Employees’ perception of organizational climate and its implications for organizational effectiveness in Amhara regional public service organs

42

EMPLOYEES’ PERCEPTION OF ORGANIZATIONAL CLIMATE

AND ITS IMPLICATIONS FOR ORGANIZATIONAL

EFFECTIVENESS IN AMHARA REGIONAL

PUBLIC SERVICE ORGANS

By

Mesfin Raji Kiltu

Project submitted in partial fulfilment for the award of the Degree of

EXECUTIVE MASTER OF BUSINESS ADMINISTRATION

Bahir Dar University, College of Business and Economics

Department of Management

Bahir Dar

June 2012

42





By

Mesfin Raji Kiltu

Student ID Number: CBE/129/03

Project submitted in partial fulfilment for the award of the Degree of

EXECUTIVE MASTER OF BUSINESS ADMINISTRATION

Bahir Dar University, College of Business and Economics

Bahir Dar

June 2012

Employees’ Perception of Organizational Climate and its implications for Organizational Effectiveness

iii

DECLARATION

I hereby declare that this Project Report titled “Employees’ perception of

organizational climate and its implications for organizational

effectiveness in Amhara regional public service organs” is

submitted by me to the College of Business and Economics, Department of

Business Management, Bahir Dar University. It is a bonafide work undertaken

by me and it is not submitted to any other University or Institution for the

award of any degree diploma / certificate or published any time before.

Mesfin Raji Kiltu Signature

------------------------------------ --------------------------

Date ……………………………..


iv

CERTIFICATION

This is to certify that the Project Report title “Employees’ perception of

organizational climate and its implications for organizational

effectiveness in Amhara regional public service organs” is

submitted in partial fulfilment for the award of EMBA Programme of

Department of Business Management, College of Business and Economics,

Bahir Dar University, was carried out by Mr. Mesfin Raji Kiltu under our

guidance. It has not been submitted to any other University or Institution for

the award of any degree/diploma/certificate.

Principal Advisor: Yitbarek Takele (PhD) Bair Dar University College of Business and Economics Department of Management Signature Date

……………………………. ……………………….

Co- Advisor: Demeke Gadissa (MA) Bair Dar University College of Business and Economics Department of Management Signature Date

…………………………….. ………………………….


v

BOARD OF EXAMINERS

BAHIRDAR UNIVERSITY

COLLEGE OF BUSINESS AND ECONOMICS





BY

MESFIN RAJI KILTU

Approved by the Board of Examiners:

Advisor Signature

…………………………………………….. ………………………..

External Examiner Signature

-------------------------------------- ---------------------

Internal Examiner Signature

-------------------------------------- --------------------


vi

ABSTRACT

The study aimed at determining the level of Organizational Climate (OC) as

perceived by the civil servants and finding out whether there is meaningful

relationship between OC and Organizational effectiveness (OE). A standardised

OC measurement questionnaires developed by Patterson et al (2005) based on

Competing Values Model (CVM) and instrument of Speier & Venkatesh (2002)

were used in collecting data. Hence, 348 questionnaires booklets were distributed

to 6 public organizations in Amhara National Regional State (ANRS) and 260

questionnaires were returned, with an effective response rate of 75%. The collected

data was analyzed using parametric statistical tools to test the hypotheses in

SPSS. To this end, multiple linear regressions, Pearson’s Product-Moment

Correlation Coefficients, Independent-samples t-test, and One-way ANOVA was

adopted.

Overall, it was found that (a) the independent aggregate variables; Human

Relations Values (HRV) and Open Systems Values (OSV) positively & significantly

predicted the dependent variable (OE) and 32.5% of the variation in OE is

explained by HRV & OSV combined on the half segment of the Competing Values

Model (CVM); (b) the dimensions Integration, Involvement, Supervisory Support,

Training and Welfare have shown significant positive correlation with their

respective HRV domain of OC; (c) the dimensions Innovation & Flexibility,

Outward Focus, and Reflexivity have shown significant positive correlation with

their respective OSV domain of OC; and (c) there is no significant difference

exhibited in employees gender, tenure, education level, and work processes in

terms of employees perception of OC and OE. On other hand, there is significant

difference found in employees’ perception in the type of organizations in terms of

OE and OSV of the OC in which nine (20%) out of 45 tests conducted revealed

statistically significant differences in the perception of organizational climate

between organizations. However, with regard to HRV, no significance difference

observed in employees’ perception across public organizations.

The research results will have implications for policy makers and future

researches in that it might contribute for a fundamental improvement in

efficiency and performance of organizations and reduced turnover of employees.


vii

ACKNOWLEDGEMENTS

I am extremely grateful to my supervisors Dr Yitbarek Takele and Mr Demeke

Gaddissa for their guidance and continuous follow up in the entire process of

the thesis work without which this thesis could not have been completed.

I am also grateful for the Amhara National Regional Government for providing

me the opportunity to participate on the study program, staff of Amhara

Management Institute and coordinator of this especial post graduate study

program in EMBA at BDU who made the program run & successfully

completed.

I wish to thank all those who contributed directly and indirectly to this study,

and helped me conclude this research project. In particular the following

individuals deserves worth to be mentioned on facilitating data collection

process: Mr Kebede Yimam and Mr Sileshi Kume from Bureau of Environment

Protection & Land Administration; Mr Tefera Feyessa, Mr Fanta Moges & Mr

Dagnew Asmare from Bureau of Education; Mr Tilahun Arega & Mr Getahun

Ayalew from Bureau of Technical & Vocational Training; Mr Birhanu Gebre, Mr

Kassahun Molla, & Mr Adamu Bogalle from Bureau of Culture Tourism & Parks

Development; Mr Gared Legesse & Mr Chilot Amare from Office of General

Auditor; and finally, Mr Ashagrie Zewdie from Bureau of Women, Youth &

Children Affairs.

At Last but not least, my sincere thank goes to Mr Tefera Tegegne for

proofreading my manuscript and Ms Hizbalem Kebede for her unreserved

secretarial support she provided to me not only for my thesis but throughout the

learning process.

I reserve my final gratitude for my caring family, my wife Martha Desalegn and

my son, Biniyam. They have given me so much motivation, support and

encouragement, together with their love, patience, and the acknowledged

sacrifice of quality family time during my EMBA course. This dissertation

belongs more to them than to me.


viii

ACRONYMS

ANRS

BoCS

BoCTPD

BoE

BoEPLA

BoFED

BoTVT

BoWYCA

BPR

CSA

CSRP

CVM

GTP

HRV

OC

OE

OGADT

OSV

PSCAP

Amhara National Regional State

Bureau of Civil Service

Bureau of Culture Tourism & Parks Development

Bureau of Education

Bureau of Environment Protection & Land Administration

Bureau of Finance Economic Development

Bureau of Technical & Vocational Training

Bureau of Women, Youth & Children Affairs

Business Process Reengineering

Central Statistics Agency

Civil Service Reform Program

Competing Values Model

Growth Transformation Plan

Human Relations Values

Organizational Climate

Organizational Effectiveness

Office of General Auditor

Open Systems Values

Public Service Capacity Building Program


ix

TABLE OF CONTENTS

Contents Page DECLARATION .................................................................................... iii

CERTIFICATION .................................................................................. iv

BOARD OF EXAMINERS ...................................................................... v

ABSTRACT ........................................................................................... vi

ACKNOWLEDGEMENTS .....................................................................vii

ACRONYMS ......................................................................................... viii

TABLE OF CONTENTS ......................................................................... ix

LIST OF TABLES ................................................................................ xiii

LIST OF FIGURES .............................................................................. xiii

LIST OF APPENDICES ........................................................................ xiv

CHAPTER I - THE PROBLEM AND ITS APPROACH ........................... 1

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

1.2. STATEMENT OF THE PROBLEM ............................................................. 7

1.3. OBJECTIVES ........................................................................................... 9

1.4. RESEARCH QUESTIONS ....................................................................... 10

1.5. RESEARCH DESIGN & METHODOLOGY ................................................ 10

1.5.1 Nature and Sources of Data ............................................................. 10

1.5.2. Sampling technique & sample size Determination .............................. 11

1.5.3. Method of Data collection ................................................................ 14

1.5.4. Method of Data analysis .................................................................. 16

1.5.5. Definitions and explanation of terms ................................................ 17

1.5.6. Validity & Reliability Tests ............................................................... 19

1.5.7. Variables of the study and Conceptual framework ............................. 21

1.5.8. Research hypotheses ........................................................................ 22

1.6. SIGNIFICANCE OF THE STUDY ............................................................. 23

1.7. SCOPE OF THE STUDY .......................................................................... 24

1.8. LIMITATIONS OF THE STUDY .............................................................. 25

1.9. ORGANIZATION OF THE PAPER ........................................................... 27

CHAPTER II – REVIEW OF RELATED LITERATURE ....................... 28

2.1. INTRODUCTION ................................................................................... 28

2.2. THEORETICAL FRAMEWORK ............................................................... 28

2.2.1. Overview ........................................................................................ 28


x

2.2.2. Definitions of Organizational Climate ............................................... 30

2.2.3. The emergence of Competing Values Model ....................................... 31

2.2.4. The link between Competing Values Model and Organizational Climate35

2.2.5. The relationship of Organizational Climate and Culture ..................... 36

2.2.6. Importance of Organizational Climate .............................................. 39

2.2.7. Factors affecting Organizational Climate .......................................... 41

2.3. CRITICAL REVIEW OF EMPIRICAL STUDIES ........................................ 44

2.3.1. Organizational Climate and Organizational Effectiveness .................. 44

2.3.2. Validation of instruments ................................................................ 46

CHAPTER III – OVERVIEW OF THE ANRS ...................................... 47

3.1. INTRODUCTION ................................................................................... 47

3.2. DEMOGRAPHIC SITUATION ................................................................. 47

3.3. NATURAL BEAUTY ............................................................................... 47

3.4. ECONOMIC ACTIVITY ........................................................................... 48

3.5. HUMAN RESOURCE ............................................................................. 48

3.6. THE CIVIL SERVICE REFORM............................................................... 49

3.6.1. The Public Service Capacity Building Program .................................. 49

3.6.2. Business Process Reengineering ....................................................... 50

CHAPTER IV: DISCUSSION AND ANALYSIS .................................... 52

4.1. INTRODUCTION ................................................................................... 52

4.2. DESCRIPTIVE STATISTICS: AN OVERVIEW ........................................... 52

4.2.1. Demography of Respondents............................................................ 53

4.2.1.1. Gender ..................................................................................... 53

4.2.1.2. Business Processes .................................................................... 53

4.2.1.3. Education................................................................................. 54

4.2.1.4. Tenure ..................................................................................... 55

4.2.2. Descriptive Statistics ....................................................................... 55

4.2.3. Summary ....................................................................................... 60

4.3. VALIDITY ANALYSIS ............................................................................. 60

4.3.1. Human Relation Values ................................................................... 61

4.3.1.1. Integration ............................................................................... 62

4.3.1.2. Involvement ............................................................................. 63

4.3.1.3. Supervisory Support ................................................................. 64

4.3.1.4. Emphasis on Training ............................................................... 64

4.3.1.5. Welfare .................................................................................... 65

4.3.2. Open System Values ........................................................................ 65

4.3.2.1. Innovation & Flexibility ............................................................. 66


xi

4.3.2.2. Outward Focus ......................................................................... 67

4.3.2.3. Reflexivity ................................................................................ 67

4.3.3. Organizational Effectiveness ............................................................ 68

4.4. RELIABILITY ANALYSIS ....................................................................... 69

4.4.1. Human Relations Values .................................................................. 70

4.4.1.1. Integration ............................................................................... 70

4.4.1.2. Involvement ............................................................................. 71

4.4.1.3. Supervisory Support ................................................................. 71

4.4.1.4. Emphasis on Training ............................................................... 71

4.4.1.5. Welfare .................................................................................... 72

4.4.2. Open Systems Values ....................................................................... 72

4.4.2.1. Innovation & Flexibility ............................................................. 72

4.4.2.2. Outward Focus ......................................................................... 73

4.4.2.3. Reflexivity ................................................................................ 73

4.4.3. Organizational Effectiveness ............................................................ 73

4.5. HYPOTHESIS TESTING ......................................................................... 74

4.5.1. Testing of Hypothesis One (effects between variables) ........................ 74

4.5.1.1. Nature & Strength of the Effect .................................................. 75

4.5.1.2. Explanation of the hypothesis .................................................... 77

4.5.2. Testing of Hypothesis Two (relationships between variables) ............. 78

4.5.2.1. Nature & Strength of Relationship ............................................. 78


4.5.3. Testing of Hypothesis Three (relationships between variables) ........... 81

4.5.3.1. Nature & Strength of Relationship ............................................. 81


4.5.4. Testing of Hypothesis Four (difference between gender) ..................... 84

4.5.4.1. Nature & Strength of Difference ................................................. 84


4.5.5. Testing of Hypothesis Five (difference between tenure) ...................... 86



4.5.6. Testing Hypothesis Six (difference between education level) ............... 88



4.5.7. Testing Hypothesis Seven (difference between organization type) ....... 89




xii

4.5.8. Testing of Hypothesis eight (difference between work groups) ............ 92



CHAPTER V – SUMMARY, CONCLUSIONS & RECOMMENDATIONS ....................................................................... 95

5.1. INTRODUCTION ................................................................................... 95

5.2. SUMMARY ............................................................................................ 95

5.3. CONCLUSION ..................................................................................... 102

5.4. IMPLICATIONS AND RECOMMENDATIONS ........................................ 105

5.4.1. Implications for research ............................................................... 105

5.4.2. Recommendations for future research ............................................ 106

REFERENCES ................................................................................... 108

APPENDICES .................................................................................... 116


xiii

LIST OF TABLES

Table 1-1: Sample Selection & Distribution for organizations and respondents .......... 14

Table 2-1: Distinguishing Factors of the two approaches of the CVM ........................ 34

Table 2-2: Research Summary Made on OC by various researchers .......................... 42

Table 4-1: Descriptive Statistics for Gender of Respondents ..................................... 53

Table 4-2: Descriptive Statistics for Work processes of Respondents ........................ 54

Table 4-3: Descriptive Statistics for Education of Respondents ................................ 55

Table 4-4: Descriptive Statistics for Tenure of Respondents ..................................... 55

Table 4-5: Descriptive Statistics for Sub-scales of HRV ........................................... 57

Table 4-6: Descriptive Statistics for Sub-scales of OSV ............................................ 58

Table 4-7: Descriptive Statistics for HRV, OSV and OE ........................................... 59

Table 4-8: Case wise diagnostics of constructs ........................................................ 60

Table 4-9: Coefficients Result ............................................................................... 75

Table 4-10: Model Summary for the Strength of Relationship .................................. 77

Table 4-11: Pearson Correlations of dimensions with Human Relations Values .......... 79

Table 4-12: Pearson Correlations of dimensions with Open Systems Values .............. 82

Table 4-13: Independent-Samples T-test for Gender ............................................... 85

Table 4-14: One-Way Independent ANOVA test for Tenure ..................................... 87

Table 4-15: One-Way Independent ANOVA test for Education level.......................... 88

Table 4-16: One-Way Independent ANOVA test for Organization Type ..................... 90

Table 4-17: Strength of difference for organization types ......................................... 91

Table 4-18: Independent-Samples T-test between for Work Processes ...................... 93

LIST OF FIGURES

Figure 1-1: Sampling Frame Distribution based on Performance of Organizations ..... 13

Figure 2-4: Research Model Adapted from Natural System Model of CVM ............... 22

Figure 2-1: The Competing Values Framework ....................................................... 32

Figure 2-2: The Alternative Competing Values Framework ...................................... 34

Figure 2-3: The CVF and Culture .......................................................................... 38

Figure 4-1: Relationship between HRV and OSV on Organizational Effectiveness ..... 75

Figure 4-2: Relationships of Dimensions of OC with HRV ....................................... 79

Figure 4-3: Relationships of Dimensions of OC with OSV ........................................ 82


xiv

LIST OF APPENDICES

APPENDIX- A: List of Public Institution used for Sampling of Respondents ........... 116

APPENDIX- B: Determination of Respondents Sample ........................................ 117

APPENDIX- C: Questionnaire of the Study .......................................................... 118

APPENDIX- D: SPSS Chart Outputs of all Variables ............................................. 121

APPENDIX- E: Factor Analysis for Multifactor & Single factor structures ............... 132

APPENDIX- F: Item Loading for the Single Factor for HRV & OSV ........................ 135

APPENDIX- G: Item Loading for the Single Factor for Sub-scales of HRV & OSV .... 136

APPENDIX- H: Reliability Statistics for all Variables ............................................ 137

APPENDIX- I: SPSS Outputs of Regression Charts ............................................... 141

APPENDIX- J: Homogeneity test of Variance for Grouping Variable ...................... 142

APPENDIX- K: Suggestion of Intervention Strategies by Respondents ................... 143


1

CHAPTER I - THE PROBLEM AND ITS APPROACH

1.1. BACKGROUND OF THE STUDY

The environment of the early twentieth century was considerably more stable

and predictable than today’s. That is why Thomas (2009:19-20) stress the need

for strong sense of purpose by organizations and allow workers to take active

responsibility for handling more and more of the uncertainties involved in the

accomplishment of their purposes. As many of today’s businesses continue to

struggle to survive or remain competitive, it becomes important for managers to

better understanding of the factors that influence employees and important

employee-oriented work outcomes (Allison & Kaye 2005). Therefore,

individuals’ perceptions provide a starting framework for perceiving the

organization's current situation.

The growing significance placed on understanding of employees and

their behaviour within the organization has produced a great deal of interest in

investigating employees perceptions of climate within the organization (Riggle

2007) especially, at times when significant change is taking place. In our society,

we spend quite a bit of time in either public institutions, business enterprises, or

religious institutions. Therefore, the environment surrounding the individual

bears significant influence personally and professionally.

From human behaviour perspective, we learnt that people have their own

perceptions, feelings and attitudes towards the organisation. Vijayakumar

(2007) argued that climate in an organization evolves out of collective

perceptions of employees on various aspects of the organizational work life and

stressed organizational climate as indisputably a major contributing factor for


2

changing employees’ attitudes and behaviour towards superior job performance

and satisfaction. Hence, it is understandable that a person perception shapes his

attitudes to behave in a particular way. In fact, what does “perception” is all

about? How do it impart on factors of individual and group behaviours and

influence organizational effectiveness? These are the keenly awaiting answers

from the nomenclature of management theories.

According to Robbins (2004), perception can be defined as ‘a process by

which individuals organise and interpret their sensory impressions in order to

give meaning to their environment’ based on their perception of what reality is,

not on reality itself. Of course, perception affects our working relationships in

many ways relating to the factors of individual, group or organisational

behaviour. For example, based on the perceiver, context and target we may have

the perception that the management under which we are working are no good at

managing the job. Therefore, we may tend to avoid working with them, in fear of

held responsible for their failures, and in doing so, affecting our working

relationship with work environment, and ultimately, the effectiveness and

efficiency of the organisation.

Employee perceptions of organizational climate (OC) and work

experiences have become one of the most researched aspects of management.

According to Schneider & Snyder (1975) each individual perceives or

conceptualizes his organization in any number of ways, depending upon the

context and the set of information about the organization which is operative for

that individual. In this regard, climate is the employees’ perception of how it


3

feels to work in the unit, and includes specific aspects of the environment that

directly affect people's ability to get the job done (Mullins 2005).

The difference in perception is explained by Doherty & Horne (2002) as

it might be because of missing, or misconstruing, some of the stimuli since a

person’s perception is the way they select, organize and interpret stimuli.

Therefore, just as the perceptions of the individual are at the centre of any

behavioural intervention in OC, so are the perceptions of the characteristics of

the organization, by the members of the organization, central to the diagnosis of

organization's problems and dysfunctions. This in turn will lead us in

contemplating and understanding of how the OC as perceived by employees in

public sectors is antecedent of the organization’s effectiveness.

Managers in public sectors so far have concentrated on accountability

and high performance and have sought to restructure bureaucratic agencies,

redefine organizational missions, streamline organizational processes, and

decentralize decision-makings. Two of the more significant shifts in the 21st

century have been the increased attention to the delivery of public services on

the one hand, and greater decentralization of responsibility for these services on

the other (Ahmad et al. 2005). These facets of the service delivery have brought

about much attention in public sectors to be more accountable and meet the

expectations of the citizens.

Arguments on adopting some limited new forms of commercial

principles that may improve service delivery like outsourcing of some sections of

an organisation’s activities in security, cleaning and property management

could have a significant impact on changing the routinely entrenched mode of


4

service delivery (K. Brown et al. 2000). Such kind of collaboration at their face

value could be advantageous for citizens’ demands. Entwistle & Martin (2005)

argue that the turn to partnership marks an important departure in service

delivery and they insist as a proposition partnership that delivers a

transformational approach to service improvement. However, they fail short to

dictate explicitly the peculiarity and modalities in formulation of the

partnership. Across the public and private sector bridge, this characteristic of

open systems facilitates teaming with stakeholders and encouraging the

formation of partnerships.

Nowadays a new paradigm for public management has emerged, aimed

at fostering a performance-oriented culture in a less centralized public sector in

which the Ethiopian Government has tried to implement as pilot New Public

Management (NPM) initiative and now in the process of drafting as new Human

Resource Development Policy (MoFED 2012; Abay & Perkins 2010). This ‘new

paradigm’ is often referred to as new public management that focus upon

achieving qualitative service improvement, from a citizen perspective, whilst

maintaining an overt focus upon bottom-line financial performance (Milner &

Joyce 2005; Abay & Perkins 2010). The new policy document is currently under

thorough review and discussion before submitted to the legislative bodies

(MoFED 2012).

Some of the critics of NPM which are outlined by Desta (2008) are: no

clear definition what New Public Management is, the concept is loose and

multifaceted and offer a kind of shopping basket of various elements for

reformers of public administration, and some of the theoretical justifications are


5

also highly questionable. Above all, NPM tends to bread management not

necessarily in terms of numbers rather the search for more effective means of

control in the name of accountability. This final conclusive remark of Desta, as

“means of control” is against the very essence of flexibility in a world of

uncertainty that demands proactive measures. In recent times, agitated by

persistent citizen tastes and requirements the hostile environment chases public

sectors beyond their expectation.

The new public service demands nothing more than satisfying the

customers. However, in differentiating the new public service from the old

public administration, the following invaluable principles are overriding (R. B.

Denhardt & J. V. Denhardt 2000:553-556). Serving, rather than steering;

Making the public interest as the aim, not the by-product; Thinking

strategically, and acting democratically; Serving citizens, not customers;

Understanding that accountability isn’t simple; Valuing people, not just

productivity; and finally, Valuing citizenship and public service above

entrepreneurship. Without an adequate understanding of OC or culture, many

well-intended leaders have led organizations to their demise since OC

represents one of the first widely studied concepts to address the social context

in organizations (Agard 2011: 611- 612).

An attempt had been made to establish interrelationship between OC and

its effect on performance and their attitudes of the civil servants. This is done

based on best instruments available after proper adaptation. According to Lok &

Crawford (1999), various researchers have confirmed that bureaucratic and

stable environment often resulted in a lower level of employee commitment


6

(Brewer 1994; Kratina 1990; Wallach 1983) and performance (Krausz et al.

1995; Trice & Beyer 1993).

The public administration scenario in ANRS, driven by the civil servants,

who are the main change agents through efficient service delivery, undergoes so

many strains and stresses during the discharge of their duties (BoCS 2010). OC

surveys routinely show that about 75 percent of working adults report that the

most stressful aspect of their job is their immediate boss (J. Hogan et al. 2009).

Another findings studied by Vijayakumar (2007) implied that the role of

management style in shaping climate perceptions of employees is crucial to

advocate the case for strengthening participatory approach in the management.

OC is a relatively an enduring quality of the internal environment of an

organization that is experienced by its members, influences their behaviour, and

can be described in terms of the values of a particular set of characteristics (or

attributes) of the organization (Mullins 2005).

In this study, the author tries to explore the concept of OC from the

viewpoint of employees’ sensation that resides in the prevailing psychological

environment of public institutions and the relevancy for quality and change

initiatives. Civil Servants are a vital part of our work environment. Therefore,

the purpose of this study is to investigate how the organizational values are

influenced by OC factors as perceived by employees and determine its

implications for organizational effectiveness that in turn bring about job

satisfaction and improved performance and understand how employees

perception mould the quality of the working situation emanating from their

interaction.


7

1.2. STATEMENT OF THE PROBLEM

It is an undeniable fact that the public administration in ANRS is not

delivering well despite the fact that government effort to rejuvenate the system

through the managerial cult of BPR is still ongoing and the overall change

implementation process is yet at its infancy stage (BoCS 2010). According to

Hammer & Stanton (1995) full implementation of BPR across all the processes

of the business units of an organization can take many years (can easily last five

to seven years, or even longer). The deterioration in the work environment and

ineffectiveness of the whole public administration can be attributed not only to

the poor conduct of civil servants working in the organizations but it might also

be attributed to the lack of determination and failure of the leadership in

creating conducive OC which deemed to be one of its crucial responsibility.

This brings us to a point where thorough examination of the work

environment is needed to identify causes of this debacle. Effectiveness of the

public administration depends mainly upon the civil servants who are

responsible for running it according to the set goals. The efficiency of the civil

servants depends upon the extent and nature of their professional readiness for

the performance of their jobs. It is not sufficient, however, that the civil servants

merely have the required knowledge and skill or credentials only. It is essential

that they should have an adequate understanding of servant attitude and the

need to discern the underlying reasons and source of their payments besides

having the mandatory requirement of some desirable level of mastery in the job

in which they are assigned. That is why after reviewing empirical research about

public service motivation conducted during the last two decades, Perry et al.


8

(2010) concluded that at the heart of the construct is the idea that individuals

are oriented to act in the public domain for the purpose of doing good for others

and society.

Even though the ANRS public administration change process is in a

mediocre stage; the lack of discipline in government institutions, substandard

accountability, unmotivated employees, redeployment, idleness all contribute to

poor performance of civil servants seems to aggravate the situation unless

possible measures put in place to circumvent the mishaps. Furthermore, the

new result oriented approach of outcome based public administration,

rudimentary management style of the leadership, flatten organizational

structures, the high customer expectation, coping with current political and

ambitious developmental aspirations, and eradication of unethical behaviors

and practices from public service sectors are believed to cause stress on civil

servants. This in turn will lead to poor performance, high turnover and

customer dissatisfaction.

In most cases the leadership evidently denied accountability and easily

put the whole blame on employees’ poor efficiency and lack of commitment.

Apart from the necessity of having the leadership and subordinate irreplaceable

relationships and technical competency little attention is usually paid to the

underlining context of the work environment whether it favors or degrades

employees’ morale. Therefore, the turning point of all fallacies and undesirable

manifestations is looking into the context of the work environment and amend

the irregularities. A recent survey concludes that public service delivery in

Ethiopia can be improved if the commitment, ownership, and the drive for


9

change are in place (Mengesha & Common 2006; Beyene 2007). In conviction

of the researcher, this can be realized if the context of the working environment

is found to be favorable to employees to bring job satisfaction and boost their

morale. From this OC takes the major share.

1.3. OBJECTIVES

The main objective of the study is to determine the nature and strength of

perception of OC in relation to the human relations (internal focus) and open

systems (external focus) of flexible organizational orientation of OC as perceived

by the civil servants of the ANRS.

The specific objectives of the study are:

a) To determine the influence of Human HRV and OSV domains of

flexible orientations of OC on OE of Public sectors as perceived by

employees.

b) To determine the relationship that exists between the dimensions of

OC and the aggregated HRV and OSV domains of OC respectively,

and determines the dominant factor in each category.

c) To find out if there is a significant difference in employees’

perceptions of OC in terms of employees’ gender, tenure, education

level, organization type, and work processes in human relations

values, OSV and Organizational effectiveness of OC across public

sectors.

d) To recommend a future research area that capitalizes on the findings

of this research and to lay ground for future localized empirical

research on similar topics.


10

1.4. RESEARCH QUESTIONS

The study is aimed at answering the following research questions;

1. To what extent do HRV & OSV of OC influence organizational

effectiveness ANRS public services?

2. Is there any significant positive relationship between the dimensions of

OC and HRV (internal focus) of flexible orientation?

3. Is there any significant positive relationship between the dimensions of

OC and OSV (external focus) of flexible orientation?

4. What is the dominant factor of OC influencing employees’ perception in

public sectors of ANRS?

5. Is there any significant difference between employees’ perception of OC

in terms of employees’ gender, tenure, education level, organization type,

and work processes in HRV, OSVand OE across public sectors in ANRS?

1.5. RESEARCH DESIGN & METHODOLOGY

1.5.1 Nature and Sources of Data

The research design fall under the broad category of positivist studies

since its goal is to test the hypotheses proposed. A mixed research design of

qualitative and quantitative is used as it aided the researcher in analysing the

areas that impart employees’ perception towards OC and to scope out the

magnitude or extent of a particular phenomenon, problem, or behaviour. Even

though this research is qualitative in nature, data were collected using

quantitative research methods, as a quantitative approach was more

appropriate and the study involved the generation of data in quantitative form,

which is subject to rigorous quantitative analysis.


11

A cross-sectional field survey adopted to collect primarily quantitative

data such as numeric scores and biographic metrics. Field surveys are non-

experimental designs that do not involve controlling for or manipulating

independent variables or treatments (Bhattacherjee, 2012) and it is convenient

to capture snapshots of practices, beliefs, or situations from a random sample of

subjects in field settings through a survey questionnaire. In the process,

independent and dependent variables were measured at the same point in time

using a single questionnaire.

According to C. Hutchison (2000) mentioned in Silberman (2001), there

are a number of data collection and analysis tools that can provide information

about the status of an organization. The survey used climate survey or attitude

survey in which it assesses employees’ current feelings and opinions within the

organization regarding factors of OC and employees’ commitment.

The study used mainly primary observational data sources i.e. personal

feelings & sensation collected through self-administered questionnaire of cross-

sectional survey. The sources of the primary data were all type of individual

government civil servants excluding political appointees in the selected sampled

public sectors.

1.5.2. Sampling technique & sample size Determination

In a positivistic study a representative or good sample is one in which the

results obtained for the sample can be taken to be true for the whole population

that can be able to generalise from the results. A good sample must be chosen at

random (every member of the population must have a chance of being chosen),

large enough to satisfy the needs of the investigation being undertaken, and

unbiased (Collis & Roger Hussey 2003). However, many of the above methods


12

present problems of sample bias, mainly because in a sampling frame we cannot

identify unambiguously in advance. In other words, the sample will not be

representative of the population as a whole. Therefore, in a positivistic study,

attempts are usually made to minimize the bias through justification of the

sample selection method.

In this study, taking the viability and representativeness of the sample,

and resource constraints into consideration a two step process was followed in

the selection of the respondents. First, the number of organizations was

sampled due to the homogeneity in work cultures across public sectors.

Therefore, for every ten only one organization was taken as representative

sample allowing equal chance of selection through random sampling from each

stratum. In the second step, however, the respondents sample size was

determined from the total number of employees in the thirty six organizations

and subsequently allocating the calculated figure to the selected organizations in

the first step proportionately.

The stratification was done taking into account their difference in

performance evaluation rankings in Civil Service Reform Program (CSRP)

implementation, formally evaluated by the formerly known Regional Capacity

Building and Civil Service Bureau1 (Amare et al. 2010). Thirty-seven

organizations took part in the evaluation of BPR implementation among which

one organization latter had dissolved (See APPENDIX- A).

The thirty-six organizations were classified based on the normal

distribution curve of their rankings, which shows a mean of 62.21% and

1 The report was dispatched in circular Ref No. አግሲስ/2/8/87 dated 04/08/2002EC


13

standard deviation measure of 8.08%. Assuming that the data is almost

normally distributed as it fulfills the condition set in the central limit theorem,

and transforming the data into standardized form and taking the standard

values of Z-scores as cut-off between +/- 1.00 and +/- 2.00 points, 20

organizations (55.56%) fall within the middle pile of the distribution curve, 7

organizations (19.44%) fall within the left 97.22% tail of data distribution,

another 8 organizations (22.22%) fall within the right 97.22% tail of data

distribution, and only one organization fall outside the right extreme end of the

97.22 % tail of the data distribution curve. Figure 1-1 shows the normal

distribution curve of the sampling distribution of organizations.

Figure 1-1: Sampling Frame Distribution based on Performance of

Organizations

Hence, a sample size of 348 individual respondents was determined

which were drawn from all work processes in random sampling out of the total

3,656 employees of the thirty six organizations proportionately using a formula

for Sampling (Renckly 2002: 25)(see APPENDIX- B).

Accordingly, the specific sampling distribution and sample sizes are

depicted in the following table;

1 8 7 13 7 0 N. of Organization

A B C D E F Class


14

Table 1-1: Sample Selection & Distribution for organizations and respondents

Strata (based on Z scores)

No. of Organiz

ation

Sampled Org.

Type of Work Processes &

their size

Respondent Sample

Size %

Class A (Above 1.79) 1 BoE

CP – 5 39 19% SP – 5 40 28%

TOT - 10 79 23%

Class B (1.15 to 1.79) 8 BoTVT

CP – 4 16 8% SP – 5 17 12%

TOT - 9 33 9%

Class C (0 to 1.14) 7 BoEPLA

CP – 5 26 13% SP – 5 23 16%

TOT - 10 49 14%

Class D (0 to -1.14) 13 BoCTPD

OGADT

CP – 4 105 52% SP – 5 48 33%

TOT - 11 153 44%

Class E (-1.15 to -1.79) 7 BoWYCA

CP – 5 17 9% SP – 4 17 11%

TOT - 9 34 10%

Class F (Below -1.79) 0 0

0 0 0 0 0 0 0 0 0

36 6

CP – 5 203 58% SP – 6 145 42%

TOT - 11 348 100% Note: CP – Core Process & SP – Support Process Source: Researcher’s own computation

1.5.3. Method of Data collection

The study adopted the standardised, structured and validated OC

measurement developed by Patterson et al (2005) based on competing values

model (CVM). Only the flexible orientation values of HRV and OSV were tapped

from the measurement. OE is measured indirectly using proxy variable

organizational commitment measurement developed by (Speier & Venkatesh

2002), which is adapted from (O’Reilly & Chatman 1986). Organizational

commitment has been identified as a useful measure of OE explaining the work-

related behaviour of employees in organizations” (Iqbal 2007; Steers 1977) and


15

the scales believed to measure the three basic components of organizational

commitment; identification, involvement, and loyalty.

Overall, the 8 dimensions of the OC measures comprised of 37 Likert-

type items having a proven regression weight of 0.6 and above, the minimum

recommendation (Hair et al. 1998; Vijayakumar 2007) were tapped from HRV

and OSV of the CVM. For organizational commitment measure three Likert-

type items, which previous researchers Speier & Venkatesh (2002) have found

an acceptable reliabilities of (α = 0.75 – 0.83) were used. The response formats

for both types of measures use a 5 point, Likert-type scale from 1- Strongly

Disagree to 5- Strongly Agree.

Both measures, translated into local language Amharic and put into a

single questionnaire, since more than 85% of the respondents are believed to be

undergraduates, questions in English language might not produce the required

response and assumed to limit their participation on the survey. A Group of

three linguistics professionals carried out the translation meticulously

preserving the dialects and original positive/negative wording of the English

language (see APPENDIX- C).

The demographic questions put at the beginning of the questionnaire,

though there is some debate regarding the best location for the classification

questions which ask about the respondent’s sex, education, etc. Some authors

believe that they are best placed at the beginning, so that respondents gain

confidence in answering easy questions; others prefer to place them at the end,

so that the respondent starts with the more interesting questions. However,

Collis & Roger Hussey (2003:175) advised that unless your questions have a


16

large number of classification and are of a sensitive nature, it may be best to

start with the non-threatening classification questions.

At the end of the questionnaire, a filtering question was provided using

nominal and ordinal scale measures to crosscheck the consistency and

genuineness of the responses. It also serves gather respondents opinion on the

areas of possible improvement of OE.

The questionnaire was prepared in two formats, in hard copy ballpoint

format for personal contact and electronic format. Adobe Acrobat X Pro

software was used to design the e-questionnaire with a friendly use of drop-

down lists and button marked response platform. Data collection started on

April 11, 2012 and concluded within 10 days.

1.5.4. Method of Data analysis

The collected data were statistically analysed by means of the Statistical

Package for Social Sciences (SPSS Version 16) and the data analyses involved

both descriptive and inferential statistics.

Descriptive statistics allow researchers to present the data acquired in a

structured, accurate and summarised manner (Collis & Roger Hussey 2003:

196). The descriptive statistics utilised in this research used to analyse the

demographic data included frequencies, percentages, means, median, and

standard deviations.

Inferential analysis is concerned with the various tests of significance for

testing hypotheses in order to determine with what validity data can be said to

indicate some conclusion(s) and concerned with the estimation of population

values (Kothari 2004: 131). The following linear regression model was tested

assuming that the interaction between predictors is negligible and the effect of


17

control variables is minimal. In multiple linear regressions, the individual

relationships in any of the component regressions are linear (straight-line, not

curved, or any other shape).

Organizational Effectiveness (OE) = ƒ (Xi=1-2) where, Xi are the two aggregated

values of the OC. i.e.

Y = 𝜶𝟎 + b1 X1 + b2 X2 + є

(Where: Y = dependent variable of Organizational Effectiveness (OE) and Xi =

independent variables in which; X1 = HRV, X2 = OSV, 𝛼0 = the y-intercept, bi,

i=1-2 = regression coefficients of the two factors in explaining Y, and є = the Error

term). Hence, H0: bi, i=1-2 = 0

Therefore, the collected data were analyzed using parametric statistical

tools to test the hypotheses. To this end, Multiple Linear Regressions, Pearson’s

Product-Moment Correlation Coefficients, Independent-samples T- test, and

One-way ANOVA were used for testing the hypotheses.

1.5.5. Definitions and explanation of terms

The terminologies used in the study are defined as follows;

Human Relations: refers to the well-being, growth and commitment of the

community of workers within an organization (Patterson et al. 2005) and

understanding of the problems and anxieties of the staff and to encourage their

wider motivations to work (Rose 2005).

Open systems: refers to the interaction and adaptation of the organization to

its environment, with managers seeking resources and innovating in response to

environmental demands (Pugh & Hickson 1996).

Work process: is a set of interrelated steps that begin with an input or trigger

and end with an outcome that satisfies the end user (Linden 1998).


18

Core processes: are those that end up touching an external customer; they

occur when an employee fills a customer’s order, responds to a customer’s

complaint, or develops a new program or product (Linden 1998).

Support Processes: are internally focused, such as the process of recruiting,

hiring, and training of new employees (Linden 1998).

Integration: is the extent of interdepartmental trust and cooperation

(Patterson et al. 2005) binding the variety of experience and expertise among

members to provide a synergetic effect which can be applied to the increasingly

complex problems of modern organisations (Mullins 2005).

Involvement: is the degree to which one is cognitively preoccupied with,

engaged in and concerned with one’s present job (Paullay et al. 1994), drives

alignment and promotes teamwork.

Supervisory Support: is the extent to which employees experience support

and understanding from their immediate supervisor (Patterson et al. 2005).

Laissez-faire leadership described as a leader's disregard of supervisory duties

and lack of guidance to subordinates (Barbuto 2005) as a result in today’s

environment, the supervisory role has shifted from authoritarian to team

facilitator.

Emphasis on training: is about developing employees’ skills and proved in

Samuel & Chipunza (2009) researches that training and development as a

motivational variables were found to have significantly influenced employee

retention in both the public and private sector organisations.

Employee Welfare: is the extent to which the organization values and cares

for employees (Patterson et al. 2005) and make them feel as though their well

being is considered as a vital component of OC.


19

Innovation & flexibility: Innovation is the extent of encouragement and

support for new ideas and innovative approaches while flexibility is an

orientation toward change (Patterson et al. 2005). To survive, adapt, and gain

competitive advantage, organizations need to fully take advantage of their

employees’ innate creative potential (Zhou & George 2003), because employees’

creative ideas can be used as building blocks for organizational innovation,

change, and competitiveness.

Outward focus: is the extent to which the organization is responsive to the

needs of the customer and the marketplace in general (Patterson et al. 2005).

Reflexivity: is a concern with reviewing and reflecting upon objectives,

strategies, and work processes, in order to adapt to the wider environment

(Patterson et al. 2005).

1.5.6. Validity & Reliability Tests

Pilot study was carried out using convenient selection method on four

public organizations having the same characteristics with the participants of the

main study. The advantages of doing a pilot study include; it helps to detect

potential defects in the measurements procedures, it assists in identifying

ambiguous items, and it allows the researcher to become aware of non-verbal

behaviours that may occur due to the wording of questions (Singh 2009).

In fear of the boredom that may inflict on the participants, only one

organization was included from the sampling frame and the remaining three

were outside the sample frame. Since, the intention was to undertake the pilot

study on 20% of the sample size and hence, after randomly identifying and

having the list of email address of the participants, 68 questionnaires (splitting

evenly for both ballpoint and email filling) were distributed to the participants,


20

which were drawn from all work processes of the organizations. Eventually, 37

questionnaires were returned with a response rate of 54.4%.

The low response rate of the email filling, 26.5% as compared to 82.4%

for the hard copy was the first lesson learnt from the pilot study to rely only on

the ball-point and exclude the electronic questionnaire format. The second

lesson, it was learnt that no complains reported on the clarity and ambiguity of

wording of the questions. Thirdly, with regard to the psychometric properties of

the questionnaire, most items under their respective nine constructs has shown

a reliability measure, Cronbach's Alpha, within an acceptable range of .694 to

.873 except for one construct, Training, with low alpha value of .453 and

another, Integration, with a negative value. One question was identified as the

cause of low alpha value in the Training construct as there would be a possibility

of raising the alpha value to .673 if it had been eliminated there of.

The validity of the measurement during the pilot study was assessed

using the Kaiser–Meyer–Olkin measure of sampling adequacy (KMO) in

principal component analysis that represents the ratio of the squared

correlation between variables to the squared partial correlation between

variables. This had been done as KMO is another alternative way of gauging of

the substantive importance of a given variable to a given factor. Kaiser (1974) as

cited in Field (2009) recommends accepting values greater than 0.5 as barely

acceptable because values below this imply to either collect more data or rethink

what variables to include.

Hence, the KMO values obtained in the pilot study fall within the range

of .519 to .822 except for one construct, Integration that shown negative alpha

in reliability again showed KMO of .439, which is below the recommended


21

threshold value. However, it was decided latter to maintain Integration with the

Training construct that showed low alpha value though suspected of reasons

that may arise from the lax behaviours of respondents and the small sample size

used coupled with low response rate in the pilot study might have affected the

results.

1.5.7. Variables of the study and Conceptual framework

Organizational commitment that was selected as a proxy variable to measure

Organizational Effectiveness (OE) was considered as a dependent variable. The

sub-scales (dimensions) of the HRV domain (Training, Welfare, Integration,

Involvement, and Supervisory support) and OSV domain (Reflexivity, Outward

focus and Innovation & Flexibility) of OC were considered as first-order

independent variables. The aggregated domains of HRV and OSV were

considered as the second-order independent variables.

In the study, demographic variables such as sex, educational level, type of work

process in which the respondents are assigned, and tenure were considered as

control variables. Prior studies have demonstrated that these demographic

variables are potential predictors of organizational commitment (Avolio 2004).

Having a thorough review of earlier researches and noting the dearth of

empirical works in African work environment especially on public servants, this

study geared to focus in filling the gaps that is sought in the aforementioned

areas.

Figure 2-4 in the next page portrays the conceptual research model that

is formulated to rejuvenate the main elements of the study.


22

Figure 2-2: Research Model Adapted from Natural System Model of CVM

This study was based on the premise that OC perceptions contribute to

groups and organizational effectiveness and would try to test the propositions

that positive climate perceptions would improve, and negative climate

perceptions would deteriorate group and organizational effectiveness.

Therefore, the study tried to shade light on identifying the blurred areas of

confrontation between management and employees in the work environment in

terms of flexible orientations of OC i.e. HRV and OSV.

1.5.8. Research hypotheses

The study proposes to test the following eight hypotheses:

1) The aggregated HRV & OSV of OC do not predict the organizational

effectiveness, which is measured by employees’ organizational

commitment.

Innovation & Flexibility

Outcome Organizational effectiveness

Integration

Involvement

Supervisory support

Training

Welfare

Outward Focus

Reflexivity Open systems (External Focus)

Human Relations

(Internal Focus)

Flexible Orientation of OC

Natural System Model


23

2) The dimensions of OC (Integration, Involvement, Supervisory Support,

Training, and Welfare) do not positively relate with HRV domain of

flexible orientation.

3) The dimensions of OC (Innovation & Flexibility, Reflexivity, and Outward

focus) do not positively relate with OSV domain of flexible orientation.

4) There is no significant difference between employees’ perception of OC in

terms of employees’ gender in HRV, OSV and OE across public sectors.


terms of employees’ tenure in HRV, OSV and OE across public sectors.


terms of education level in HRV, OSV and OE across public sectors.


terms of type of organization in HRV, OSV and OE across public sectors.


terms of work processes in HRV, OSV and OE across public sectors.

1.6. SIGNIFICANCE OF THE STUDY

The impetus for this study arose out of the realization that the aggressive

moves by the government to transform the country’s economy to middle-income

economy level within the coming decade, coupled with the general perception of

the necessity of creating competent public sectors and administration that

actively engaged on implementation of government policies to mobilize the

society. Hence, a more analytical approach in understanding how employees

perceive their environment and how this in turn influences their attitudes


24

towards the OE first need to be figured out to devise appropriate organizational

measures.

In this study, there are two basic factors: OC and OE. The study aimed at

determining the level of OC as perceived by the civil servants and find out

whether there is meaningful relationship between OC and OE. The study also

tries to verify whether there is difference in perception of OC within institutions

in terms of gender, tenure, educational level and work processes.

The findings of this study would serve as a basis for fostering improved

working relationships between the leadership and employees and that of

customers. It would also help the leadership of the regional government

bureaux to regulate their relationship towards their subordinates by providing

welfare facility, adequate participation, training prospects and promotion

opportunities. The results of the study will enable to acquire adequate

knowledge about the management styles of the leadership in ANRS. The

research may be helpful to the cabinet council to make intense efforts to

improve the public sector management competencies. The result of this

research will provide necessary information and more understanding about

public sectors officials’ competencies and their relation with their subordinates.

The result of this research will emphasize the need for and importance of pre-

service and in-service training of leadership for effective management.

1.7. SCOPE OF THE STUDY

The study is geographically confined to governmental public sectors of

the ANRS at the regional tier of political governance supervised by the regional

Bureau of Civil Service (BoCS) for the reason of responsibilities levied upon in


25

devising the developmental programs and put directions for the lower

administrative levels. The regional public offices are by far better than branch

offices at lower administration levels in terms of intellectual and institutional

arrangements to portray the working culture. The study also deals only on

aspects of Human relations (internal focus) and Open systems (external focus)

of flexible orientations of CVM of OC because it enables to get focussed and have

better insight and deal with the institutional adaption to the overall

organizational change process.

1.8. LIMITATIONS OF THE STUDY

One of the major limitations emerges from its scope, in spite of time

constraints and fear of bulkiness in managing the study process, the

relationship between organizational effectiveness and the control orientation’s

of organizations which represent almost half of the organizational analysis in

the CVM i.e. the Internal Process Values (IPV) and Rational Goal Values (RGV)

were not included in the set of independent variables. Since climate is best

described as employee perceptions of the organization and will be a function of

employee attitudes and values (Toulson & Smith 1994), and also Quinn (1988)

argued that a balance of competing organizational values is required for OE.

Therefore, it would have been better if the assessment is done holistically to gain

insight in light of factors of OE framed in OC.

Secondly, the study involves largely latent constructs that are not directly

measurable. Thus, though the measure is applied across a variety of

organizational types and in a variety of national contexts (Patterson et al 2005),

the inherent limitations of the questionnaire and selectivity of measurement


26

scales that was tapped from the manufacturing environment adaptation to

service industry of standardized validated measurement of such constructs

remain.

Thirdly, potential limitations that emerge from the nature of sampling;

targeting of on regional level public institutions and public servants, relatively

non-updated information used in determining the sampling frame and sample

size (true representativeness of the current situation may suffer) and the cross-

sectional nature of the data in the study. As a result, generalization of the results

may be limited. This research also relied on self-report surveys to measure

employees' perceptions of their work environment preferences, which raises the

potential for common method variance. Common method variance, in this case

refers to the problem that occurs when the same participant completes all the

measures using the same type of paper-and pencil response format (Vakola &

Nikolaou 2005). It is possible that data collected from the questionnaires do not

capture the complexity of employees’ perceptions towards their workplace

conditions. Since a quantitative design was used, qualitative data could have

added value to the research. Alternatively, a triangulation method like interview

and focal group discussion could have been employed to gather richer data to

establish the linkages of OC and OE.

Lastly, a limitation in a dearth of similar empirical researches and

relevant literatures in the area of employees’ perception of OC in Ethiopian as

well as ANRS work environments. In general, the results need to be interpreted

in the spatial, temporal, and methodological context of the study. That is, in the

country’s government institutions context and regional work culture as well as

the nature of the measurement employed for the statistical tests need to be


27

considered in interpreting the results. The use of a combination of methods also

relates to this need for flexibility in the study. Thus, the hypotheses need to be

tested in other empirical settings to garner further support.

1.9. ORGANIZATION OF THE PAPER

Chapter-I sets the tone and context of OC in the shift from old to new

public administration and outlines the reasons behind the study. It provides a

brief description about the background of the study, statement of the problem,

general and specific objectives, research questions & hypotheses, research

methodology, significance of the study, the scope, limitations and organization

of the paper.

Chapter-II provides a thorough review of related theoretical and

empirical literatures on the thematic issue of OC. The empirical evolution of

conceptual and methodological issues pertaining to research problem was

emphasised highlighting the methodological clues drawn through the literature

review.

Chapter-III addresses a brief historical retrospect about the entity of the

study, the regional government’s profile in relation to civil service reform

implementation.

Chapter-IV presents the data analysis and the most salient results

emanating from the analysis obtained in the study.

Chapter-V provides the summary and conclusions that are drawn based

on the obtained results and integrated with existing literature. Moreover,

practical implications of the research findings are highlighted and

recommendations for future research outlined.


28

CHAPTER II – REVIEW OF RELATED LITERATURE

2.1. INTRODUCTION

This chapter reassesses the literature of the theoretical basis of the framework

used in the study, Competing Values Model. Literatures on the links between

Competing Values Model and Organizational Climate, the relationship of

Organizational Climate and Culture and the importance of OC and factors

affecting OC. The chapter try to review some of the empirical studies with

regard to the subject matter in light of its connection to organizational

effectiveness.

2.2. THEORETICAL FRAMEWORK

2.2.1. Overview

Early theories of employee motivation almost completely dominated by

the assumption that the only incentives available, which are likely to exist until

today to some managers, believed to rely more on the monetary ones and

economic self-interest (Schein 2004). However, Hawthorne studies

(Roethlisberger & Dickson 1939; Homans 1950) had born the new series of

“social” assumptions, postulating that employees motivated by the need to

relate well to their peer and membership groups and that such motivation often

overrides economic self-interest (Ibid, p172). This argument is against the many

economic theories assumption that human beings are rational and employ

utility maximization based on cost and benefit expectations as a way of

understanding human behaviour (Bhattacherjee 2012).

On the contrary, political science theories, assume that people are more

political than rational, and try to position themselves in their professional or

personal environment in a way that maximizes their power and control over


29

others (Ibid). This was previously supported by Ajzen (1991) in his theory of

planned behaviour postulating that behaviours are based on one’s intention

regarding that behaviour, which in turn is a function of the person’s attitude

toward the behaviour, subjective norm regarding that behaviour, and perception

of control over that behaviour. Recent theories also emphasize the need to

enhance the career development and psychosocial support to employees

through mentoring and reduce their perception of job-related stress (Sosik &

Jung 2010:345). In all perspectives, people’s behaviour framed not merely from

personal exposition but has direct linkage with organizational behaviours.

Even though the exact time of the individual assertion not mentioned,

excerpts obtained from the book “Writers on Organization” (Pugh & Hickson

1996), the great management gurus of the olden times had highlighted how the

need to function successfully in different environments led organizations to

adopt different structures and strategies. For instance, it was explained how

Tom Burns examined the effects rapidly changing technological developments

on the attempts of old-fashioned firms to adjust to new environments. How Paul

Lawrence and Jay Lorsch emphasised that it is the appropriateness of the

organization’s structure in relation to its environmental requirements, which is

the basis of effectiveness. James D. Thompson also portrayed organizations as

open systems having to achieve their goals in the face of uncertainty in their

environments, while Raymond Miles and Charles Snow emphasised the

strategic choices that managements have to make to adapt to the environmental

pressures they face. All the writers concern was the need for adaptation for

change situations and being flexible to the environment surrounding the

organizations.


30

In their approach, they highlight three key elements on understanding of

organizational behaviour, which believed in line with the underling outlook of

this study. These are: a) it is people who have purposes, not organizations; b)

people have to come together to coordinate their different activities into an

organization; and c) the effectiveness of the organization is judged by the

adequacy with which the members’ needs are satisfied through planned

transactions with the environment (ibid).

2.2.2. Definitions of Organizational Climate

OC perceptions are descriptive of conditions that exist in the work

environment. The perceptions are not evaluative or affective (Schneider &

Snyder 1975) but recent work contradicts this view, suggesting strong evaluative

or affective components (Patterson et al 2005). For decades, the definitions

barely changed in the early understanding of OC as a “normative structure of

attitudes and behavioural standards which provided a basis for interpreting the

situations and act as a source of pressure for directing activities” (Gregopoulos

1965). To the recent amalgamated definition of Agard (2011) of all the

preceding studies, seeing OC to consist the visible attributes of an organization’s

values as interpreted, in a shared manner, by multiple members of the

organization. All in all, climate is best described as employee perceptions of the

organization, it follows that the measurement of climate will be a function of

employee attitudes and values (Toulson & Smith 1994).

There are a variety of measures of OC as summarized by Furnham &

Gunter (1993). To name the few; the categorical approach which attempts to

classify organizations according to pre-existing theoretical types, the

dimensional approach which attempts to classify organizations according to the


31

perceptions of its members to a set of dimensions, the third method is to use

historical data of an organization to develop an aggregate index of OC. The first

and the third methods are objective measures while the second is a subjective

measure based on the perceptions of individuals. We can therefore, summarize

the definitions as any course of sequence of behavior that aids in achieving a

necessary purpose or a series of action that lead to the accomplishment of

objectives.

2.2.3. The emergence of Competing Values Model

As part of their contribution on organizational behavior, Quinn and

Rohrbaugh (1983), where they engaged in a series of studies to review the OC

literature have compiled a list of dimensions, which they termed as the

“Competing Values Model”. Even though the model is likely rooted from

mechanistic and organic type of classification of organizations in which the

former is adapted to relatively stable conditions and the latter is adapted to

unstable conditions when new and unfamiliar problems continually arise (Burns

& Stalker 1961), the CVM is a preferred way of portraying the organizational

behavior in the context of organic type of organization that seek adaptation to

new environment.

According to (K. S. Cameron & Quinn, 1999; Quinn, 1988), the CVM

named as one of the fifty most important models in the history of business. It

has since extended as a framework that makes sense of high performance in

regards to numerous topics in the social sciences and organizations. The CVM

studied and tested in organizations for more than twenty-five years by a group

of thought leaders from leading business schools and corporations. It has been

the topic of many books and papers and it employed in the improvement of


32

thousands of organizations. Still, various researchers use the CVM for all

aspects and levels in organizations.

Two domains of the Competing Values Framework used in the present

study as a frame of reference (Quinn and Rohrbaugh 1983). This framework

captures the dimensions of flexibility/stability and the external/internal focus of

organizations and makes it possible to distinguish between organizational

values. The Open System type encompasses values such as flexibility, external

organizational orientation, adaptability, the capacity to change, uniqueness and

an orientation towards customers and the Human Relations type of values is

supported by an internal focus, cohesion, morale, trust and belongingness (K. S.

Cameron & Quinn 1999).

Source: (Adapted from Quinn & Rohrbaugh (1983: 369)

Figure 2-1: The Competing Values Framework

The framework suggests four main quadrants, each associated with

different managerial ideologies encapsulating the means by which outcomes

may be achieved (Cooil et al. 2009). A major strength of this model is its

Predictability/Control RATIONAL GOAL MODEL

INTERNAL PROCESS MODEL

Means: Information Management; Communication

Ends: Stability; Control

Internal Focus

Means: Cohesion; Morale Ends: Human Resource Development

Output

Q lit

Natural System Values

Rational Values

Flexibility/Spontaneity

External Focus

HUMAN RELATION MODEL

OPEN SYSTEM MODEL

Means: Flexibility; Readiness Ends: Growth; Resource Acquisition

Means: Planning; Goal Setting Ends: Productivity; Efficiency


33

derivation from four orientations to the study of organizational effectiveness,

reflecting long traditions in work and organizational psychology (Patterson et

al., 2004). Patterson and his colleagues thus, went on differentiating the two

approaches from the other two in that the open systems approach emphasizes

the interaction and adaptation of the organization in its environment, with

managers seeking resources and innovating in response to environment. The

human relations approach reflects the tradition derived from socio technical

and human relations schools emphasizing the well-being, growth and

commitment of the community of workers within the organization.

One of the main advantages of the CVM is the fact that it derives its

approach from long standing theories in management and organizational

psychology (Cooil et al. 2009) and it clarifies leadership roles and expectations

and the clarification minimizes ambiguity and avoids interpersonal conflicts

within teams (Zafft et al. 2009). The emergence of the pairs of competing

values; flexibility versus stability, and internal versus external reflects a basic

dilemma of organizational life and those organizations that are able to best

balance integration and differentiation are the most effective systems. From

which side we perceive, participants have unique feelings, likes and dislikes, and

require consideration, appropriate information, and stability in their workplace

(Quinn & Rohrbaugh 1983). Therefore, parallels among the models are

important. The human relations and open system models share an emphasis

upon flexibility whereas; the rational goal and internal process models are

rooted in a value on control (Ibid).


34

Source: Adapted from Quinn & Rohrbaugh (1983: 374)

Figure 2-2: The Alternative Competing Values Framework

In the following table the distinguishing factors of the two approaches in

CVM is presented;

Table 2-1: Distinguishing Factors of the two approaches of the CVM

Human Relations Approach:

Open Systems Approach:

Focus Commitment, Cohesion, and Morale

Adaptability and External Support

Assumption: Involvement results in commitment

Continual adaptation and innovation lead to acquiring and keeping necessary external resources

Emphasis: Participation, conflict resolution, consensus building

Political adaptability, creative problem solving, innovation, and management of change

Expectation: Act as a team, with high employee involvement

Operate in a high-risk, fast-paced, innovative climate, and to rely on vision and shared values

The leader: To take the role of a mentor, coach, and facilitator

To be highly adaptable, an innovator and broker

People: Want to and will perform well given the right environment and encouragement

Thrive on challenge, move from project to project as needed, and must watch for burn-out

Roles: Mentor, Facilitator Innovator, Broker Source: Adapted from Faerman (1990:4-5)

Quinn & Rohrbaugh further argue that OE is not a concept. It is a socially

constructed, abstract notion carried about in the heads of organizational


35

theorists and researchers and in judging the effectiveness of any organization,

they come up to demonstrate through social judgment analysis that it is possible

to articulate values, make the weights on each value explicit, and develop a

formula for empirically combining scores on each criterion. OE refers not only

to results, which are important but also to a number of other aspects - values,

philosophy, policies, process and outcomes.

2.2.4. The link between Competing Values Model and Organizational Climate

The CVM is an empirically derived and comprehensive framework that

encompasses many of the proposed dimensions in the literature and it has

proven to have both face and empirical validity (Cooil et al. 2009). With this

model, Quinn and his colleagues proposed that OC can best be classified by the

fundamental dimensions of internal versus external focuses and flexibility

versus control orientations (Quinn & Rohrbaugh 1983).

Kurt Lewin and his colleagues coined the term “Organizational Climate”

first in 1939 following a study of children’s school clubs. He subsequently

developed his well known field theory of behavior, which he linked to the

Gestalt psychology of holistic perception, and expanded to encompass whole

organizations (Clegg & Bailey 2008; Kundu 2007). The article mainly

emphasised on the relationship between leadership styles and so-called ‘Social

Climate’ that states as a distinctly organizational concept attributed to Rensis

Likert, whose work expanded Lewin’s ideas, and still actively influence the ways

scholars and practitioners approach OC. Likert’s use of surveys to measure

climate – still the dominant approach today – was intended to measure an OC


36

that he considered could not be explicitly known to the organization’s members,

nor was it something that could be created artificially.

OC can be seen as an enduring quality of the internal environment that is

experienced by members, influences their behavior and can be described by a

particular set of values of the characteristics of the organization that are created

by shared psychological climates and it is the employee’s perception of the work

environment and not the environment that is important. Schneider (1990) as

cited in (Patterson et al. 2004), suggested that OC perceptions focus on the

processes, practices, and behaviors which are rewarded and supported in an

organization. The success of Human Services organizations generally depends

on the relationships and interactions between service providers and service

recipients. These relationships are central to the quality and outcome of

services. Importing climate and process from the external environment,

organizations adapt ways from other organizations with which they compete or

cooperate. Effective management of organization processes is vital for

sustaining the competitive edge of any organization.

Processes no longer viewed as just production processes. Today,

management realizes there are many more processes that use material,

equipment, and people to provide many types of outputs and services. They are

called business processes, and today they are even more important to

competitiveness than production processes (Harrington 1991).

2.2.5. The relationship of Organizational Climate and Culture

Climate regarded as an attribute of the organization, a conglomerate of

attitudes, feelings, and behaviours that characterizes life in the organization,

and exists independently of the perceptions and understandings of the members


37

of the organization (Ekvall 1996). Ekvall has also stressed that OC is not

identical to organizational culture. The OC is mostly about attitude and

behaviours. Whereas culture is a process in which the aim is to form a collection

about more comprehensible system of values and believes (Gill 2008).

One of the critical issues in OC is its differentiation from organizational

culture. Indeed, the terms “culture” and “climate” used interchangeably in the

organizational literature. These concepts are, however, clearly differentiated

ontological perspectives and in most cases, culture refers to deeply embedded

values and assumptions (Clegg & Bailey 2008). Climate, on the other hand

refers to environmental factors that consciously perceived and, importantly are

subject to organizational control. That means, climate is something that can be

directly influenced by management policies and leadership, while culture is

much more difficult to change and control (Ibid).

Different authors like (Ashkanasy et al. 2000; Schneider 1990; Tagiuri &

Litwin 1968) as cited in (Edgar H. Schein 2004), defined the word “climate” as

the feeling that is conveyed in a group by the physical layout and the way in

which members of the organization interact with each other, with customers, or

other outsiders. In short, the author concludes climate understood as a surface

manifestation of culture. Nevertheless, some writers on culture divided the

concept into five components: values, beliefs, myths, traditions and norms that

are difficult and almost impossible to measure and even harder for people to

articulate but they are real and should be managed as part of the process of

changing the organization. On the other hand, more precisely, climate is shared

perceptions of organizational policies, practices and procedures (Imran et al.


38

2010). Therefore, climate is more dependent on perceptions rather than

assumptions (Kundu 2007).

The study of OC split and evolved in two directions: research on climate

and research on culture. This divisiveness in the literature remains until today,

as articulated by researchers who advocate keeping the concepts of climate and

culture distinct and independent of each other. However, a growing number of

researchers laud the benefits of understanding climate and culture as reciprocal

and reinforcing concepts that may benefit from mutual study that exist as

related concepts with similar definitions (Agard 2011:613). James et al. (1990)

as cited in (Neal et al. 2000) highlighted that perceptions of the general OC

develop as individuals attribute meaning to their organizational context based

on the significance of the environment for individual values. Apart from these

principal research works, explained in (Kundu 2007), there were also other

studies and the collection of all the research work ultimately provided the initial

framework of OC.

Source: Adapted from Quinn (1988) cited in (Gray & Densten 2006:596) Figure 2-3: The CVF and Culture


39

As shown in Figure 2-3 above, an internally focused flexible

organization thought of as a clan, whereas an internally focused stable

organization thought of as a hierarchy. An externally focused flexible

organization is labelled an adhocracy, and an externally focused stable

organization is thought of as a market (Schein 2004).

In explaining the four culture types Higgs (2010: 79-80) has stated that;-

… clan organizations have parallels with family run organizations, characterized as a friendly place to work, with shared values and goals, a strong cohesiveness and sense of ‘we-ness’ permeates throughout the organization. In an adhocracy culture typically, power is decentralized, effective leaders are visionary, innovative and risk taking. The hierarchy organization characterized as formal and structured where procedures govern how people work and effective leadership includes good coordination and organization, where the maintenance of a smooth-flowing operation is the key. The fundamental assumptions of the market are the external environment is hostile and customers are demanding and seeking value. Leaders are typically hard driving, who are tough and demanding to work. The organization is bound together by its emphasis on winning.

Therefore, as Patterson et al. (2005) stated there is no doubt that culture

and climate are similar concepts since both describe employees’ experiences of

their organizations.

2.2.6. Importance of Organizational Climate

Patterson et al. (2005) suggested that climate perceptions are associated

with a variety of important outcomes at the individual, group, and

organizational levels. He cited the various researches to support his argument

on leader behaviour (Rousseau 1988; Rentsch 1990), turnover intentions

(Rousseau 1988; Rentsch 1990), job satisfaction (Mathieu, Hoffman & Farr

1993; James & Tetrick 1986; James & Jones 1980), individual job performance

(Brown & Leigh 1996; Pritchard & Karasick 1973), and organizational

performance (Lawler et al. 1974; Patterson et al. 2004). Furthermore, Glisson


40

and James (2002) have proved that organizational commitment and job

satisfaction also found to be closely related (Imran et al. 2010).

On the other hand, some of the characteristic features of a healthy

organisational climate were elucidated in Mullins (2005) and Punto (2009).

They emphasised that the need of integration of organisational goals and

personal goals and recognition of people’s needs and expectations at work and

individual differences and attributes. The necessity of equitable systems of

rewards based on positive recognition; concern for the quality of working life

and job design; opportunities for personal development and career progression;

and a sense of identity with, and loyalty to, the organisation and a feeling of

being a valued and important member. Every incident treated as a learning

opportunity and people have a sense of satisfaction in their work; and finally,

people feel that they are cared for and have a sense of belonging. However, what

is far more important than healthiness of an organization especially in service

sector is the issue of service agility and flexibility.

Bessant et al. (2001:31) offer the following definition of agility cited in

(S. Brown et al. 2005): Agility in manufacturing involves being able to respond

quickly and effectively to the current configuration of market demand, and also

to be proactive in developing and retaining markets in the face of extensive

competitive forces. Moreover, they offer an emerging model of agile

manufacturing capabilities, consisting of four key interlinked parameters: agile

strategy, agile processes, agile linkages, and agile people developing a flexible

and multi-skilled workforce, creating a culture that allows initiative, creativity

and supportiveness to thrive throughout the organization.


41

Successful services are dynamic organizations that can adapt to changes

in the quantity and nature of demand. How well a service can adapt depends

greatly on the flexibility inbuilt in it. Flexibility also might be called "designing

for the future" (]ames A. Fitzsimmons & M. Fitzsimmons 2006). Therefore, a

positive OC is important job resource for organizations as it helps them cope

with demanding interactions with customers.

2.2.7. Factors affecting Organizational Climate

Several authors on literatures, one way or another, tried to explain that

OC is affected by several factors both internal & external: Internal -

Organizational structure, Individual responsibility, Rewards, Risk taking, and

Conflict & Tolerance. External - Physical environment, Leadership style,

Organizational politics, Characteristics of members, and Organizational size &

structure. Most importantly, Climate is somewhat used interchangeably with the

term psychological environment and is concerned with the structure, autonomy,

reward structure, tolerance and conflict, need for innovation, warmth, support,

consideration, job stress, job satisfaction, leadership style etc (Raza 2010).

Hence, we can easily understand that OC construct is used to describe the

psychological structure of organization and their sub units.

Table 2-2 portrays some of the compiled types of dimensions used while

studying OC by various researchers at different times.

42

Table 2-2: Research Summary Made on OC by various researchers

No Authors Variables used in their research Main findings Thesis Statement

1 Forehand &

Gilmer (1964)

1) Size 2) Structure 3) System Complexity 4) Leadership Style, and 5) Goal directions

They viewed climate as an objective property of the organization and found that firm’s climate cannot be affected by fluctuations in employee behaviours such as turnover

It has proved how OC influence the behaviour of people in the organization

2 Litwin & Stringer (1968)

1) Structure 2) Responsibility 3) Reward 4) Risk 5) Warmth, and 6) Support

They viewed climate as the perceived attributes of an organization and its sub-systems and they found that over time, the climates became increasingly differentiated consistent with the leader’s style.

Their work more focused on managerial styles and accounts for variance of climate perceptions

3 Schneider &

Snyder (1975)

1) Support 2) structure 3) harmony 4) Concern 5) agent independence, and 6) morale

They found that climate and satisfaction measures are correlated for people in some positions in the agencies and people agree more on the climate of their agency than they do on their satisfaction.

Their work is more concerned with the interpositions agreement on climate perception

4

Jones & James (1979)

1) leadership facilitation and support 2) work group cooperation, friendliness, and warmth 3) conflict and ambiguity 4) professional and organizational spirit 5) job challenge, importance, and variety 6) mutual trust

They proved that employee evaluations of OC have been related to the perceptions of customers who purchased the organization’s services or products.

They delineated the approaches to the study of OC using organizational & individual attributes.

5 Preziosi (1980)

1) Purpose 2) Structure 3) Leadership 4) Relationship 5) Reward 6) Helpful Mechanisms, and 7) Propensity for Change

He develop an organizational diagnosis questionnaire that helps in analysing the relationships among variables that influence organizational functioning.

It is based on Weisbord’s six box model and measures employee’s perception

6 Lehman et al.(2002)

1) Clarity of mission and goals 2) Staff cohesiveness 3) Staff cohesiveness 4) Openness of communication 5) Stress, and 6) Openness to change

A comprehensive assessment of organizational functioning and readiness for change (ORC) was developed based on a conceptual model and previous findings on transferring research to practice

Intended to device a measurement tool based on motivation and personality attributes


43

No Authors Variables used in their research Main findings Thesis Statement

7 Patterson et al.

(2005)

1) Autonomy 2) Clarity of Organizational Goals 3) Efficiency 4) Effort 5) Formalization 6) Innovation & Flexibility 7) Integration 8) Outward focus 9) Participation 10) Performance Feedback 11) Pressure to produce 12) Quality 13) Reflexivity 14) Supervisory Support 15) Tradition 16) Training, and 17) Welfare

They developed and validated a comprehensive multidimensional OC Measure (OCM), based upon Quinn and Rohrbaugh’s Competing Values model that help to examine organizational change processes.

Offers researchers a relatively comprehensive and flexible approach to the assessment of organizational members’ experience

8 Saad, Juhdi, & Samah (2008)

1) Support from Organization 2) Work-Family Conflict 3) Relationship With Peers 4) Self Competence 5) Impact on Job 6) Meaningfulness of Job 7) Optimism on Organizational Change 8) Autonomy 9) Access to Resources, and 10) Time Control

They found that only three variables (meaningfulness of job, optimism on organizational change, and autonomy) are significantly related to Job Satisfaction explaining 28.8% of the variance in Job Satisfaction.

It gives insight into employee’s perception of their work-life quality

9 Cooil et al.

(2009)

1) Autonomy 2) Integration 3) Involvement 4) Supervisory Support 5) Training 6) Welfare 7) Clarity of Goals 8) Efficiency 9) Performance Feedback 10) Effort and Pressure to produce

OC is positively correlated with all positive perceptions and most highly correlated with the perceptions of well-defined objectives/tasks, necessary personal resources, and with perceptions relating to teamwork using a multivariate partial least squares (MPLS) approach

Their approach was geared to the three business outcomes: employee retention, customer satisfaction, and scaled revenue.

10

Adenike (2011) adapted from Nicholson and Miljus (1992)

1) Management or leadership styles 2) Participation in decision making 3) Provision of challenging jobs to employees 4) Reduction of boredom and frustration 5) Provision of benefits 6) Personnel policies 7) Provision of good working conditions, and 8) Creation of suitable career ladder

The finding showed a significant positive relationship between OC and employee job satisfaction of academic staff from a private Nigerian University

Their work was a symbolical and good start for developing nations to build upon especially in African context.

Source: Researcher’s own compilation

44

2.3. CRITICAL REVIEW OF EMPIRICAL STUDIES

2.3.1. Organizational Climate and Organizational Effectiveness

Since OC represents the way, in which its members perceive the

organization, from a practical point of view, climate usually assessed by

measuring employee’s perceptions of specific aspects of dimensions of the

organization. From public sectors point of view, the OC is the blend of top

leadership’s behaviour and employee’s behaviour. Most empirical studies have

used an aggregate unit of analysis, such as the work group, department, or

organization (Patterson et al. 2005). The rationale behind aggregating

individual data to a unit level is the assumption that organizational collectives

have their own climate and that these climates identified through the

demonstration of significant differences in climate between units and significant

agreement in perceptions within units.

In this regard, empirical studies on the process of how climate

perceptions are formed are scanty, indirect and mostly anecdotal and numerous

studies have shown OC as indisputably a major contributing factor for changing

employees’ attitudes and behaviour towards superior job performance and

satisfaction (Vijayakumar 2007). Some studies have focused on perceptually

based measures of climate dimensions and job satisfaction. For instance,

Adenike (2011), focusing on academic staffs of private Nigerian University,

sampled size of 384 proved in his finding that there is a significant positive

relationship (r = 0.671; df = 293, 0.01 sig. level) between OC and job

satisfaction. Adenike (2011) also showed a significant positive relationship

between these two variables and the findings show that 85.7% of the variability


45

in OC explained by boredom and frustration, personnel policies, working

conditions and participation in decision-making.

In the same country Nigeria, a study conducted by Idogho (2006) on

academic staff of Edo state Universities indicated the existence of significant

difference among academic staff [F (2, 4091) = 48.46, P < 0.05], among

universities in their perception of OC [F (3, 4091) = 12.545, P < 0.05)].

Moreover, the male and female academic staff of universities, do not differ in

their perception of OC [F (1, 4092) = 1.530, P > 0.05)] and no difference exist

between young and older academic staff in their perception of OC [F (1, 4092) =

0.002, P > 0.05)].

On the other hand, Cooil et al. (2009) proved that OC is significantly and

positively correlated with both retention and customer satisfaction using ten

dimensions of OC. According to (Imran et al. 2010) who relied only on the two

open system and rational goal models from CVM in his research to determine

innovative work behavior has proved that OC has highly significant positive

relation with its subscales open system model (r = 0.82, p < 0.01).

In Another Pakistan work environment (Iqbal 2007) has proved that

statistically significant correlations between some dimensions of OC and

organizational commitment (r = 0.38, P < 0.01 and r = 0.24, P < 0.01 for

Challenge & Involvement and Trust & Openness dimensions respectively)

demonstrating its strong implications for the literature of organizational

employees perception in developing countries. Therefore, several researchers

have tried to measure the perception of OC using their own specific dimensions

in their work and Prior research suggests that there are personal and


46

organizational factors that serve as antecedents to organizational commitment

(Avolio et al. 2004).

2.3.2. Validation of instruments

The OC measurement instrument that is intended to be used in this study

is well addressed through the rigorous methods the researcher followed in that a

sample of 6,869 employees across 55 manufacturing organizations was used in

the formulation process (Patterson et al. 2005). All the scales contained within

the measure had acceptable levels of reliability and were factorially distinct.

Reliability is concerned with the research and results in terms of replication (J.

Hussey & R. Hussey 1997). If the prime objective of a study is to understand the

OC and it is likely that another researcher following the same method with the

same data would offer similar conclusions, even though the opinions of a

different researcher would add a degree of subjectivity. This is because the

review method is a summary and synthesis of existing empirical research, thus

reliability would be reasonably high. Similar outcomes should be obtainable if

the research is repeated.

The concept of validity refers to the probability that an assertion or

finding is true (Dooley 1984). The unrelenting effort made to review research

from peer-reviewed research journals, the validity of the data set would be quite

accurate in representing organisational climate.


47

CHAPTER III – OVERVIEW OF THE ANRS

3.1. INTRODUCTION

This chapter highlights some of the socio-demographic characteristics of the

regional state in relation to its administrative structures, natural beauty,

economic activity, human resource and with a particular emphasis on the

undergoing organizational civil service reform program.

3.2. DEMOGRAPHIC SITUATION

ANRS is one among the nine and the third largest regional member

states established in Ethiopian Constitution by article 47 (FDRE 1995) and

decentralized into 10 administrative zones, 167 woredas (districts) and 3411

kebeles (localities)(BoFED 2011). The region covers an area of 157, 076 km2, and

covering 15% of the country’s total area. It has a population of 17,221,976 (Male

50.18% and Female 49.82 %) and the economically active and inactive

population stands at 49.4% and 21.9% respectively (CSA 2007). In the same

report it is indicated that out of 8,513,439 economically active population 98.1%

are employed and unemployed rate stands at 1.9 (urban 14.3 and rural 0.6).

The age structure of the population in the region, 42.59 percent are age

14 and under and those who are greater than or equal to 65 constitute 3.97

percent of the population. Hence, the young age dependency ratio is 79.69 and

that of the old age is 8.53 percent which make the societal dependency ratio

87.13 per cent (BoFED 2009).

3.3. NATURAL BEAUTY

The region is known for its historical and tourist attractions with about

70% of international and 80% of domestic tourists flow to the region (BoCTPD

2011). In the same report, it was disclosed that the three main tourist


48

destinations are Bahirdar, Gonder and Lalibella. The flow of domestic tourists

flow have showed a staggering 21 fold increment from 2002 (33,792) to 2010

(708,399) while the international tourists flow has increased steadily by 4 fold

from 2002 (22,589) to 2010 (86,772) during the eight years respectively

(BoCTPD 2010). However, still there is much to remain to reap out of the

immense potential and natural beauty of the region’s expositions.

3.4. ECONOMIC ACTIVITY

Concerning the economic activity rate or labour force participation rate,

which is computed as the percentage of the economically active population to

the total of economically active and inactive population, the region’s activity rate

accounts 61.0 which is above the national activity rate of 60.3 percent (CSA

2011). This means out of 100 persons aged ten years and above 61 persons is

engaged or available to participate in the production of goods and services.

While the remaining 39 persons are not ready to do so due to various reasons

such as education, illness, pregnancy, old age…etc.

3.5. HUMAN RESOURCE

In the regional state, there are 170,951 civil servants (Male 63.2% and

Female 36.8%) working at various government institutions of which; 13.9% are

graduate and above, 71.5% are undergraduates of diploma and certificates, and

the remaining 14.6% are high schools and undefined (BoFED 2011). The same

report has indicated that at regional level there are 4,276 civil servants working

in forty-six Public Institutions out of which currently three institutions have

been merged due to the organizational restructuring process.


49

3.6. THE CIVIL SERVICE REFORM

Having noting the need to reform the overall public institutions, the

regional government has embarked intensively on BPR initiatives ever since the

program launched at National level in 2001.

3.6.1. The Public Service Capacity Building Program

The Civil Service Reform Program (CSRP) which is one of the six country

wide reform sub-programs under PSCAP started implementation in 1996/1997

in response to weaknesses in the administrative system and aims to introduce

new and improved legislation and working systems to simplify administrative

processes as well as ensuring effectiveness, efficiency, and ethical behaviour in

performance and service delivery. The PSCAP which was part of the GTP gave

especial focus on reform activities, mobilizing the civil servants to bring

dramatic improvements in the civil service, ensure zero tolerance to rent-

seeking attitude and practice, as well as deliver effective and efficient service

delivery to the customers.

In her results analysis report of the National project PSCAP (November

2004 to April 2009) Araya, (2009) stated that all the seven sub-program

components that run under CSRP progressed well in some aspects and failed to

bring the expected results. The components are: i) strengthening the capacity of

CSRP coordinating structures; ii) improving governance of financial resource

management; iii) improving governance of human resource management; iv)

improving performance and public service delivery; v) improving accountability

and transparency; vi) strengthening top management systems; and vii) building

the policy and institutional governance capacity of the four least developed

regional states.


50

The same report by Araya has also revealed that Amhara region has

demonstrated a good start in rolling out the sub-programs and especially

pioneer in implementing the BPR, which in later stage lags behind from its

determined targets and outcomes. Another report that investigates the

weaknesses in service delivery on 6,944 samples (Amhara Management

Institute, 2007) has attempted to identify the causes, which keep public

servants from observing the conduct norms specific to their field.

These causes are listed as follows:

a) The lack of accountability and transparency (29%);

b) Lack of fairness in placement (28%);

c) The lack of shared vision and a clear mission (11%);

d) The lack of Involvement (20%);

e) The low level of the leadership capacity (25%) and public servants (9%);

f) Lack of ownership of the public servants (24%);

g) The low level of morality when it comes to public servants (17%); and

h) Attitudinal problems (16%)

3.6.2. Business Process Reengineering

Reengineering is the fundamental rethinking and radical redesign of

work processes to achieve dramatic improvements in critical, contemporary

measures of performance such as cost, quality, service and speed (Hammer &

Champy 1993). Unfortunately the number of BPR successes where expectations

have been fully realized is said to be quite small (E. Cameron & Green 2009).

BPR therefore offers the very attractive prospect of radically transforming key

processes by starting from a very blank sheet. The downside comes during


51

implementation, when resistance from those who have not been involved may

be encountered.

According to the GTP annual progress report released recently by

MoFED (2012) clearly stated that “though encouraging efforts have been done

in capacity building and good governances in the civil service, there were certain

weaknesses observed. These include among others that institutional

transformation is not progressing at the expected level and rent-seeking

attitudes and practices are still the key constraining challenges facing the civil

service.” That is why to solve the problems of hierarchical bureaucracy with

many non-value adding works/staffs/positions, nepotism, etc; BPR is seriously

implemented in all public institutions gradually. The three elements that

characterize work processes are the inputs, the processing and the outcome. The

problematic part of the process is processing (Zigiaris 2000). Work process

reengineering mainly intervenes in the processing part, which reengineered in

order to become less time and money consuming.

The organizational change program that the government had embarked

upon was once evaluated in connection to determining the extent of

implementation of BPR using rigorous criteria developed by the then regional

Bureau of Capacity Building and Civil Service (Amare et al. 2010). The

evaluation team constitute 24 individuals pooled from 17 public institutions.

The criteria used for the evaluation revolve around nine managerial issues.

These were; Planning, Efficiency, Effectiveness, Communication, Transparency,

Accountability, Rule of law, Participatory, and Ethics. The result of the

assessment report was used for determining the sampling frame of this study as

mentioned in chapter two.


52

CHAPTER IV: DISCUSSION AND ANALYSIS

4.1. INTRODUCTION

This chapter focuses on research results. The purpose of the chapter is to

explain the results from the analysis conducted using SPSS (Statistical Package

for the Social Sciences), on the data obtained from the respondents via the

questionnaires.

Following this introduction, Section 4.2 presents the descriptive statistics

of the measured demographic variables. Section 4.3 shows the results of validity

testing using principal component analysis to validate the constructs. Section

4.4 describes reliability analysis using Cronbach’s alpha to analyse the

constructs, and Section 4.5 provides details of hypothesis testing using

statistical tests of Multiple Linear Regression, Pearson’s Product-Moment

Correlation Coefficients, Independent-Samples t-test, and One-Way ANOVA

analysis.

4.2. DESCRIPTIVE STATISTICS: AN OVERVIEW

Descriptive Statistics, the simplest level of quantitative analysis, is used

to summarize or display quantitative data and is limited to, at most, the analysis

of frequencies, average and ranges (Collis & Roger Hussey 2003; Lancaster

2005). The demographics of respondents include gender, level of education,

tenure, and work processes in which they are working.

As part of this study, 348 questionnaires were distributed to 6 public

organizations in ANRS and 260 questionnaires were returned, an effective

response rate of 75%. Of the returned questionnaires, nineteen were found to be

missing responses to one or more questions. The missing responses were


53

replaced with the mean value of the variables based on the valid responses (Hair

et al. 2003).

4.2.1. Demography of Respondents

4.2.1.1. Gender

Table 4-1 shows that, of the 260 respondents, 169 were male and 91

were female. Males made up the majority of respondents at 65% while females

were 35%. The ratio of males to females in this sample is 65 to 35.

The sample is similar to the ratio of males and females (Male 63.2% and

Female 36.8%) in the distribution of ANRS civil servants (Bureau of Finance

and Economic Development, 2011), which covers workers at regional level. As

such, the sample is representative of the public work force in ANRS.

Table 4-1: Descriptive Statistics for Gender of Respondents

Frequency Percent Valid Percent

Cumulative Percent

Valid Male 169 65.0 65.0 65.0 Female 91 35.0 35.0 100.0 Total 260 100.0 100.0

Source: Researcher’s own computation

4.2.1.2. Business Processes

Table 4-2 shows that, of the 260 respondents, 149 working in core

process and 111 working in support process. Respondents from core process

made up the majority of respondents at 57.3% while respondents from support

process were 42.7%. The ratio of respondents in core process to support process

in this sample is 57 to 43.

The sample is similar to the ratio of the working force available (In Core

process 59% and in Support process 41%) in the distribution of ANRS civil

servants (Bureau of Civil Service 2010), which covers workers public institutions


54

at regional level. As such, the sample is representative of the proportion of work

processes in ANRS.

Table 4-2: Descriptive Statistics for Work processes of Respondents


Cumulative Percent

Valid Core Process 149 57.3 57.3 57.3 Support Process 111 42.7 42.7 100.0 Total 260 100.0 100.0


4.2.1.3. Education

Table 4-3 shows the distribution of respondents’ level of Education as

follows: 10th, 12th & below (5.2%), Certificate (3.1%), Diploma (20.0%), Bachelor

Degree (52.7%) and 2nd Degree & above (16.2%). 8 respondents (3.1%) did not

state their education level.

The sample is a little different to the ratio of the education level (13.9%

are graduate and above and 71.5% are undergraduates of diploma and

certificates and the remaining 14.6% are high schools and undefined) in the

distribution of ANRS civil servants (BoFED 2011), which covers workers of

public institutions at regional level. This might be explained by the expansion of

the education sector compounded by the fast economic growth that helped were

graduating from 2010 onwards. As such, the sample is representative of the

proportion of level education in ANRS.


55

Table 4-3: Descriptive Statistics for Education of Respondents


Cumulative Percent

Valid 10th,12th & Below 13 5.0 5.2 5.2 Certificate 8 3.1 3.2 8.3 Diploma 52 20.0 20.6 29.0 Bachelor Degree 137 52.7 54.4 83.3 2nd Degree & Above 42 16.2 16.7 100.0 Total 252 96.9 100.0

Missing 0 8 3.1

Total 260 100.0


4.2.1.4. Tenure

Table 4-4 shows the distribution of respondents’ tenure as follows:

Below 5 years (42.4%), 5 to 10 years (27.2%), 11 to 15 years (11.6%), 16 to 20

years (8.0%) and above 20 years (10.8%). 10 respondents (3.8%) did not want

to state their tenure.

Table 4-4: Descriptive Statistics for Tenure of Respondents


Cumulative Percent

Valid Below 5 Years 106 40.8 42.4 42.4 5 to 10 Years 68 26.2 27.2 69.6 11 to 15 Years 29 11.2 11.6 81.2 16 to 20 Years 20 7.7 8.0 89.2 Above 20 Years 27 10.4 10.8 100.0 Total 250 96.2 100.0

Missing 0 10 3.8

Total 260 100.0


4.2.2. Descriptive Statistics

The key descriptive statistics are mean, standard deviation, skewness and

kurtosis (Field 2009; Veaux et al. 2008; Collis & Roger Hussey 2003). Standard

deviation is an indication of the dispersion of the data (De Veaux et al. 2008).


56

Positive values of skewness indicate too many low scores in the distribution,

whereas negative values indicate a build-up of high scores. Positive values of

kurtosis indicate a pointy and heavy-tailed distribution, whereas negative values

indicate a flat and light-tailed distribution (Field 2009).

Skewness measures the degree to which cases are clustered towards one

end of an asymmetry distribution. In general, the further the value of skewness

is from zero, the more likely it is that the data are not normally distributed

(Field 2009).

Kurtosis measures the level of peakiness in a histogram (De Veaux et al.

2008). High peaks have positive kurtosis, while flatter distributions have

negative kurtosis (De Veaux et al. 2008). Skewness and kurtosis are converted

to z-scores using the following formulas (Field 2009:139)

Zskewness = 𝑆−0𝑆𝐸𝑠𝑘𝑒𝑤𝑛𝑒𝑠𝑠

Zkurtosis = 𝐾−0𝑆𝐸𝑘𝑢𝑟𝑡𝑜𝑠𝑖𝑠

An absolute value of z-scores greater than 1.96 is significant at p < .05,

above 2.58 is significant at p < .01 and absolute values above about 3.29 are

significant at p < .001. Large samples will give rise to small standard errors and

so when sample sizes are big, significant values arise from even small deviations

from normality therefore, in large samples this criterion should be increased to

the 2.58(Field 2009: 139).

For a large sample (200 or more) it is more important to look at the

shape of the distribution visually and to look at the value of the skewness and

kurtosis statistics rather than calculate their significance (Field 2009: 139).


57

Tables 4-5, 4-6 & 4-7 show the descriptive statistics for the variables:

Integration, Involvement, Supervisory Support, Training, Welfare, Innovation

& Flexibility, Outward Focus, Reflexivity, HRV, OSV and OE.

Table 4-5 shows that the Integration variable has a mean of 3.396, a

median of 3.50, and a standard deviation of 0.997. It is a negatively skewed

distribution (-0.383) and with negative kurtosis of (-0.479). The Involvement

variable has a mean of 3.07, a median of 3.00, and a standard deviation of

0.912. It is a negatively skewed distribution (-0.105) and with negative kurtosis

of (-0.630). The Supervisory Support variable has a mean of 3.15, a median of

3.20, and a standard deviation of 1.02. It is a negatively skewed distribution (-

0.205) and with negative kurtosis of (-0.765). The Training variable has a mean

of 2.91, a median of 2.67, and a standard deviation of 0.974. Its skewness is

almost zero and with negative kurtosis of (-0.573). The Welfare variable has a

mean of 2.87, a median of 3.00, and a standard deviation of 1.05. It is a

negatively skewed distribution (-0.118) and with negative kurtosis of (-0.865).

Table 4-5: Descriptive Statistics for Sub-scales of HRV

Integration Involvement

Supervisory

Support

Emphasis on

Training

Welfare

N Valid 260 260 260 260 260 Mean 3.396 3.07 3.15 2.91 2.87 Median 3.500 3.00 3.20 2.67 3.00 Std. Deviation .997 .912 1.02 .974 1.05 Skewness -.383 -.105 -.205 -.002 -.118 Std. Error of Skewness .151 .151 .151 .151 .151 Kurtosis -.479 -.630 -.765 -.573 -.865 Std. Error of Kurtosis .301 .301 .301 .301 .301 Zskewness -2.54 -0.70 -1.36 -0.01 -0.78 Zkurtosis -1.59 -2.09 -2.54 -1.90 -2.87 Not Significant at P < .01 P < .01 P < .01 P < .05 P < .001



58

Table 4-6 shows that the Innovation & Flexibility variable has a mean of

2.999, a median of 3.00, and a standard deviation of 0.84. It is a negatively

skewed distribution (-0.109) and with negative kurtosis of (-0.421). The

Outward Focus variable has a mean of 3.695, a median of 4.00, and a standard

deviation of 0.774. It is a negatively skewed distribution (-0.474) and with

negative kurtosis of (-0.194). The Reflexivity variable has a mean of 3.39, a

median of 3.33, and a standard deviation of 0.84. It is a negatively skewed

distribution (-0.476) but with positive kurtosis of (0.076).

Table 4-6: Descriptive Statistics for Sub-scales of OSV


Outward Focus

Reflexivity

N Valid 260 260 260 Mean 2.9994 3.6949 3.3949 Median 3.0000 4.0000 3.3333 Std. Deviation .84318 .77447 .84061 Skewness -.109 -.474 -.476 Std. Error of Skewness .151 .151 .151 Kurtosis -.421 -.194 .076 Std. Error of Kurtosis .301 .301 .301 Zskewness -0.72 -3.14 -3.15 Zkurtosis -1.40 -0.64 0.25 Not Significant at P < .05 P < .001 P < .001


Table 4-7 shows that the HRV variable has a mean of 3.06, a median of

3.05, and a standard deviation of 0.718. It is a positively skewed distribution

(0.058) and with negative kurtosis of (-0.462). The OSV variable has a mean of

3.01, a median of 3.00, and a standard deviation of 0.867. It is a negatively

skewed distribution (-0.114) and with negative kurtosis of (-0.479). The OE

variable has a mean of 3.49, a median of 3.67, and a standard deviation of 1.06.


59

It is a negatively skewed distribution (-0.49) and with negatively kurtosis of (-

3.22).

Table 4-7: Descriptive Statistics for HRV, OSV and OE

HRV OSV OE N Valid 260 260 260 Mean 3.0595 3.0085 3.4885 Median 3.0526 3.0000 3.6667 Std. Deviation .71756 .86694 1.05829 Skewness .058 -.114 -.490 Std. Error of Skewness .151 .151 .151 Kurtosis -.462 -.479 -.322 Std. Error of Kurtosis .301 .301 .301 Zskewness 0.38 -0.75 -3.25 Zkurtosis -1.53 -1.59 -1.07 Not Significant at P < .05 P < .05 P < .001


Table 4-8 shows Case wise diagnostics for the sample size of 260. It is

reasonable to expect about 13 cases (5%) to have Standardized Score outside of

the limit of +/- 1.96 and expect about 3 cases (1%) to have Standardized Score

outside of the limit of +/- 2.58 (Field 2009). Hence, we can see that we have 17

cases (7%) only for Innovation & Flexibility, which is outside of the limits. There

are no cases that falls outside the limit of +/- 2.58. This indicates that the

sample can be assumed as normally distributed and statistically analyzed with

99% confidence level. Therefore, our sample is within 1% error of what we

would expect.


60

Table 4-8: Case wise diagnostics of constructs

Constructs z-scores outside +/-1.96

% z-scores outside +/-2.58

% z-scores outside +/-3.29

%

Integration 7 3% 0 0 Involvement 10 4% 0 0 Supervisory Support 5 2% 0 0 Emphasis on Training 8 3% 0 0 Welfare 7 3% 0 0 Innovation & Flexibility 17 7% 0 0 Outward Focus 12 5% 2 1% 0 Reflexivity 10 4% 0 0 OE 12 5% 0 0 HRV 13 5% 1 1% 0 OSV 12 5% 0 0

Sample size 260 100% Source: Researcher’s own computation

4.2.3. Summary

In summary, the majority of the respondents were male (65%). The

majority of respondents are working in Core work process (57.3%) and the

majority of respondents were holders of Bachelor degree and above (71.1%). The

majority of respondents have worked in the present institution more than 5

years (57.6%). The means, standard deviations, skewness and kurtosis of the

eleven variables were presented. (The plots of Histogram, Normal Q - Q and Box

plots are annexed (see APPENDIX- D).

4.3. VALIDITY ANALYSIS

The psychometric properties of a measurement are important because it

gives an indication of the effectiveness of the measurement utilized. It was

determined by measuring the reliability and validity. Validity is the extent to

which an instrument measures what it claims to.


61

Principal component analysis is a psychometrically sound procedure, it is

conceptually less complex than factor analysis, and it bears numerous

similarities to discriminant analysis (Field 2009). In a reliable scale, all items

should correlate with the total.

Factors with a few low loadings should not be interpreted unless the

sample size is 300 or more (Field 2009) as communalities become lower the

importance of sample size increases. In the worst scenario of low

communalities (well below 0.5) and a larger number of underlying factors

MacCallum, Widaman, Zhang, & Hong, (1999) recommended samples above

500. However, as Field (2009) pointed out that a sample of around 300 or more

will probably provide a stable factor solution. Typically, researchers take a

loading of an absolute value of more than 0.3 to be important (Field 2009).

Since the communality is a measure of the proportion of variance

explained by the extracted factors, Stevens (2002) as mentioned in Field (2009:

644) recommends that based on an alpha level of .01 (two-tailed), for a sample

size of 200 it should be greater than 0.364, for 300 it should be greater than

0.298. On the other hand Hair et al. (1998) suggested that a cut-off loading

value of 0.50 be adopted because of the large number of variables being

analyzed. Therefore, a cut-off loading value of 0.5 was used for this analysis.

4.3.1. Human Relation Values

A principal component analysis was conducted using SPSS on the HRV scale to

examine its proposed multi-factor structure. The results of the principal

components analysis annexed (see APPENDIX- E) and according to the

“Eigenvalue > 1” rule, there are five significant factors named as Supervisory

Support, welfare, integration, involvement and Training. It explains a total of


62

65.218% of the total variance in the nineteen items discarding items revQn1,

Qn2, revQn8, revQn9 & Qn10 due to their non significant correlation with any

other items and low communality (below 0.5).

Item loading for the multi Factor for HRV that contains the item loading

showed that all of the items are loaded strongly onto their respective

components (See APPENDIX- F). This suggests a multi-factor structure with

five sub-scales is extracted for the HRV scale. Eight items loaded on the first

factor, which is characterized by Supervisory Support & Welfare sub-scales

together, four items loaded on the second factor solicited from Emphasis on

Training, welfare & involvement sub-scales, three items explicitly characterized

by integration sub-scale loaded on the third factor, three items solicited from

involvement and training sub-scales loaded on the fourth factor and lastly, one

item from training sub-scale loaded on the fifth factor strongly. All of the items

have loadings above the 0.5 level, as recommended by Hair et al. (1998). KMO

value of .914, which is above the cut-off point of 0.5 recommended by Kaiser

(1974) and close to 1 indicates that patterns of correlations are relatively

compact and so factor analysis should yield distinct and reliable factors.

4.3.1.1. Integration

A principal component analysis was conducted using SPSS on the

Integration scale to examine its proposed single-factor structure. The results of

the principal components analysis annexed (see APPENDIX- E ) and according to

the “Eigenvalue > 1” rule, there is only one significant factor, Integration, and it

explains 75.140% of the total variance in the two items discarding items revQn1,

Qn2 & revQn5 due to their non significant correlation with any other items and

low communality (below 0.5).


63

Item loading for the Single Factor for Integration that contains the item

loading, showed that all of the items are loaded strongly onto the first

component (see APPENDIX- F). This suggests a single-factor structure for the

Integration scale. All of the items have loadings above the 0.5 level, as

recommended by Hair et al. (1998). KMO value of .5, which is exactly equal to

the cut-off point of 0.5 recommended by Kaiser (1974) and close to 1 indicates

that patterns of correlations are relatively compact and so factor analysis should

yield distinct and reliable factors.

4.3.1.2. Involvement


Involvement scale to examine its proposed single-factor structure. The results of


the “Eigenvalue > 1” rule, there is only one significant factor, Involvement, and

it explains 56.517% of the total variance in the three items discarding items

revQn7, revQn8 & revQn11 due to their non significant correlation with any


Item loading for the Single Factor for Involvement that contains the item



Involvement scale. All of the items have loadings above the 0.5 level, as

recommended by Hair et al. (1998). KMO value of .635, which is above the cut-

off point of 0.5 recommended by Kaiser (1974) and close to 1 indicates that

patterns of correlations are relatively compact and so factor analysis should



64

4.3.1.3. Supervisory Support


Supervisory Support scale to examine its proposed single-factor structure. The

results of the principal components analysis annexed (see APPENDIX- E) and

according to the “Eigenvalue > 1” rule, there is only one significant factor,

Supervisory Support, and it explains 69.697% of the total variance in the five

items.

Item loading for the Single Factor for Supervisory Support that contains

the item loading, showed that all of the items are loaded strongly onto the first


Supervisory Support scale. All of the items have loadings above the 0.5 level, as





4.3.1.4. Emphasis on Training


Emphasis on Training scale to examine its proposed single-factor structure.

The results of the principal components analysis annexed (see APPENDIX- E)

and according to the “Eigenvalue > 1” rule, there is only one significant factor,

Emphasis on Training, and it explains 62.106% of the total variance in the three

items.

Item loading for the Single Factor for Emphasis on Training that

contains the item loading, showed that all of the items are loaded strongly onto

the first component (see APPENDIX- F). This suggests a single-factor structure


65

for the Emphasis on Training scale. All of the items have loadings above the 0.5

level, as recommended by Hair et al. (1998). KMO value of .623, which is above

the cut-off point of 0.5 recommended by Kaiser (1974) and close to 1 indicates

that patterns of correlations are relatively compact and so factor analysis should


4.3.1.5. Welfare


Welfare scale to examine its proposed single-factor structure. The results of the

principal components analysis annexed (see APPENDIX- E) and according to the

“Eigenvalue > 1” rule, there is only one significant factor, Welfare, and it

explains 77.705% of the total variance in the three items discarding one item

revQn21 due to its non significant correlation with any other items and low

communality (below 0.5).

Item loading for the Single Factor for Welfare that contains the item



Welfare scale. All of the items have loadings above the 0.5 level, as





4.3.2. Open System Values

A principal component analysis was conducted using SPSS on the OSV

scale to examine its proposed multi-factor structure. The results of the principal

components analysis annexed (see APPENDIX- E) and according to the


66

“Eigenvalue > 1” rule, there are two significant factors, Innovation & Flexibility

and Outward Focus, and altogether explain 65.717% of the total variance in the

thirteen items discarding items Qn30, revQn31, Qn35, Qn36 and Qn37 due to

their non significant correlation with any other items and low communality

(below 0.5).

Item loading for the Single Factor for OSV that contains the item loading,

showed that all of the items are loaded strongly onto their respective

components (see APPENDIX- F). This suggests a multi-factor structure with

two sub-scales is extracted for the OSV scale. Five items loaded on the first

factor, which is explicitly characterized by Innovation & Flexibility sub-scale,

three items loaded on the second factor explicitly characterized by the Outward

Focus sub-scale. All of the items have loadings above the 0.5 level, as





4.3.2.1. Innovation & Flexibility


Innovation & Flexibility scale to examine its proposed single-factor structure.

The results of the principal components analysis annexed (see APPENDIX- E)

and according to the “Eigenvalue > 1” rule, there is only one significant factor,

Innovation & Flexibility, and it explains 61.732% of the total variance in the Six

items.

Item loading for the Single Factor for Innovation & Flexibility that

contains the item loading, showed that all of the items are loaded strongly onto


67

the first component (see APPENDIX- F). This suggests a single-factor structure

for the Innovation & Flexibility scale. All of the items have loadings above the

0.5 level, as recommended by Hair et al. (1998). KMO value of .856, which is

above the cut-off point of 0.5 recommended by Kaiser (1974) and close to 1

indicates that patterns of correlations are relatively compact and so factor

analysis should yield distinct and reliable factors.

4.3.2.2. Outward Focus


Outward Focus scale to examine its proposed single-factor structure. The

results of the principal components analysis annexed (see APPENDIX- E) and

according to the “Eigenvalue > 1” rule, there is only one significant factor,

Outward Focus, and it explains 66.835% of the total variance in the four items

discarding one item revQn31 due to its non significant correlation with any


Item loading for the Single Factor for Outward Focus that contains the

item loading, showed that all of the items are loaded strongly onto the first


Outward Focus scale. All of the items have loadings above the 0.5 level, as





4.3.2.3. Reflexivity


Reflexivity scale to examine its proposed single-factor structure. The results of


68


the “Eigenvalue > 1” rule, there is only one significant factor, Reflexivity, and it

explains 65.389% of the total variance in the three items.

Item loading for the Single Factor for Reflexivity that contains the item



Reflexivity scale. All of the items have loadings above the 0.5 level, as





4.3.3. Organizational Effectiveness

A principal component analysis was conducted using SPSS on the OE

scale to examine its proposed single-factor structure. The results of the principal

components analysis annexed (see APPENDIX-E) and according to the

“Eigenvalue > 1” rule, there is only one significant factor, OE, and it explains

79.181% of the total variance in the three items.

Item loading for the Single Factor for OE that contains the item loading,

showed that all of the items are loaded strongly onto the first component (see

APPENDIX- F). This suggests a single-factor structure for the OE scale. All of

the items have loadings above the 0.5 level, as recommended by Hair et al.

(1998). KMO value of .725, which is above the cut-off point of 0.5 recommended

by Kaiser (1974) and close to 1 indicates that patterns of correlations are

relatively compact and so factor analysis should yield distinct and reliable

factors.


69

4.4. RELIABILITY ANALYSIS

The test of reliability is an important test of sound measurement. It refers

to consistency of obtaining the same results carried out under same conditions

or a condition that particular data collection approach will yield the same

results on different occasions (Kothari 2004; Lancaster 2005) i.e. if we took two

people from different organizations that have positive outlook on same

construct, they should both get equally same scores. The split-half method is

used to test internal consistency levels of the measuring instrument (Field

2009; Nunnally 1978). The method randomly splits all items that are used to

measure the same construct into two sets (Field 2009; Nunnally 1978). By

comparing one half of the results with the other half of the results from the

same construct using Cronbach’s coefficient alpha (𝛼) test, reliability can be

established (Nunnally 1978).

Cronbach’s alpha is a commonly used test of internal reliability and it

essentially calculates the average of all possible split-half reliability coefficients.

The correlation between the two halves is the statistic computed in the split-half

method, with large correlations being a sign of reliability (Field 2009). The

intention is to test the level to which scale items are consistent and reveal the

same fundamental constructs. The calculated alpha coefficient fluctuates

between 1 (perfect internal reliability) and 0 (no internal reliability). The figure

.70 is recommended by Nunnally (1978) as a rule of thumb, to indicate the level

of internal consistency reliability that can be considered satisfactory.

Nonetheless, Kline (1999) cited in Field (2009) suggest that when dealing with

psychological constructs values below even .7 can, realistically, be expected

because of the diversity of the constructs being measured. It also mentioned in


70

same document, Cronbach (1951) suggested that if several factors exist then the

formula should be applied separately to items relating to different factors.

(Reliability statistics of the SPSS outputs for all variables is annexed see

APPENDIX- E)

4.4.1. Human Relations Values

A Cronbach’s alpha analysis was performed using SPSS on the HRV scale

to examine its internal consistency. Cronbach’s alpha for the nineteen items

scale after discarding five items (revQn1, Qn2, revQn8, revQn9 & Qn10) was

calculated to check the internal consistency reliability of the scale and was

0.900, which is above the 0.70 criterion of Nunnally (1978). Since the value can

be improved to 0.907 by discarding one item (revQn19) further, the item was

retained because the increment does not bring substantial difference and above

all, both values reflect a good degree of reliability. Therefore the internal

consistency reliability of the HRV scale used in this study can be considered

acceptable.

4.4.1.1. Integration

A Cronbach’s alpha analysis was performed using SPSS on the

Integration scale to examine its internal consistency. Cronbach’s alpha for the

two items scale after discarding three items (revQn1, Qn2 & revQn5) was


0.667, which is not substantially below the 0.70 criterion of Nunnally (1978).

Therefore the internal consistency reliability of the Integration scale used in

this study can be considered acceptable (Kline 1999 as cited in Field 2009: 675).


71

4.4.1.2. Involvement


Involvement scale to examine its internal consistency. Cronbach’s alpha for the

three items scale after discarding three items (revQn7, revQn8 & revQn11) was


0.615, which is not substantially below the 0.70 criterion of Nunnally (1978).

Therefore the internal consistency reliability of the Involvement scale used in

this study can be considered acceptable (Kline 1999 as cited in Field 2009: 675).

4.4.1.3. Supervisory Support


Supervisory Support scale to examine its internal consistency. Cronbach’s alpha

for the five items scale was calculated to check the internal consistency

reliability of the scale and was 0.891, which is above the 0.70 criterion of

Nunnally (1978). Therefore the internal consistency reliability of the

Supervisory Support scale used in this study can be considered acceptable.

4.4.1.4. Emphasis on Training

A Cronbach’s alpha analysis was performed using SPSS on the Emphasis

on training scale to examine its internal consistency. Cronbach’s alpha for the

three items scale after discarding one item (revQn19) was calculated to check

the internal consistency reliability of the scale and was 0.691, which is not

substantially below the 0.70 criterion of Nunnally (1978). Therefore the internal

consistency reliability of the Emphasis on training scale used in this study can’t

be considered acceptable (Kline 1999 as cited in Field 2009: 675).


72

4.4.1.5. Welfare

A Cronbach’s alpha analysis was performed using SPSS on the Welfare

scale to examine its internal consistency. Cronbach’s alpha for the three items

scale after discarding one item (revQn21) was calculated to check the internal

consistency reliability of the scale and was 0.856. Since the value can be

improved to 0.866 by discarding one item (Qn24) further, the item was retained

because the increment does not bring substantial difference and above all, both

values reflect a good degree of reliability. The obtained value is above the 0.70

criterion of Nunnally (1978). Therefore the internal consistency reliability of the

Welfare scale used in this study can be considered acceptable.

4.4.2. Open Systems Values

A Cronbach’s alpha analysis was performed using SPSS on the OSV scale

to examine its internal consistency. Cronbach’s alpha for the thirteen items scale

after discarding four items (Qn30, revQn31, Qn35, Qn36 & Qn37) was


0.835, which is above the 0.70 criterion of Nunnally (1978). Since the value can

be improved to 0.837 by discarding one item (revQn32) further, the item was

retained because the increment does not bring substantial difference and above

all, both values reflect a good degree of reliability. Therefore the internal

consistency reliability of the OSV scale used in this study can be considered

acceptable.

4.4.2.1. Innovation & Flexibility


Innovation & Flexibility scale to examine its internal consistency. Cronbach’s

alpha for the six items scale was calculated to check the internal consistency


73

reliability of the scale and was 0.875, which is above the 0.70 criterion of

Nunnally (1978). Therefore the internal consistency reliability of the Innovation

& Flexibility scale used in this study can be considered acceptable.

4.4.2.2. Outward Focus

A Cronbach’s alpha analysis was performed using SPSS on the Outward

Focus scale to examine its internal consistency. Cronbach’s alpha for the three

items scale after discarding one item (revQn31) was calculated to check the

internal consistency reliability of the scale and was 0.751, which is above the

0.70 criterion of Nunnally (1978). Therefore the internal consistency reliability

of the Outward Focus scale used in this study can be considered acceptable.

4.4.2.3. Reflexivity

A Cronbach’s alpha analysis was performed using SPSS on the Reflexivity

scale to examine its internal consistency. Cronbach’s alpha for the three items

scale was calculated to check the internal consistency reliability of the scale and

was 0.735, which is above the 0.70 criterion of Nunnally (1978). Therefore the

internal consistency reliability of the Reflexivity scale used in this study can be

considered acceptable.

4.4.3. Organizational Effectiveness

A Cronbach’s alpha analysis was performed using SPSS on the OEscale to

examine its internal consistency. Cronbach’s alpha for the three items scale was


0.868, which is above the 0.70 criterion of Nunnally (1978). Therefore the

internal consistency reliability of the OE scale used in this study can be

considered acceptable.


74

4.5. HYPOTHESIS TESTING

It is proposed that the collected data be analyzed using parametric

statistical tools to test the hypotheses since it is assumed that the sampling

distribution is normal and none of the assumptions were found violated.

Hypotheses 1 is tested using multiple linear regressions. Hypotheses 2 and 3 are

tested using Pearson’s product-moment Correlation Coefficients. Hypothesis 4

and 8 are tested using Independent-samples T- test. Hypotheses 5, 6 and 7 are

tested using One-way ANOVA.

4.5.1. Testing of Hypothesis One (effects between variables)

Multiple Linear Regression was used to determine the effects of the two

independent variables (HRV and OSV) on the dependent variable (OE)

measured indirectly by organizational commitment (Speier & Venkatesh 2002).

The following multiple regression model was used to measure the effects

of the two independent variables on the dependent variable.

Y = 𝜶𝟎 + b1 X1 + b2 X2 + є

Where: Y = the dependent Variable of OE, Xi = the independent Variables in

which; X1 = HRV, X2 = OSV, 𝛼0 = the y-intercept, bi, i=1-2 = regression

coefficients of the two factors in explaining Y, and є = the Error term.

With a statistical significance p < .05, the test results may be considered

acceptable at the 95% confidence level, and the results are unlikely to change.

With a value of p < 0.01 the test results can be considered acceptable at the 99%

confidence level. The SPSS results from the multiple linear regressions to test

the relationship in the model and to determine to what degree the dependent

variable is explained by the independent variables are presented in the following

sections. Though prior studies have demonstrated that demographic variables


75

are potential predictors of organizational commitment (Avolio 2004), all the

demographic variables in this study correlated hardly with the dependent

variable and hence, their effects have been removed from the regression

analysis. (Regression chart outputs are annexed See APPENDIX- G)

4.5.1.1. Nature & Strength of the Effect

As shown in Table 4-9, HRV and OSV significantly predicted OE (β =

0.272, p < 0.01 and β = 0.338, p < 0.01, respectively). The VIF values less than

10 and tolerance values greater than 0.2 indicates there is no problem of

multicollinearity.

Table 4-9: Coefficients Result

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.

Collinearity Statistics

B Std.

Error Beta Tolerance VIF

1 (Constant) 1.021 .239 4.277 .000

HRV .401 .113 .272 3.544 .000 .446 2.242 OSV .412 .094 .338 4.398 .000 .446 2.242

a. Dependent Variable: OE Source: Researcher’s own computation

Figure 4-1 provides a diagrammatic view of the relationship between HRV and

OSV on OE.

Figure 4-1: Relationship between HRV and OSV on Organizational Effectiveness

Independent Variables Dependent Variable β = .272, p < .01 β = .338, p < .01

Human Relations Values (X1)

Open Systems Values (X2)

Organizational effectiveness (Y)


76

Referring back to Table 4-9, “B” values were extracted and the following

regression equation was derived:

OE= 1.021 + 0.401 (HRV) + 0.412 (OSV)

Therefore, according to the regression equation, HRV and OSV have a

positive influence on OE. Table 4-10 shows the strength of the above

relationship as indicated by the adjusted R Square value which in this case is

0.319, and is considered as low positive correlation (Collis & Roger Hussey

2003). The difference for the final model is small (in fact the difference between

the values is .325 − .319 = .005 (about 0.6%). This shrinkage means that if the

model were derived from the population rather than a sample it would account

for approximately 0.6% less variance in the outcome.

Another important point to notice from Table 4-10 is the Durbin–

Watson test that tests for serial correlations between errors in regression

models (Field 2009). Specifically, it tests whether adjacent residuals are

correlated, which is useful in assessing the assumption of independent errors

(Field 2009). Values less than 2 indicate a tendency for observations that are

close in time to be similar (positive autocorrelation), values greater than 2

indicate a tendency for close observations to be different (negative

autocorrelation) and values close to 2 indicates there is no autocorrelation. In

this result, the Durbin-Watson test does assume that the regression residuals

are normally distributed (Manly 2009: 191).


77

Table 4-10: Model Summary for the Strength of Relationship

Model Summaryb

Model R R

Square

Adjusted R

Square

Change Statistics

Durbin-

Watson

R Square Change

F Change df1 df2

Sig. F Chang

e 1 .570a .325 .319 .325 61.765 2 257 .000 1.974

a. Predictors: (Constant), Open Systems Values, Human Relations Values b. Dependent Variable: OE Source: Researcher’s own computation

4.5.1.2. Explanation of the hypothesis

Null hypothesis 1: The aggregated HRV & OSV of OC do not predict the OE

that is measured by employees’ Organizational commitment.

The Multiple Linear Regression analyses discussed above indicate that

the effect of HRV significantly predicted OE (β = .272, p < .05). The

independent variable HRV significantly predicts the dependent variable OE,

which reflects the research findings from the organic view of CVM model of

Quinn and Rohrbaugh (1983) on organizational effectiveness. This indicates

that in the natural system approach employees perceive that OC is important

(exhibit high HRV such as morale and cohesion) and has an impact on their

behavioral intentions to give more emphasis on human resource development.

This, in turn, places OC as a leading indicator of organisational performance

that contributes to OE (Srivastav 2009).

The Multiple Linear Regression analyses indicate also OSV significantly

predicted OE (β = .338, p < .05). The independent variable OSV significantly

predicts the dependent variable OE, which reflects the research findings from

the organic view of CVM model of Quinn and Rohrbaugh (1983) on

organizational effectiveness. This indicates that in the natural system approach

employees perceive that OC is important (exhibit high OSV such as flexibility


78

and readiness) and has an impact on their behavioral intentions to give more

emphasis on growth and resource acquisition. This, in turn, places OC as a key

motivational factor for organizational change that contributes to OE (Lehman et

al. 2002).

Most importantly, in the model summary, R square of .325 indicates

32.5% of the variation in OE is explained by HRV & OSV combined. The

remaining 67.5% variation in OE is explained by factors not included in the

model, essentially, contributed by either the untapped items (5 items from

Autonomy dimension, 1 item from Outward Focus dimension, and 2 items from

Reflexivity dimension) or contributed by the other two organizational values of

the quadrants of CVM; Rational Goal Values (RGV) & Internal Process Values

(IPV) or might be explained by both factors. HRV & OSV combined proved to

contribute almost 65% of the variation on the half segment of the CVM. In a

summary, the multiple linear regression test undertaken above proved that the

null hypothesis 1 is rejected.

4.5.2. Testing of Hypothesis Two (relationships between variables)

Pearson's product-moment correlation coefficient (r) was used to

determine the strength of association between the specific dimensions and

domains of OC. Pearson's product moment correlation coefficient (r) is a

parametric technique which gives a measure of the strength of association

between two variables (Collis & Roger Hussey 2003).

4.5.2.1. Nature & Strength of Relationship

As shown in Table 4-11, Involvement, Supervisory Support, Training

and Welfare have shown high positive correlation with HRV (r = .736, .868,

.766, and .848 at p < 0.01 respectively). In contrast, Integration have shown


79

medium positive correlation with HRV (r = .622) (Collis & Roger Hussey 2003;

Patterson et al. 2005). The coefficient of determination, R2 that determines

the amount of variability in one variable that is shared by the other (Field

2009), shows that Integration shares 38.7% of the variability in HRV,

Involvement shares 54.2% of the variability in HRV, Supervisory Support

shares 75.3% of the variability in HRV, Training shares 58.7% of the variability

in HRV, and Welfare shares 71.9% of the variability in HRV. Therefore the

Condition for hypothesis test is met.

Table 4-11: Pearson Correlations of dimensions with Human Relations Values

Variables HRV Integration

Involvement

Supervisory

Support

Emphasis on

Training Welfare

HRV 1 Integration .622** 1 Involvement .736** .539** 1 Supervisory Support .868** .433** .584** 1 Emphasis on Training .766** .390** .552** .543** 1

Welfare .848** .468** .545** .741** .616** 1 **. Correlation is significant p < 0.01 level (1-tailed). Source: Researcher’s own computation Figure 4-2 provides a diagrammatic view of the relationship between the

dimensions; Integration, Involvement, Supervisory Support, Training and

Welfare with HRV domain.

Figure 4-2: Relationships of Dimensions of OC with HRV

Dimensions Domain R2 = .387, p < .01 R2= .542, p < .01 R2 = .753, p < .01 R2 = .587, p < .01 R2= .719, p < .01

Integration

Supervisory Support

Training

Welfare

Involvement

Human Relations

Values (HRV)


80


Null hypothesis 2: The dimensions of OC (Integration, Involvement,

Supervisory Support, Training, and Welfare) do not

positively related with HRV of flexible orientation.

The Pearson's product moment correlation coefficient analyses discussed

above indicate that Integration, Involvement, Supervisory Support, Training

and Welfare have shown high and medium positive correlation with HRV (r =

.622, .736, .868, .766, and .848 at p < 0.01 respectively).

Although Integration, Involvement, Supervisory Support, Training and

Welfare can account for 38.7%, 54.2% , 75.3% , 58.7% , and 71.9% of the

variation in HRV respectively, it does not necessarily cause this variation and

this still says nothing about which way causality runs. It can only express in

terms of “the variance in y accounted for by x ”, or even the variation in one

variable explained by the other (Collis & Roger Hussey 2003; Field 2009). The

research findings from the competing values framework perspective proved that

the climate strength of all or most climate dimensions within a quadrant inter-

correlate highly as a predictor of organizational outcomes (Patterson et al

2005). Previous research conducted in Pakistan work environment by Iqbal

(2007) has proved that statistically significant correlations between some

dimensions of OC and organizational commitment (r = 0.38, P < 0.01 and r =

0.24, P < 0.01 for Challenge & Involvement and Trust & Openness dimensions

respectively), which is consistent with this findings.

Above all, the results have shown that employees of public institutions do

not only perceive the dimensions of HRV positively but also it has strong effect


81

on their behavioural intentions of HRV such as morale, cohesion, trust and

belongingness (Reino & Vadi 2010).

The findings also reveal that in relative terms, supervisory support found

to be the major dominant factor and Integration is the least dominant factor

among the HRV domain in influencing employees’ perception. This is somewhat

contradictorily answered by respondents in the cross-checking question (see

APPENDIX- I) whether they do believe their organization is effective in doing

its job, the majority respondents suggested that Welfare & Emphasis on

training should be viewed as a first intervention strategy in improving the work

environment. In a summary, Pearson's product-moment correlation coefficient

analysis undertaken above proved that the null hypothesis 2 is rejected.

4.5.3. Testing of Hypothesis Three (relationships between variables)

Pearson's product-moment correlation coefficient (r) was used to

determine the strength of association between the specific dimensions and

domains of OC.

4.5.3.1. Nature & Strength of Relationship

As shown in Table 4-12, Innovation & Flexibility indicates very high

positive correlation with OSV (r = .987; p< 0.01). In contrast, Reflexivity, have

demonstrated medium positive correlation with OSV (r = .677 at p < 0.01) and

Outward Focus have demonstrated low positive correlation with OSV (r = .367

at p < 0.01) (Collis & Roger Hussey 2003; Patterson et al. 2005). The

coefficient of determination, R2 shows that Innovation & Flexibility shares

97.4% of the variability in OSV, Outward Focus shares 13.5% of the variability


82

in OSV, and Reflexivity shares 45.8% of the variability in OSV. Therefore the


Table 4-12: Pearson Correlations of dimensions with Open Systems Values

Variables OSV

Innovation &

Flexibility

Outward Focus Reflexivity

OSV 1 Innovation & Flexibility .987** 1 Outward Focus .367** .383** 1 Reflexivity .677** .676** .403** 1 **. Correlation is significant p < 0.01 level (1-tailed). Source: Researcher’s own computation Figure 4-3 provides a diagrammatic view of the relationship between the

dimensions; Innovation & Flexibility, Outward Focus, and Reflexivity with

OSV domain.

Figure 4-3: Relationships of Dimensions of OC with OSV


Null hypothesis 3: The dimensions of OC (Innovation & flexibility,

Reflexivity, and Outward focus) do not positively related

with OSV of flexible orientation.

The Pearson's product moment correlation coefficient analyses discussed

above indicate that Innovation & Flexibility, Outward Focus, and Reflexivity

Dimensions Domain R2 = .974, p < .01 R2 = .135, p < .01 R2= .458, p < .01


Outward Focus

Reflexivity

Open Systems Values (OSV)


83

have shown high, medium and low positive correlation with OSV (r = .987, .677,

and .367 at p < 0.01) respectively.

Although Innovation & Flexibility, Outward Focus, and Reflexivity can

account for 97.4%, 13.5%, and 45.8% of the variation in OSV respectively, it does

not necessarily cause this variation and this still says nothing about which way

causality runs. It can only express in terms of ‘the variance in y accounted for by

x’, or even the variation in one variable explained by the other (Collis & Roger

Hussey 2003; Field 2009). The research findings from the competing values

framework perspective proved that the climate strength of all or most climate

dimensions within a quadrant inter-correlate highly as a predictor of

organizational outcomes (Patterson et al 2005). Above all, the results have

shown that employees of public institutions do not only perceive the dimensions

of OSV positively but also it has strong effect on their behavioural intentions of

OSV that encompasses values such as flexibility, external organizational

orientation, adaptability, the capacity to change, uniqueness and an orientation

towards customers (Reino & Vadi 2010).

The findings also reveal that in relative terms, Innovation & Flexibility

found to be the major dominant factor and Outward Focus is the least

dominant factor among the OSV domain in influencing employees’ perception.

This is somewhat contradictorily, tied-up answer obtained in the cross-checking

question (see APPENDIX- I) whether they do believe their organization is

effective in doing its job, the majority respondents suggested that Innovation &

Flexibility should be viewed as a first intervention strategy in improving the

work environment. On other hand, the same size respondents suggested

Innovation & Flexibility to be considered as the last option. However, the


84

former group’s opinion is supported since it seems realistically suggested. In a

summary, Pearson's product-moment correlation coefficient analysis

undertaken above proved that the null hypothesis 3 is rejected.

4.5.4. Testing of Hypothesis Four (difference between gender)

Independent Samples t-test, a test that uses the t-statistic to establish

whether two means collected from independent samples differ significantly

(Field 2009). The t-test compares two means, when those means have come

from different groups of entities and a significant result under Levene’s Test for

Equality of Variance indicates that the variances are significantly different –

therefore, the assumption of homogeneity of variances has been violated (Field

2009). If the Sig. value of Levene’s test is bigger than .05 then you should look

at the row in the table, labelled Equal variances assumed and the F-ratio is,

therefore, a measure of the ratio of systematic variation to unsystematic

variation (Field 2009).

To discover whether the effect is substantive it is important to know

about effect sizes by converting a t-value into an r-value using the following

formula and a value of .5 is the threshold for a large effect (Field 2009: 332).

𝑟 = �t2

t2 + df

4.5.4.1. Nature & Strength of Difference

Table 4-13 shows the results of Independent-samples t-test, on average,

Males experienced greater positive perception to OE (M = 3.53, SE = 0.09) than

to Females (M = 3.42, SE = 0.10), greater positive perception to HRV (M = 3.06,

SE = 0.06) than to Females (M = 3.05, SE = 0.07), and greater positive

perception to OSV (M = 3.04, SE = 0.07) than to Females (M = 2.96, SE =


85

0.09). This difference was not significant, t (209.6) = .829, p > .05 for OE; not

significant, t (258) = .151, p > .05 for HRV; and not significant, t (258) = .685, p

> .05 for OSV.

Table 4-13: Independent-Samples T-test for Gender

Group Statistics Variables Gender N Mean Std. Deviation Std. Error Mean

OE Males 169 3.5266 1.11126 .08548 Females 91 3.4176 .95400 .10001

HRV Males 169 3.0645 .73498 .05654 Females 91 3.0503 .68793 .07211

OSV Males 169 3.0355 .86694 .06669 Females 91 2.9582 .86949 .09115

Levene's Test for Equality of Variances t-test for Equality of Means Variables Condition F Sig. t df Sig. (2-tailed)

OE

Equal variances assumed

4.213 .041 .792 258 .429

Equal variances not assumed

.829 209.613 .408

HRV


.790 .375 .151 258 .880


.154 195.141 .877

OSV


.313 .576 .685 258 .494


.684 183.913 .495



Null hypothesis 4: There is no significant difference between employees’

perception of OC in terms of employees’ Gender in HRV,

OSV and OE across public sectors.

The Independent-Samples t-test discussed above indicated that Males

experienced greater positive perception to all three variables of OE, HRV and

OSV in which, the difference in perception in all cases was not significant (t

(209.6) = .829, p > .05), (t (258) = .151, p > .05) and (t (258) = .685, p > .05)


86

than to Females respectively. This will lead us to a conclusion that male and

female do not differ in their perception of OC and on OE.

The research findings proved that consistent result obtained with the

previous research conducted by Idogho (2006) on Nigerian academic staff of

universities, in which he found that male and female do not differ in their

perception of OC [F (1, 4092) = 1.530, P > 0.05)]. In a summary, Independent-

Samples t-test undertaken above proved that there is no ground for the null

hypothesis 4 to be rejected for OC and OE.

4.5.5. Testing of Hypothesis Five (difference between tenure)

One-way independent ANOVA test was used to test for differences

between several independent groups. The one-way independent ANOVA

compares several means, when those means have come from different groups of

people based on respondents Tenure. (Homogeneity test of Variance for

grouping variables is annexed see APPENDIX- H)


Table 4-14 shows there was no significant difference observed in

employees perception based on Tenure in terms of OE, F (4, 245) = 1.151, p

>.05. There was no significant difference observed in employees perception

based on Tenure in terms of HRV, F (4, 245) = .918, p >.05. There was no

significant difference observed in employees perception based on Tenure in

terms of OSV, F (4, 245) = .864, p >.05. Therefore the Condition for hypothesis

test is met.


87

Table 4-14: One-Way Independent ANOVA test for Tenure

Sum of

Squares df

Mean Square

F Sig.

OE

Between Groups 5.030 4 1.258 1.151 .333 Within Groups 267.690 245 1.093 Total 272.720 249

HRV

Between Groups 1.958 4 .489 .918 .454 Within Groups 130.606 245 .533 Total 132.564 249

OSV

Between Groups 2.520 4 .630 .864 .486 Within Groups 178.597 245 .729 Total 181.117 249




perception of OC in terms of employees’ Tenure in HRV, OSV

and OE across public sectors.

The One-way Independent ANOVA test discussed above indicate that

there was no significant difference in Tenure exhibited in a period of job

possession in terms of employees perception of OC and organizational

commitment; OE, F (4, 245) = 1.151, p >.05, HRV, F (4, 245) = .918, p >.05, and

OSV, F (4, 245) = .864, p >.05.

The research findings proved that consistent result obtained with the

previous research conducted by Idogho (2006) on Nigerian academic staff of

universities, in which he found that no difference exist between young and older

academic staff in their perception of OC [F (1, 4092) = 0.002, P > 0.05)]. In a

summary, One-way Independent ANOVA test undertaken above proved that

there was no ground for the null hypothesis 5 to be rejected for OC factors of

HRV & OSV and OE.


88

4.5.6. Testing Hypothesis Six (difference between education level)

One-way independent ANOVA test was used to test for differences

between several independent groups. The one-way independent ANOVA

compares several means, when those means have come from different groups of

people based on respondents education level.


Table 4-15 shows there was no significant difference observed in

employees perception based on Education level in terms of OE, F (4, 247) =

1.918, p >.05. There was no significant difference observed in employees

perception based on Education level in terms of HRV, F (4, 247) = .369, p >.05.

There was no significant difference observed in employees perception based on

Education level in terms of OSV, F (4, 247) = .995, p >.05. Therefore the


Table 4-15: One-Way Independent ANOVA test for Education level

Sum of Squares

df Mean

Square F Sig.

OE Between Groups 8.506 4 2.126 1.918 .108 Within Groups 273.799 247 1.108

Total 282.305 251

HRV Between Groups .786 4 .197 .369 .831 Within Groups 131.586 247 .533

Total 132.372 251

OSV Between Groups 2.940 4 .735 .995 .411 Within Groups 182.420 247 .739

Total 185.360 251



89



perception of OC in terms of Education level in human

relations, OSV and OE across public sectors.

The One-way Independent ANOVA test discussed above indicated that

there was no significant difference in Education level exhibited whether the

employee is qualified or not in terms of employees perception of OC and

organizational commitment. OE, F (4, 247) = 1.92, p >.05, HRV, F (4, 247) =

.369, p >.05, and OSV, F (4, 247) = .995, p >.05.

The research findings proved that employees’ background in educational

qualification has nothing to do with employees’ perception towards OC. In a

summary, One-way Independent ANOVA test undertaken above proved that

there was no ground for the null hypothesis 6 to be rejected for OC factors of

HRV & OSV and OE.

4.5.7. Testing Hypothesis Seven (difference between organization type)

One-way independent ANOVA test and Independent-sample t-test were

used to test for differences between several independent groups. The one-way

independent ANOVA compares several means, when those means have come

from different groups of people based on respondents’ organization type. The t-

test compares two means, when those means have come from different groups

of entities.


90


Table 4-16 shows there was a significant difference observed in

employees perception based on the type of organization in terms of OE, F (5,

254) = 2.395, p <.05 with a mean of OGADT = 3.84, BoTVT = 3.67, BoCTPD =

3.53, BoEPLA = 3.47, BoE = 3.28, and BoWYCA = 3.19. There was no significant

difference observed in employees perception based on the type of organization

in terms of HRV, F (5, 254) = 2.081, p >.05. There was a significant difference

observed in employees perception based on the type of organization in terms of

OSV, F (5, 254) = 3.67, p <.05 with a mean of OGADT = 3.39, BoCTPD = 3.09,

BoEPLA = 2.99, BoTVT = 2.93, BoE = 2.91, and BoWYCA = 2.65. Therefore the


Table 4-16: One-Way Independent ANOVA test for Organization Type

Sum of

Squares df Mean

Square F Sig.

OE

Between Groups 13.059 5 2.612 2.395 .038 Within Groups 277.017 254 1.091 Total 290.076 259

HRV Between Groups 5.248 5 1.050 2.081 .068 Within Groups 128.108 254 .504 Total 133.356 259

OSV Between Groups 13.115 5 2.623 3.670 .003 Within Groups 181.546 254 .715 Total 194.661 259


Table 4-17 shows the result of Independent-sample t-test run for each

grouping that 9 out of 45 tests conducted revealed statistically significant

differences in the perception of organizational climate. At least two significant

differences exist in each factor. At least one significant difference exists for each

pair of organization grouping. Organizational climate is, therefore, not uniform,

but differential across various groups across organizations.


91

Table 4-17: Strength of difference for organization types

Pair of groups for Organizations

t-values OE HRV OSV

BoE Vs BoTVT -1.726 .321 -.114 BoE Vs BoEPLA -.778 -1.421 -.411 BoE Vs OGADT -2.691** -1.724 -3.021**

BoE Vs BoCTPD -1.193 -.121 -1.041 BoE Vs BoWYCA .397 1.301 1.654 BoTVT Vs BoEPLA .814 -1.581 -.282 BoTVT Vs OGADT -.767 -1.839 -2.617*

BoTVT Vs BoCTPD .589 -.400 -.853 BoTVT Vs BoWYCA 2.152* .889 1.733 BoEPLA Vs OGADT -1.520 -.134 -1.930 BoEPLA Vs BoCTPD -.249 1.212 -.426 BoEPLA Vs BoWYCA 1.126 2.542* 1.713 OGADT Vs BoCTPD 1.419 1.479 1.664 OGADT Vs BoWYCA 2.948** 2.851** 4.603***

BoCTPD Vs BoWYCA 1.497 1.312 2.548*

Notes: * p<=.05, **p<= .01 and ***p<= .001 Source: Researcher’s own computation



perception of OC in terms of type of organization in HRV,

OSV and OE across public sectors.

The One-way Independent ANOVA test discussed above indicate that

there is significant difference in employees perception across Organizations in

terms of OE (F (5, 254) = 2.395, p <.05) with a mean of OGADT = 3.84, BoTVT

= 3.67, BoCTPD = 3.53, BoEPLA = 3.47, BoE = 3.28, and BoWYCA = 3.19 and

OSV (F (5, 254) = 3.67, p <.05) with a mean of OGADT = 3.39, BoCTPD = 3.09,

BoEPLA = 2.99, BoTVT = 2.93, BoE = 2.91, and BoWYCA = 2.65 of the OC. On

other hand, no significance difference observed in HRV (F (5, 254) = 2.081, p

>.05) of employees perception across public organizations. OGADT & BoWYCA

are the two organizations, which exhibited extreme values in employees’


92

perception in both cases that impart significant difference in perception of the

OC. Furthermore, the Independent-sample t-test reveals nine (20%) out of 45

tests conducted revealed statistically significant differences in the perception of

organizational climate between organizations.

The research findings proved that partial result obtained with the

previous research conducted by Idogho (2006) on academic staff of Edo state

Universities that indicated the existence of significant difference among

universities in their perception of OC [F (3, 4091) = 12.545, P < 0.05)], which

are not categorized as human relations or open systems values. This makes the

obtained result differentiated from the previous researches. In a summary, One-

way Independent ANOVA test undertaken above proved that the null hypothesis

7 can be rejected for OC factor of OSV and OE. However, there is no ground for

the null hypothesis 7 to be rejected for OC factor of HRV.

4.5.8. Testing of Hypothesis eight (difference between work groups)

Independent Samples t-test was used to determine the difference and its

significance by comparing the means of two work groups in which the

respondents are working in.


Table 4-18 shows the results of Independent-samples t-test, on average,

employees in Core processes experienced greater positive perception to OE (M =

3.56, SE = 0.08) than to employees in Support processes (M = 3.39, SE = 0.11).

On other hand, on average, employees in Support processes experienced greater

positive perception to HRV (M = 3.08, SE = 0.07) than to employees in Core

processes (M = 3.04, SE = 0.06) and on average, employees in Support


93

processes experienced almost equal positive perception to OSV (M = 3.01, SE =

0.09) with employees in Core processes (M = 3.01, SE = 0.07). However, the

differences in OE & HRV were not significant t (258) = 1.291, p > .05 for OE; not

significant t (258) = -.381, p > .05 for HRV; and not significant t (258) = -.038,

p > .05 for OSV. Therefore the Condition for hypothesis test is met.

Table 4-18: Independent-Samples T-test between for Work Processes

Group Statistics Variables Business Processes N Mean Std. Deviation Std. Error Mean

OE Core Process 149 3.5615 1.01126 .08285 Support Process 111 3.3904 1.11543 .10587

HRV Core Process 149 3.0449 .68989 .05652 Support Process 111 3.0792 .75583 .07174

OSV Core Process 149 3.0067 .80216 .06572 Support Process 111 3.0108 .95073 .09024

Levene's Test for Equality of Variances t-test for Equality of Means Variables Condition F Sig. t df Sig. (2-tailed)

OE


.692 .406 1.291 258 .198


1.273 223.634 .204

HRV


.998 .319 -.381 258 .704


-.376 224.608 .707

OSV


3.669

.057 -.038 258 .970


-.037 213.071 .971




perception of OC in terms of work processes in HRV, OSV

and OE across public sectors.

The Independent-Samples t-test discussed above indicate that employees

in Core work processes experienced greater positive perception to OE than

employees in Support processes in which, the difference in perception is not


94

significant (t (258) = 1.291, p > .05). On other hand, employees in Support

processes experienced greater positive perception to HRV than employees in

Core processes in which, the difference in perception is not significant (t (258) =

-.381, p > .05). Lastly, employees in Support processes experienced almost equal

positive perception to OSV with employees in Core processes in which, their

perception is not significant t (258) = -.038, p > .05.

The research findings produces contradictory result with previously

studied related topics that was conducted on 155 individuals drawn from 27

hospital management teams by N. R. Anderson & M. A. West (1998), which

states there is variation in level of agreement both across teams within samples

and within teams across particular dimensions. In a summary, Independent-

Samples t-test undertaken above proved that there is no ground for the null

hypothesis 8 to be rejected for OE as well as for OC factors of HRV and OSV.


95

CHAPTER V – SUMMARY, CONCLUSIONS &

RECOMMENDATIONS

5.1. INTRODUCTION

This chapter presents the concluding part of the research project. Section

5.1 provides an introduction to the chapter. Section 5.2 focuses on the major

findings while Section 5.3 is the conclusion for the research. Finally, Section 5.4

provides implications and recommendations for future research.

5.2. SUMMARY

Chapter 4 presented the research results that were generated by SPSS software.

The results include the demographics of respondents, namely: gender,

education level, work groups they are working in and years of experience in the

latest organization. The majority of respondents are male (63.2%). The finding

is representative of the ANRS public institutions work force at regional level,

and is consistent with statistic for civil servants (Bureau of Finance and

Economic Development, 2011). The majority of respondents are from core work

processes (57.3%) and the majority of respondents were holders of Bachelor

degree and above (71.1%). The majority of respondents have worked in the

present institution more than 5 years (57.6%). Except for educational level the

sample is representative of the distribution of ANRS civil servants at regional

level (Bureau of Civil Service 2010). Prior studies have demonstrated that these

demographic variables are potential predictors of organizational commitment

(Avolio 2004)

For testing the eight hypotheses in accordance with the research model in

Figure 2-4, various statistical tests were adopted to reject the null hypotheses.


96

For null hypothesis 1, Multiple Linear Regression was used to

determine the effects of the two independent variables (HRV and OSV) on the

dependent variable (OE) measured indirectly by organizational commitment

(Speier & Venkatesh 2002).

The results show that the conditions for regression analysis have been

met and the independent variables significantly predicted the dependent

variable.

The Multiple Linear Regression together with the relationship described

in Sections 4.5.1.1and 4.5.1.2, demonstrate that Hypothesis 1 was not supported,

rather HRV and OSV significantly predicted OE (β = .272, p < .05) and (β =

.338, p < .05) respectively. In the regression model summary, R square of .325

indicates 32.5% of the variation in OE is explained by HRV & OSV combined.

The remaining 67.5% variation in OE is probably explained by factors not

included in the model, essentially, by the other two values in the quadrants of

CVM; Rational Goal Values (RGV) & Internal Process Values (IPV) or either

explained by the remaining untapped items or both. HRV & OSV contribute

around 65% of the variation on the half segment of the CVM if we assume that

the full model is split into two segments proportionately.

The research finding does not support null Hypothesis 1 and is consistent

with prior theory and research in that OC positively & significantly influence on

employees’ perception of their work environment and impacts upon OE (Quinn

and Rohrbaugh 1983). Employees’ psychological capital is positively related to

their performance, satisfaction, and commitment and that a supportive climate

is related to employees’ satisfaction and commitment(Bakker & Schaufeli

2008). Moreover, according to CVM about 50% of the variation in OE should


97

have to be explained by HRV & OSV domains (Quinn & Rohrbaugh 1983).

However, in this study, 32.5% of the variation was proved been accounted by the

two quadrants of CVM; HRV and OSV.

This indicates that in the natural system approach employees perceive

that OC is important (exhibit high HRV such as morale and cohesion, and high

OSV such as flexibility and readiness) and has an impact on their behavioral

intentions to give more emphasis on human resource development and growth

and resource acquisition. This, in turn, places OC as a leading indicator of

organisational performance and as a key motivational factor for organizational

change that contributes to OE (Srivastav 2009; Lehman et al. 2002).

Since the alternate hypothesis was supported, the research question has

been answered, in that the OE of public sectors in ANRS that is measured by

employees’ organizational commitment are highly predicted by the flexible

orientation internal & external values of OC.

For null hypothesis 2 & 3, Pearson's product-moment correlation

coefficient (r) was used to determine the strength of association between the

specific dimensions and domains of OC. The result indicates that Involvement,

Supervisory Support, Training and Welfare have shown high positive

correlation with HRV (r = .736, .868, .766, and .848 at p < 0.01 respectively). In

contrast, Integration have shown medium positive correlation with HRV (r =

.622) accounting with determination of coefficient, R2, of 38.7%, 54.2%,

75.3%, 58.7%, and 71.9% of the variation in sub-scales of Integration,

Involvement, Supervisory Support, Training, and Welfare in the HRV of OC

respectively.


98

On other hand, Innovation & Flexibility indicates very high positive

correlation with OSV (r = .987; p< 0.01). In contrast, Reflexivity have

demonstrated medium positive correlation with OSV (r = .677 at p < 0.01) and

Outward Focus have demonstrated low positive correlation with OSV (r = .367

at p < 0.01) accounting with determination of coefficient, R2, of 97.4%,

13.5%, and 45.8% of the variation in sub-scales of Innovation & Flexibility,

Outward Focus, and Reflexivity in the OSV of OC respectively.

The research finding does not support null Hypotheses 2 & 3 and is

consistent with prior theory and research conducted on competing values

framework that the climate strength of all or most climate dimensions within a

CVM quadrant inter-correlate significantly as a predictor of organizational

outcomes such as organizational commitment (Iqbal 2007; Patterson et al.

2005)

The results have shown that employees of public institutions do not only

perceive the dimensions in the HRV and OSV domain of OC positively, but also

their perception has strong effect on their behavioural intentions of HRV such

as morale, cohesion, trust and belongingness. This is true also for OSV that

encompasses values such as flexibility, external organizational orientation,

adaptability, the capacity to change, uniqueness and an orientation towards

customers (Reino & Vadi 2010).

The findings also reveal that in relative terms Supervisory support and

Innovation & Flexibility found to be the dominant factors under HRV and OSV

domain of OC in influencing employees’ perception respectively. Integration

and Outward Focus are the least among the HRV and OSV domain of OC in

influencing employees’ perception respectively.


99

Since both alternate hypotheses 2 & 3 were supported, the research

questions has been answered, in that there is significant positive relationship

between the dimensions of OC and both HRV (internal focus) and OSV (external

focus) of flexible orientation.

For null hypothesis 4 & 8, Independent Samples t-test was used to

determine the difference and its significance by comparing the means of two

groups of gender and work processes with respect to employees’ perception

towards to OC. It was found that Males experienced greater positive perception

to OE (M = 3.53, SE = 0.09) than to Females (M = 3.42, SE = 0.10), greater

positive perception to HRV (M = 3.06, SE = 0.06) than to Females (M = 3.05,

SE = 0.07), and greater positive perception to OSV (M = 3.04, SE = 0.07) than

to Females (M = 2.96, SE = 0.09). However, the difference was not significant, t

(209.6) = .829, p > .05 for OE; not significant, t (258) = .151, p > .05 for HRV;

and not significant, t (258) = .685, p > .05 for OSV.

Employees in Core processes experienced greater positive perception to

OE (M = 3.56, SE = 0.08) than to employees in Support processes (M = 3.39, SE

= 0.11). On other hand, on average, employees in Support processes experienced

greater positive perception to HRV (M = 3.08, SE = 0.07) than to employees in

Core processes (M = 3.04, SE = 0.06) and on average, employees in Support

processes experienced almost equal positive perception to OSV (M = 3.01, SE =

0.09) with employees in Core processes (M = 3.01, SE = 0.07). However, the

differences in perceptions were not significant t (258) = 1.291, p > .05 for OE;

not significant t (258) = -.381, p > .05 for HRV; and not significant t (258) = -

.038, p > .05 for OSV.


100

The research findings was consistent with the previous research that

states male and female do not differ in their perception of OC (Idogho 2006).

On the contrary, contradictory result obtained with regard to work processes

with previously studied related topics that states there is variation in level of

agreement both across teams within samples and within teams across particular

dimensions (Anderson & West 1998; Srivastav 2009). However, it cannot

arguably be ruled out that the organizational dynamism could have significant

impact in today’s work environment than long time ago to rely more on latest

phenomena.

Even though, both null hypotheses 4 & 8 were supported for all factors in

the same manner, the research questions has been answered, in that there is no

significance difference between employees’ perception of OC in terms of

employees’ gender and work processes in HRV, OSV and OE across public

sectors.

For null hypothesis 5, 6 & 7, One-way independent ANOVA test was

used to test for differences between several independent groups. The one-way

independent ANOVA compares several means, when those means have come

from different groups of people based on respondents’ tenure, education level,

and organization type. It was found that based on employees tenure, no

significant difference in Tenure exhibited in a period of job possession in terms

of employees’ perception of OC and organizational commitment; OE, F (4, 245)

= 1.151, p >.05, HRV, F (4, 245) = .918, p >.05, and OSV, F (4, 245) = .864, p

>.05. There was no significant difference observed either in employees’

perception based on Education level in terms of OE, F (4, 247) = 1.918, p >.05,

in terms of HRV, F (4, 247) = .369, p >.05, and in terms of OSV, F (4, 247) =


101

.995, p >.05. On other hand, there is significant difference in employees

perception across Organizations in terms of OE (F (5, 254) = 2.395, p <.05) and

OSV, F (5, 254) = 3.67, p <.05) of the OC in which nine (20%) out of 45 tests

conducted revealed statistically significant differences in the perception of

organizational climate between organizations. However, no significance

difference observed in HRV, F (5, 254) = 2.081, p >.05) of employees perception

across public organizations.

The research findings proved that in terms of tenure, consistent result

obtained with the previous research conducted on academic staff of universities

in which there is no difference exist between young and older academic staff

(Idogho 2006). In terms of education level, even though no previous research

found to contrast with, the findings proved that employees’ background in

educational qualification has nothing to do with employees’ perception towards

OC. In terms of differences in organization type, partial result obtained with the

previous research conducted on academic staff of Universities that indicated the

existence of significant difference among universities in their perception of OC

(Idogho 2006) even if the unit of analysis are aggregated by human relations or

open systems values. The measuring instrument should demonstrate significant

differences in employee perceptions across organizations if it is to be useful in

discriminating between organizations (Patterson et al 2005).

Since, both null hypotheses of 5 & 6 were supported, the research

questions has been answered, in that there is no significance difference between

employees’ perception of OC in terms of employees’ tenure and education level

in HRV, OSV and OE across public sectors. On other hand, null hypothesis 7 is

partially supported in which the research questions have been answered, in that


102

there is significance difference between employees’ perception of OC in terms of

OE & OSV. However, there is no significance difference between employees’

perception of OC in terms of organization type in HRV.

5.3. CONCLUSION

The ANRS public service management is slow becoming nexus between

government deliverables and citizens demand. To maintain efficiency in service

delivery in Amhara is somehow illusive because employees have an inherent

exposition on how the work environment could be crafted to suit the general

public. One such view is OC in which it was described in the introduction part as

employees’ perception of how it feels to work in the unit, and includes specific

aspects of the environment that directly affect people's ability to get the job

done.

The literature review in Chapter 2 indicates that OC can be used as a tool

to assess employee perception towards organizational practices in the notion of

upholding participatory management. Public institutions around the world,

these days, are becoming heavily accountable in their service delivery to bring

about customer satisfaction. Investigations have indicated that employees have

positive outlook and capable of sharing their responsibilities on the work

environment. This is a significant breakthrough for bolstering the

organizational change process that can be achieved within the realm of reform

programs.

Findings from the literature review indicate that there is a lack of

localized empirical research in the country that relates OC to organizational

effectiveness, especially in the public service institutions. Therefore, to bridge

this gap, the following research questions were developed: (a) To what extent


103

does the OE of public sectors that is measured by organizational commitment of

employees are explained by the internal & external values of OC? (b) Is there

any significance positive relationship between the dimensions of OC and HRV

(internal focus) of flexible orientation? (c) Is there any significance positive

relationship between the dimensions of OC and OSV(external focus) of flexible

orientation?, and (d) Is there any significance difference between employees’

perception of OC in terms of employees’ gender, tenure, education level,

organization type, and work processes in HRV, OSVand OE across public

sectors?

From the research problem and research question, a research model was

developed adapted from competing values model. The model adopts HRV and

OSV as two aggregated independent variables, which are direct antecedents of

OE. Within each aggregated independent variables, there are sub-scales in

which for HRV there are Integration, Involvement, Supervisory Support,

Emphasis on Training, and Welfare and for OSV, there are Innovation &

Flexibility, Outward Focus, and Reflexivity. The last construct is OE as the

dependent variable measured by organizational commitment.

As part of the research model, eight hypotheses were derived, namely: (a)

The aggregated HRV & OSV of OC do not predict the OE that is measured by

employees’ organizational commitment. (b) The dimensions of OC (Integration,

Involvement, Supervisory Support, Training, and Welfare) do not positively

relate with HRV of flexible orientation. (c) The dimensions of OC (Innovation &

flexibility, Reflexivity, and Outward focus) do not positively relate with OSV of

flexible orientation. (d) There is no significant difference between employees’

perception of OC in terms of employees’ Gender in HRV, OSV and OE across


104

public sectors. (e) There is no significant difference between employees’

perception of OC in terms of employees’ Tenure in HRV, OSV and OE across

public sectors. (f) There is no significant difference between employees’

perception of OC in terms of Education level in HRV, OSV and OE across public

sectors. (g) There is no significant difference between employees’ perception of

OC in terms of type of organization in HRV, OSV and OE across public sectors.

(h) There is no significant difference between employees’ perception of OC in

terms of work processes in HRV, OSV and OE across public sectors.

A quantitative cross-sectional mixed research method was use to test the

eight hypotheses, and the unit of analysis were the individual, organization and

work groups. Standardized and validated questionnaires by Patterson et al

(2005) and Speier & Venkatesh (2002) were used to collect the data required for

analysis. The questions were adapted from previous studies and are based on

Likert scales.

The research data was tested using the SPSS Version 16 statistical test

utilities namely; multiple linear regression, Pearson’s moment-product

correlation, Independent samples t-test, and One-way independent samples

ANOVA test.

The hypotheses testing reveals the following results: (a) the independent

aggregate variables (HRV and OSV) positively & significantly predicted the

dependent variable (OE) and 32.5% of the variation in OE is explained by HRV

& OSV combined; (b) the dimensions Integration, Involvement, Supervisory

Support, Training and Welfare have shown significant positive correlation with

their respective HRV domain of OC; in addition, it also revealed that in relative

terms Supervisory support found to be the dominant and Integration becomes


105

the least influencing factors under HRV domain of OC; (c) the dimensions

Innovation & Flexibility, Outward Focus, and Reflexivity have shown

significant positive correlation with their respective OSV domain of OC, in

addition, it also revealed that in relative terms Innovation & Flexibility found to

be the dominant and Outward focus becomes the least influencing factor under

OSV domain of OC; (d) there is no significant difference exhibited in employees

gender in terms of employees’ perception of OC and OE; (e) there is no

significant difference exhibited in employees tenure in terms of employees

perception of OC and OE; (f) there is no significant difference exhibited in

employees education level in terms of employees’ perception of OC and OE; (g)

there is significant difference in employees’ perception in the type of

organizations in terms of OE and OSV of the OC. However, no significance

difference observed in HRV of employees’ perception across public

organizations; (f) there is no significant difference exhibited in work groups in

terms of employees’ perception of OC and OE.

5.4. IMPLICATIONS AND RECOMMENDATIONS

5.4.1. Implications for research

Future researchers may consider investigating whether OE and other OC

variables have a significant bottom-line impact on firm performance.

Investigating these bottom-line influences will help organizations decide

whether to allocate scarce resources toward developing positive OC. Moreover,

research may find that certain types of individual’s behaviours are more

susceptible to these OC variables and thus will be more motivated than other

types of employees. The implication of this would be a fundamental


106

improvement in efficiency and performance of organizations and reduced

turnover of employees.

Since this study focused only on direct path relationships, future research

should focus on assessing more mediating and moderating relationships.

Mediating and moderating relationships between the OC variables and

psychological and behavioural outcomes could help shed light on exactly how

these relationships vary. The implication of this would be a multidimensional

view of organizations and their interaction with the internal and external

environment.

Examining the association between OC and OE where if the latter is

measured in a multi-dimensional manner is also worthwhile. This is because an

aggregate unidimensional measure like OC may not help adequately capture the

contribution that employee perception may make to different dimensions of OC.

5.4.2. Recommendations for future research

This study focused on one of the three axes or value dimensions of OE

criteria’s i.e. on organizational focus, from an internal, micro emphasis on the

well-being and development of people in the organization to an external, macro

emphasis on the well-being and development of the organization itself (Quinn &

Rohrbaugh 1983). The other two, which are related to organizational structure

from an emphasis on stability to an emphasis on flexibility, and related to

organizational means and ends, and from an emphasis on important processes

to an emphasis on final outcomes (Ibid), should be addressed in future studies

based on the other two values; rational goal values & internal process values.

Because, it enables managers’ in organizations to assess employees’ experience

over many fundamental dimensions of OC (Patterson et al 2005).


107

Although the sample size had a satisfactory number of respondents to

compute all the statistical analyses, it was a randomly sampled from stratified

sample based on single-moment performance evaluation on change

implementation program. This implies an organization maintain its

achievement on change successes consistently for long period, which is unlikely

in real situation especially in the country’s creeping organizational change

initiatives. Therefore, future research should be conducted keeping these

variables constant, or doing studies comparing multiple industries or several

organizations with different sampling methodology.

Within each organization, this study also used just one data point to

gather information regarding the employees’ perception. For that reason, future

research should use multiple data points within one organization (for instance;

observe specific leadership behaviour, conduct in depth‐interviews with leaders

and survey the leaders’ subordinates). These multiple data points would results

in proven generelizability. Furthermore, the examination of employee’s

perceptions about their climate and its impact on OE requires relatively longer

period. A longitudinal design would capture the dynamic nature of the

perception process and its outcomes in a more comprehensive manner (Imran

et al. 2010).


108

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116

APPENDICES APPENDIX- A: List of Public Institution used for Sampling of Respondents

No Organizations No employees Perform

ance Results

Z- scores M F ToT

1 Bureau of Education 116 56 172 80.55% 2.27

2 Bureau of Justice 56 44 100 74.20% 1.48

3 Urban planning Institute 52 16 68 72.90% 1.32

4 Bureau of Industry & Urban works development 98 63 161 72.30% 1.25

5 Bureau of Technical & Vocational Training 46 19 65 71.85% 1.19

6 Office of Prison Administration 245 198 443 71.60% 1.16

7 Cooperatives Promotion Agency 28 10 38 71.45% 1.14

8 Police Commission 16 28 44 71.25% 1.12

9 Bureau of Administration & Security Affairs 27 20 47 71.00% 1.09

10 Bureau of Health 67 36 103 68.75% 0.81

11 Sport Commission 51 35 86 67.95% 0.71

12 Bureau of Finance & Economic Development 94 41 135 65.95% 0.46

13 Bureau of Env/ Protection & Land Adm. 67 36 103 65.60% 0.42

14 Management Institute 41 25 66 64.15% 0.24

15 Office of Communication 32 21 53 62.95% 0.09

16 ANRS Council Office 58 47 105 62.55% 0.04

17 Office of HIV Secretariat 32 15 47 61.95% -0.03

18 Supreme Court 45 44 89 61.15% -0.13

19 Revenue Authority 45 22 67 60.90% -0.16

20 Micro & Small Industries promotion Agency 48 35 83 60.50% -0.21

21 Bureau of Civil service 58 33 91 60.25% -0.24

22 Agricultural Research Institute 50 40 90 59.01% -0.40

23 Bureau of Agriculture 146 54 200 58.45% -0.47

24 Office of General Auditor 135 38 173 58.45% -0.47

25 Mining and Rural Energy Dev’t & Prom’n Agency 32 5 37 58.20% -0.50

26 Bureau of Water Development 138 44 182 58.15% -0.50

27 Bureau of Culture Tourism & Parks Development 74 19 93 57.15% -0.63

28 Bureau of Labour & Social Affairs 22 9 31 56.80% -0.67

29 Bureau of Trade & Transport 79 53 132 55.50% -0.83

30 Office of Militia 4 4 8 53.75% -1.05

31 Secretariat of the Council of the ANRS 35 20 55 53.05% -1.13

32 Bureau of Women, Youth & Children Affairs 42 35 77 52.80% -1.16

33 Office of Food Security & Disaster Prevention 73 24 97 50.70% -1.42

34 Parks Development & Protection Authority 17 2 19 50.15% -1.49

35 Ethics and Anti-corruption Commission 47 15 62 50.00% -1.51

36 Mass media Agency 154 80 234 47.78% -1.79

Source: Amhara National Regional State Amare (2010)


117

Table of Z values

Confidence Level Z Factor 99.9 3.2905 99.7 3.0000 99.5 2.8070 99.0 2.5758 98.0 2.3263 95.5 2.0000 95.0 1.9600 90.0 1.6449 85.0 1.4395 80.0 1.2816

APPENDIX- B: Determination of Respondents Sample

A formula for Sampling (Renckly 2002: 25);

𝑛 = 𝑁Z2 ∗0.25

[𝑑2∗ (𝑁−1)]+ ⌊𝑍2∗0.25⌋ , OR

𝑛 = 384∗N

384+N, (for d = 0.05 & z = 1.96)

Where: n = sample size required

N = total population size (known or estimated)

d = precision level (usually .05 or .10)

Z = number of standard deviation units of the sampling distribution

corresponding to the desired confidence level

Hence, for our sample, N = 552 n = 3,656 ∗ 1.962 ∗0.25

[0.052∗ 3,656]+ ⌊1.962∗0.25⌋

n = 3,511.22/10.10

n = 348

If the total population (N) is 3,656, and we wish a 95% confidence level and ± 5

percent precision level (d = .05, Z = 1.96 from the table) and the number of

distributed questionnaire without adjusting for response rate will be 348.


118

APPENDIX- C: Questionnaire of the Study

Questionnaire

Dear respondent,

My name is Mesfin Raji, I am carrying out a research entitled “Employees’ perception of organizational climate and its implications for organizational effectiveness in Amhara regional PSOs”. This forms part of the requirements for the award of Executive Master of Business Administration Degree at Bahirdar University. The aim of the study is to find ways of improvement of the work environment incorporating employees’ needs. Your participation and views regarding the topic is fundamentally important for the success of the study. I would be grateful for your cooperation in filling the accompanying questionnaire completely. I assure you all replies to this questionnaire are confidential and will be used for statistical purposes only, as part of academic research. Please attempt all questions based on the instructions given below promptly. I appreciate in devoting your valuable time in filling the questions.

I really appreciate your Participation in the Study!!

Instructions

1. You don’t have to state your name or any other personal identification other

than the one you asked to provide in this questionnaire.

2. Read the questions in the left hand of the table and rate parallel to them

according to your feeling using the space provided on the right hand side of the

table.

3. For Part I, give your answer by ticking “√” or “X” sign where it best describes

you.

4. For Part II, rate each question from least 1 - “Strongly Disagree” to the most 5

- “Strongly Agree” using the signs shown in the above instruction number 3.

5. Question 42 will be answered based on your response for Question 41, please

don’t answer Question 42 if your answer for question for 41 is “Yes”,


119

Part I – Information on demography

1)Gender Male 1

4) Educational level attained Female 2 2)Work Process you are working in

Core Process 1 Support Process 2

3)Tenure within the current organization

Below 5 Years 1 10th ፣12th and below 1 From 5-10 Years 2 Certificate 2 From 11-15 Years 3 Diploma 3 From 16-20 Years 4 Bachelor Degree 4 Above 20 years 5 Second Degree & above 5

Part II – Information on the Subject matter

No

Rating scale: Strongly disagree (1), Disagree (2), Undecided (3), Agree (4), and Strongly agree (5)

Questions (1) (2) (3) (4) (5) 1 People are suspicious of other departments* 2 There is very little conflict between departments here 3 People in different departments are prepared to share

information

4 Collaboration between departments is very effective 5 There is very little respect between some of the

departments here*

6 Management involve people when decisions are made that affect them

7 Changes are made without talking to the people involved in them*

8 People don’t have any say in decisions which affect their work*

9 People feel decisions are frequently made over their heads*

10 Information is widely shared 11 There are often breakdowns in communication here* 12 Supervisors here are really good at understanding

peoples’ problems

13 Supervisors show that they have confidence in those they manage

14 Supervisors here are friendly and easy to approach 15 Supervisors can be relied upon to give good guidance

to people

16 Supervisors show an understanding of the people who work for them

17 People are not properly trained when there is a new machine or bit of equipment*

18 People receive enough training when it comes to using new equipment

19 The company only gives people the minimum amount of training they need to do their job*


120

No Questions Rating scale (1) (2) (3) (4) (5)

20 People are strongly encouraged to develop their skills 21 This company pays little attention to the interests of

employees*

22 This company tries to look after its employees 23 This company cares about its employees 24 This company tries to be fair in its actions towards

employees

25 New ideas are readily accepted here 26 This company is quick to respond when changes need

to be made

27 Management here are quick to spot the need to do things differently

28 This organization is very flexible; it can quickly change procedures to meet new conditions and solve problems as they arise

29 Assistance in developing new ideas is readily available 30 People in this organization are always searching for

new ways of looking at problems

31 This organization is quite inward looking; it does not concern itself with what is happening in the market place*

32 Ways of improving service to the customer are not given much thought*

33 Customer needs are not considered top priority here* 34 This company is slow to respond to the needs of the

customer*

35 The methods used by this organization to get the job done are often discussed

36 There are regular discussions as to whether people in the organization are working effectively together

37 In this organization, time is taken to review organizational objectives

38 I am proud to tell others that I am part of this organization.



41 Generally, do you believe that your organization is effective in doing its job? Yes ____ No____

42 If your answer is "No" please rank from 1 to 8 the following possible interventions strategy in their order of priority within the scope of the research

1) Integration 3) Supervisory Support

5) Welfare 7) Outward Focus

2) Involvement 4) Training

6) Innovation & Flexibility

8) Reflexivity

Remark: Items marked with an asterisk (*) are reversed. - Items from 1-37 refers OC measures - Items from 38 – 40 refers Organizational Commitment measures


121

APPENDIX- D: SPSS Chart Outputs of all Variables

Integration


122

Involvement


123

Supervisory Support


124

Emphasis on Training


125

Welfare


126



127

Outward Focus


128

Reflexivity


129

Organizational Commitment


130

Human Relations Values


131

Open Systems Values


132

APPENDIX- E: Factor Analysis for Multifactor & Single factor structures

Results for HRV

Total Variance Explained

Component

Initial Eigenvalues Rotation Sums of Squared Loadings

Total % of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 7.320 38.529 38.529 5.104 26.865 26.865 2 1.537 8.091 46.620 2.581 13.582 40.447 3 1.334 7.020 53.639 1.763 9.281 49.728 4 1.174 6.182 59.821 1.524 8.021 57.749 5 1.025 5.397 65.218 1.419 7.468 65.218 6 .842 4.430 69.648

7 .692 3.640 73.287 Collapsed for saving space

18 .236 1.243 98.980

19 .194 1.020 100.000 Extraction Method: Principal Component Analysis.

Results for OSV


Componen

t

Initial Eigenvalues Rotation Sums of Squared Loadings

Total % of

Variance

Cumulative

% Total

% of

Variance Cumulative %

1 3.741 46.765 46.765 3.207 40.088 40.088 2 1.516 18.952 65.717 2.050 25.629 65.717 3 .766 9.579 75.296

4 .577 7.217 82.513 Collapsed for saving space

7 .315 3.939 96.545


Results for OE


Component

Initial Eigenvalues Extraction Sums of Squared Loadings

Total % of

Variance

Cumulative

% Total

% of


1 2.375 79.181 79.181 2.375 79.181 79.181 2 .383 12.778 91.959



133

Results for Integration


Component


Total % of

Variance

Cumulative

% Total

% of


1 1.503 75.140 75.140 1.503 75.140 75.140 2 .497 24.860 100.000

Extraction Method: Principal Component Analysis. Results for Involvement


Component


Total % of

Variance

Cumulative

% Total

% of


1 1.696 56.517 56.517 1.696 56.517 56.517 2 .708 23.608 80.125


Results for Supervisory Support


Component


Total % of

Variance

Cumulative

% Total

% of


1 3.485 69.697 69.697 3.485 69.697 69.697 2 .488 9.769 79.466

3 .426 8.511 87.978

4 .354 7.076 95.053


Results for Emphasis on Training


Component


Total % of

Variance

Cumulative

% Total

% of


1 1.863 62.106 62.106 1.863 62.106 62.106 2 .711 23.685 85.792



134

Results for Welfare


Component


Total % of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 2.331 77.705 77.705 2.331 77.705 77.705 2 .434 14.469 92.174


Results for Innovation & Flexibility


Component


Total % of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 3.704 61.732 61.732 3.704 61.732 61.732 2 .750 12.505 74.237

3 .523 8.718 82.955

4 .409 6.820 89.775

5 .324 5.405 95.180


Results for Outward Focus


Component


Total % of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 2.005 66.835 66.835 2.005 66.835 66.835 2 .614 20.478 87.313


Results for Reflexivity


Component


Total % of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 1.962 65.389 65.389 1.962 65.389 65.389 2 .544 18.139 83.528

3 .494 16.472 100.000 Extraction Method: Principal Component Analysis. Source: Researcher’s own computation


135

APPENDIX- F: Item Loading for the Single Factor for HRV & OSV

Rotated Component Matrixa HRV(HRV) OSV(OSV)

Component Component 1 2 3 4 5 1 2

Qn15 .826 Qn27 .816

Qn14 .813 Qn29 .815

Qn16 .784 Qn28 .784

Qn12 .782 Qn26 .769

Qn13 .743 Qn25 .764

Qn24 .697 revQn33 .861 Qn23 .671 revQn32 .801 Qn22 .600 .511 revQn34 .741 revQn21 .705

Qn18 .601

Qn20 .584

Qn6 .551

Qn3 .781

Qn4 .713

revQn5 .573

revQn11 .795

revQn17 .565 revQn7 .538 revQn19 .816 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 7 iterations. a. Rotation converged in 3

iterations. Kaiser-Meyer-Olkin Measure of Sampling Adequacy

.914 .804 Source: Researcher’s own computation


136

APPENDIX- G: Item Loading for the Single Factor for Sub-scales of HRV & OSV

Component Matrixa Items Component Component Component

1 1 1 Integration Welfare Organizational

effectiveness Qn3 .867 Qn22 .910 Qn38 .909 Qn4 .867 Qn23 .898 Qn39 .902 Qn24 .835 Qn40 .858

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .500 .709 .725

Involvement Innovation & Flexibility

Qn6 .789 Qn25 .744 revQn9 .733 Qn26 .770 Qn10 .732 Qn27 .819 Qn28 .808 Qn29 .828 Qn30 .741

Kaiser-Meyer-Olkin Measure of Sampling Adequacy

.635 .856 Supervisory Support Outward Focus

Qn12 .814 revQn33 .874 Qn13 .798 revQn34 .790 Qn14 .814 revQn32 .785 Qn15 .887 Qn16 .859


.874 .652 Emphasis on Training Reflexivity

revQn17 .699 Qn35 .797 Qn18 .803 Qn36 .821 Qn20 .855 Qn37 .807


.623 .685



137

APPENDIX- H: Reliability Statistics for all Variables

Reliability Statistics for HRV Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance if

Item Deleted

Corrected Item-Total Correlation

Squared Multiple

Correlation

Cronbach's Alpha if

Item Deleted

Qn3 54.53 172.520 .423 .354 .898 Qn4 54.93 168.077 .524 .417 .895 revQn5 54.91 174.756 .327 .242 .901 Qn6 55.20 165.180 .589 .412 .893 revQn7 54.97 172.420 .397 .284 .899 revQn11 55.27 175.981 .268 .174 .903 Qn12 55.04 162.647 .673 .568 .891 Qn13 55.00 165.112 .646 .553 .892 Qn14 54.88 164.430 .615 .574 .893 Qn15 55.03 161.976 .715 .686 .890 Qn16 54.94 161.749 .739 .664 .889 revQn17 55.11 169.363 .459 .346 .897 Qn18 55.33 170.043 .466 .364 .897 revQn19 55.02 181.475 .099 .147 .907 Qn20 55.24 161.773 .693 .582 .890 revQn21 55.18 170.656 .445 .329 .898 Qn22 55.26 161.792 .732 .684 .889 Qn23 55.53 162.435 .715 .682 .890 Qn24 54.99 164.876 .665 .556 .891 Cronbach's Alpha for N of items 19 = .900 Cronbach's Alpha can be improved to .907 but it is not a substantial change if the item is deleted



138

Reliability Statistics for OSV

Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance if

Item Deleted

Corrected Item-Total

Correlation

Squared Multiple

Correlation

Cronbach's Alpha if Item

Deleted Qn25 23.02 24.347 .591 .497 .811 Qn26 23.20 23.425 .626 .539 .806 Qn27 23.10 23.005 .663 .557 .801 Qn28 23.00 23.958 .665 .545 .802 Qn29 23.27 24.010 .629 .530 .806 revQn32 22.40 27.300 .368 .359 .837 revQn33 22.40 26.002 .465 .464 .827 revQn34 22.49 25.942 .478 .364 .826 Cronbach's Alpha for N of items 8 = .835 Cronbach's Alpha can be improved to .837 but it is not a substantial change if the item is deleted

Reliability Statistics for Sub-scales of HRV & OSV Reliability Statistics for Integration

Item-Total Statistics Scale Mean

if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total Correlatio

n

Squared Multiple

Correlation

Cronbach's Alpha if Item

Deleted

Qn3 3.20 1.448 .503 .253 .a Qn4 3.60 1.199 .503 .253 .a Cronbach's Alpha for N of items 2 = .667 Cronbach's Alpha cannot be improved since the value will become negative due to a negative average covariance among items.



139

Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance if

Item Deleted


Squared Multiple

Correlation

Cronbach's Alpha if

Item Deleted

Reliability Statistics for Involvement Qn6 6.28 3.645 .466 .217 .451 revQn9 6.20 4.006 .404 .167 .543 Qn10 5.94 4.251 .402 .167 .545 Cronbach's Alpha for N of items 3 = .615 Cronbach's Alpha cannot be improved as no better value will be obtained if any item is deleted Reliability Statistics for Supervisory Support Qn12 12.67 17.132 .707 .501 .873 Qn13 12.63 17.955 .685 .491 .877 Qn14 12.52 17.154 .706 .514 .873 Qn15 12.67 16.540 .805 .664 .850 Qn16 12.57 17.033 .765 .608 .860 Cronbach's Alpha for N of items 5 = .891 Cronbach's Alpha cannot be improved as no better value will be obtained if any item is deleted Reliability Statistics for Emphasis on training revQn17 8.81 5.845 .396 .185 .382 Qn18 9.03 5.984 .416 .324 .368 revQn19 8.72 8.535 -.008 .012 .691 Qn20 8.94 5.174 .518 .376 .254 Cronbach's Alpha for N of items 4 = .528 Cronbach's Alpha for N of items 3 if item(revQn19) discarded = .691 Reliability Statistics for Welfare Qn22 5.74 4.447 .780 .629 .749 Qn23 6.01 4.560 .758 .607 .772 Qn24 5.47 5.161 .654 .430 .866 Cronbach's Alpha for N of items 3 = .856 Cronbach's Alpha can be improved to .866 but it is not a substantial change if the item is deleted



140

Item-Total Statistics Scale Mean

if Item Deleted

Scale Variance if Item Deleted


Squared Multiple

Correlation

Cronbach's Alpha if

Item Deleted

Reliability Statistics for Innovation & Flexibility Qn25 14.89 18.707 .636 .495 .861 Qn26 15.07 17.946 .663 .515 .857 Qn27 14.97 17.447 .717 .550 .847 Qn28 14.87 18.436 .705 .544 .850 Qn29 15.13 17.986 .731 .570 .845 Qn30 15.04 18.790 .624 .418 .863 Cronbach's Alpha for N of items 6 = .875 Cronbach's Alpha cannot be improved as no better value will be obtained if any item is deleted Reliability Statistics for Outward Focus revQn32 7.36 2.942 .532 .316 .719 revQn33 7.36 2.417 .670 .449 .556 revQn34 7.45 2.735 .541 .323 .712 Cronbach's Alpha for N of items 3 = .751 Cronbach's Alpha cannot be improved as no better value will be obtained if any item is deleted Reliability Statistics for Reflexivity Qn35 6.63 3.299 .543 .296 .667 Qn36 6.91 3.049 .576 .332 .628 Qn37 6.83 3.253 .557 .312 .651 Cronbach's Alpha for N of items 3 = .735 Cronbach's Alpha cannot be improved as no better value will be obtained if any item is deleted Reliability Statistics for OE Qn38 7.03 4.513 .782 .625 .783 Qn39 7.11 4.737 .771 .611 .794 Qn40 6.80 5.074 .695 .484 .862 Cronbach's Alpha for N of items 3 = .868 Cronbach's Alpha cannot be improved as no better value will be obtained if any item is deleted



141

APPENDIX- I: SPSS Outputs of Regression Charts


142

APPENDIX- J: Homogeneity test of Variance for Grouping Variable

Variances

Grouping Variable Variables Levene

Statistic df1 df2 Sig.

Education level

Organizational Commitment 1.305 4 247 .269

Human Relations Values .983 4 247 .418 Open Systems Values 2.597 4 247 .037



Tenure

Organizational Commitment .292 4 245 .883

Human Relations Values .577 4 245 .680 Open Systems Values .204 4 245 .936



Organization Type

Organizational Commitment .621 5 254 .684

Human Relations Values 1.607 5 254 .159 Open Systems Values 2.118 5 254 .064

Correlations for regressed variables

Variables Organizational Commitment

Human Relations

Values

Open Systems Values

Pearson Correlation

Organizational Commitment 1.000

Human Relations Values .523*** 1.000 Open Systems Values .540*** .744*** 1.000

***Correlation significant, p < .001 Sig. (1-tailed)



143

APPENDIX- K: Suggestion of Intervention Strategies by Respondents

Do you believe that your organization is effective in doing its job? Frequency Percent Valid

Percent Cumulative

Percent Valid Yes 158 60.8 65.8 65.8

No 82 31.5 34.2 100.0 Total 240 92.3 100.0

Missing 0 20 7.7

Total 260 100.0 For the response “No”, prioritized intervention strategy suggested by

respondents

Variables Valid No Suggestion

Missing Total Ranking (Mode)

Integration 70 12 178 260 (4a)3a Involvement 70 12 178 260 3

Supervisory Support 70 12 178 260 4 Training 70 12 178 260 1 Welfare 70 12 178 260 2 Innovation & Flexibility

70 12 178 260 (8a)1a

Outward Focus 70 12 178 260 7

Reflexivity 70 12 178 260 6 Total 240 12 8 260 a. Multiple modes exist. All values are shown


Documents

Employees’ perception of organizational climate and its implications for organizational effectiveness in Amhara regional public service organs