving repeated observations

before and after the implementation of work - life balance practices.

The problems concerning conducting field research studies in the developing

countries have already been highlighted by the researchers (Vose & Cervellini, 2005).

Similar problems were experienced by the researcher for the current study while

gathering data. The problems in Pakistan for conducting this research study included non

availability of secondary sources for survivor’s data and accessing organizations for the

information is a tough task. Organizations operating in Pakistan seem least convinced

regarding the importance of participating in research studies.


Concluding remarks

The current challenges and complex economic situation intensified the competitive

position of organizations. The Pakistan’s economy is well connected to the global

economy that compels the organizations contributing toward the economy of Pakistan to

take measures for reducing costs and to survive in the highly competitive market. For

doing so, the organizations need to reduce costs by reducing workforce. This thesis

provides insights in the after effects of downsizing on survivors and indicates how the

relationships of various variables exist among layoff survivors.

The current study is conducted in the context of layoff survivors by using path

analysis, a part of structural equation model, to examine the relationships of the variables

as after effects of work force reduction (downsizing). The findings of the current

examination are summarized as the work load/ role overload are the causal factors for

work - life imbalance among layoff survivors. The results also confirm that due to role

overload the job satisfaction level of layoff survivors is greatly affected negatively.

Similar to the effects of role overload on layoff survivors’ job satisfaction it has negative

affects on layoff survivors’ life satisfaction but with low intensity.

The perception of work - life balance has slightly effected the job satisfaction of

layoff survivors’ positively. Moreover, the results confirm that the perception of work -

life balance of layoff survivors’ helps them to remain satisfied with their lives up to some

extent. The layoff survivors who perceive their balancing work and life positive are

interested to retain their jobs and work in the same organization. The perception of being

balanced has a great impact on retention of their jobs.

Additionally, it is clear that the perception of layoff survivors that they can better

manage their work and life affairs has least impact on their commitment with the

organization and unlike the researchers imagination the layoff survivors’ who are happy

with their jobs are least productive. The results show a positive but very mild relationship

between layoff survivors’ job satisfaction and their productivity. It means that job

satisfaction is least responsible for bringing change in the productivity of layoff survivors

in a developing country, Pakistan.

The results show that layoff survivors are least productive even after retaining

their jobs. It means that retention of job does not mean that the employees be productive


while at work. Moreover, the results depict that the commitment of layoff survivors that

they hold towards their organizations has a least concern with their being productive.

Layoff survivors who perceive that they are satisfied with their lives account for very

little change in productivity while at work.

In the light of results of the study it is suggested that the organizations must take it

as a responsibility to promote healthy working attitudes and practices in order to keep

employee satisfaction high. Indeed, organizations in New Zealand (Forsyth & Polzer –

Debruyne, 2007), United States of America (Galinsky, Bond & Friedman, 1993; Keene &

Reynolds, 2005; Virick et al., 2007), Germany (Bauer, GroB, Oliver, Sirglen & Smith,

2007), India (Lakshmikanthan & Deepa, 2010), and now in Pakistan (Malik, Gomez,

Ahmad & Saif, 2010) are realizing that it is in their own best interests to promote work -

life balance and satisfaction of employees for better outcomes.


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Appendixes

Appendix A - The cover letter

Appendix B - The questionnaire


Appendix - A

Covering Letter

Dear Participant,

I am carrying out this research having title “Role of Work Life Balance In

maintaining the Productivity among Layoff Survivors”. If you are a layoff survivor (still

working with the same organization after downsizing) it would be greatly appreciated if

you could take twenty minutes of your valuable time to complete this questionnaire.

I assure you that the questionnaire is anonymous and no identities can be captured

by completing this questionnaire. I therefore ensure strict confidentiality.

Thank you for taking the time to complete this questionnaire.

Kind regards.


Ph.D. Scholar

FUIEMS, Foundation University Islamabad,

Pakistan.

[email protected]



Appendix - B

Questionnaire

Section – A. Demographic Information.

1. You are currently working with HBL PTCL

2. Number of years you worked in this organization. 1 – 5 6 – 10

10 – 15 Over 15 yrs

3. Job status. Top mgt. Middle mgt.

1st level mgt. Others

4. Gender. Male Female

5. Marital status. Unmarried Married

6. Age (years). 20 - 29 30 – 39

40 - 49 50 - 59

7. Education Matric. Higher secondary Graduation

Masters Doctorate Others

8. Dependents in your family? Children Elders

1 – 3 1 – 3

4 – 6 4 - 6

Section – B. Perceived post – layoff Work load Increase.

Please encircle the following as 1 = strongly disagree to 5 = strongly agree.

WLI1 I feel my job requires me to work too fast. 1 2 3 4 5

WLI 2 I feel that I never have enough time to get everything done at

work.

1 2 3 4 5

WLI 3 My job requires me to work very hard (physically and/or

mentally).

1 2 3 4 5

WLI 4 I often have to work overtime. 1 2 3 4 5

WLI 5 I feel my workload is always too heavy. 1 2 3 4 5

WLI 6 The amount of work I am expected to do never allows me to do

a good job.

1 2 3 4 5

WLI 7 I feel highly satisfied with the amount of work I am expected to

do.

1 2 3 4 5


WLI 8 I feel that I have too much work for one person to do. 1 2 3 4 5

Section – C. Role Overload

RO1 I do not have time and energy to do the work that must be done. 1 2 3 4 5

RO 2 There are too many demands on my time 1 2 3 4 5

RO 3 I need more hours in the day to do all the things which are

expected of me.

1 2 3 4 5

RO 4 I can’t ever seem to get hold of the tasks at work. 1 2 3 4 5

RO 5 It seems that I have not any time for myself. 1 2 3 4 5

RO 6 There are times when I cannot meet everyone’s expectations. 1 2 3 4 5

RO 7 Sometimes I feel as if there are no enough hours in the day. 1 2 3 4 5

RO 8 Many times I have to cancel commitments. 1 2 3 4 5

RO 9 Sometimes I have to overextend myself in order to be able to

finish everything I have to do.

1 2 3 4 5

RO 10 I seem to have more commitments to overcome than some other

employee I know.

1 2 3 4 5

RO 11 I have to prepare priority list to get all the things done.

Otherwise I forget.

1 2 3 4 5

RO 12 I feel I have to do things hastily and may be less carefully in

order to get everything done.

1 2 3 4 5

RO 13 I just can’t find the energy in me to do all the things expected of

me.

1 2 3 4 5

Section D. Work Life Balance

WLB1 It is very easy for me to balance the demands of work and

personal and family life.

1 2 3 4 5

WLB 2 I have sufficient time away from my job at my organization to

maintain adequate work and personal/family life balance.

1 2 3 4 5

WLB 3 When I take a vacation, I am able to separate myself from work

and enjoy myself.

1 2 3 4 5

WLB 4 I always feel drained when I go home from work because of

work pressures and problems.

1 2 3 4 5

WLB 5 All in all I feel completely successful in balancing my work and

personal and family life.

1 2 3 4 5

Section – F. Life satisfaction.

LS1 In most ways my life is close to my ideal 1 2 3 4 5

LS 2 The conditions of my life are excellent. 1 2 3 4 5

LS 3 I am satisfied with my Life. 1 2 3 4 5

LS 4 So far I have achieved the important things I wanted in Life. 1 2 3 4 5

LS 5 If I have another chance in life, I will change nothing.. 1 2 3 4 5

Section – G. Organizational commitment.

Affective Commitment

OC1 I would be very happy to spend the rest of my career with this

organization.

1 2 3 4 5

OC 2 I really feel as if this organization’s problems are my own. 1 2 3 4 5

OC 3 I do not feel a strong sense of “belonging’ to my organization.* 1 2 3 4 5

OC 4 I do not feel “emotionally attached” to this organization. * 1 2 3 4 5

OC 5 I do not feel like “part of the family” at my organization. * 1 2 3 4 5

OC 6 This organization has a great deal of personal meaning for me. 1 2 3 4 5


Continuance commitment

OC 7 At present, staying with my organization is a matter of necessity

as much as desire.

1 2 3 4 5

OC 8 It would be very hard for me to leave my organization right

now, even if I want to.

1 2 3

OC 9 Too much of my life would be disrupted if I decided to leave my

organization now.

1 2 3 4 5

OC 10 I feel that I have too few options to consider leaving this

organization.

1 2 3 4 5

OC 11 If I had not already put so much of myself into this organization,

I might consider working elsewhere.

1 2 3 4 5

OC 12 One of the few negative consequences of leaving this

organization would be the scarcity of available alternatives.

1 2 3 4 5

Normative commitment

OC 13 I do not feel any obligation to remain with my current employer.

*

1 2 3 4 5

OC 14 Even if it were to my advantage, I do not feel it would be right

to leave my organization now.

1 2 3 4 5

OC 15 I would feel guilty if I left my organization now. 1 2 3 4 5

OC 16 This organization deserves my loyalty. 1 2 3 4 5

OC 17 I would not leave my organization right now because I have a

sense of obligation to the people in it.

1 2 3 4 5

OC 18 I owe a great deal to my organization. 1 2 3 4 5

Section – H. Employee retention.

ER1 I plan to work at my present job for as long as possible. 1 2 3 4 5

ER 2 I will most probably look for a new job in the near future. 1 2 3 4 5

ER 3 I plan to stay in this job for at least two to three years. 1 2 3 4 5

ER 4 I would hate to quit this job. 1 2 3 4 5

Section – I. Employee productivity.

Job autonomy

EP1 My job allows me to make my own decisions about how to

schedule my work.

1 2 3 4 5

EP 2 My job allows me to decide on the order in which things are

done on the job.

1 2 3 4 5

EP 3 My job allows me to plan how I do my work. 1 2 3 4 5

EP 4 My job gives me a chance to use my personal initiative or

judgment in carrying out the work.

1 2 3 4 5

EP 5 My job allows me to make a lot of decisions on my own. 1 2 3 4 5

EP 6 My job provides me with significant autonomy in making

decisions.

1 2 3 4 5

EP 7 My job allows me to make decisions about what methods I use

to complete my work.

1 2 3 4 5

EP 8 My job gives me considerable opportunity for independence and

freedom in how I do the work.

1 2 3 4 5

EP 9 My job allows me to decide on my own how to go about doing

my work.

1 2 3 4 5

Meeting time demands

EP 10 I work the required hours. 1 2 3 4 5

EP 11 I usually get going beginning of the work day. 1 2 3 4 5


EP 12 I start on work soon after arriving at my workplace. 1 2 3 4 5

EP 13 I generally work without breaks and rests. 1 2 3 4 5

EP 14 I generally stick to my routine/ schedule. 1 2 3 4 5

Work efficiency

EP 15 I efficiently handle the workload 1 2 3 4 5

EP 16 I work fast enough while at work. 1 2 3 4 5

EP 17 I generally finish work on time. 1 2 3 4 5

EP 18 I generally work without mistakes. 1 2 3 4 5

EP 19 I do all the tasks I am capable of. 1 2 3 4 5

Section – E. Job satisfaction

Please note 1 = Extremely dissatisfied, to 5 = Extremely satisfied.

Please add “On my Present job, this is how I feel about” at the beginning of each statement.

JS1 Being able to keep busy all the time 1 2 3 4 5

JS 2 I have the chance to work alone on the job 1 2 3 4 5

JS 3 I feel I get the chance to do different things from time to time 1 2 3 4 5

JS 4 I have the chance to be” somebody” in the community 1 2 3 4 5

JS 5 The way my boss handles his/her workers 1 2 3 4 5

JS 6 The competence of my supervisor in making decisions 1 2 3 4 5

JS 7 Being able to do things that don’t go against my conscience 1 2 3 4 5

JS 8 My job provides for steady employment 1 2 3 4 5

JS 9 I have the chance to do things for other people 1 2 3 4 5

JS 10 I have the chance to tell people what to do 1 2 3 4 5

JS 11 I have the chance to do something that makes use of my abilities 1 2 3 4 5

JS 12 The way company policies are put into practice 1 2 3 4 5

JS 13 My pay and the amount of work I do 1 2 3 4 5

JS 14 The chances for advancement on this job 1 2 3 4 5

JS 15 The freedom to use my own judgment 1 2 3 4 5

JS 16 The chance to try my own methods of doing the job 1 2 3 4 5

JS 17 The working conditions 1 2 3 4 5

JS 18 The way my co – workers get along with each other 1 2 3 4 5

JS 19 The praise I get for doing a good job 1 2 3 4 5

JS 20 The feeling of accomplishment I get from the job. 1 2 3 4 5

Thank you for your responses.

role of work life balance in maintaining the productivity among layoff...

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