Tolerance to Change, Personality and Age Differences in Acceptance of Technological Innovation among Civil Servants.


This survey studied Tolerance to change personality and age differences in the acceptance of technology innovation among civil servants.

Four hundred and thirty (430) non academic civil servants were selected through convenient sampling to participate in the study.

The population size is made up of five (5) higher institutions drawn out of purposive sampling from all the higher institutions in Enugu state. They include University of Nigeria, Enugu campus, Enugu state college of education, Enugu state university of science and technology, Godfrey Okoye University, and Institute of management and technology, Enugu.

The questionnaire used were Technology acceptance Model (TAM), developed by Davies (1989), Resistance to change scale (Oreg, 2000) and Technology Readiness Index (Panasuraman, 2000).

Tolerance to change was studied using the Resistance to change scale (Oreg, 2000), Personality was studied using the Readiness Index (Panasuraman, 2000), while the technology acceptance was studied using the Technology acceptance Model (TAM), Davies (1989). Age differences were studied from the demographics data.

The survey employed a cross sectional design. Multiple regression was used to analyse it. Results of the data analysis showed that Tolerance to change is a negative predictor to acceptance of technology innovation.

Also, age is a negative significant predictor in the acceptance of technology innovation.

This study asserts that Personality is a positive significant predictor of acceptance of technology innovation and recommends establishing practices to motivate various age brackets in the civil service in accepting and adopting information technology alongside the changes it brings.


Title page i
Certification page ii
Dedication iii
Acknowledgements iv
Table of contents v
List of Tables vi
List of Figures vii
List of Appendices viii
Abstract ix

Chapter One

Introduction 1
Statement of the Problem 9
Purpose of the Study 11
Operational Definition of Terms 13

Chapter Two

Literature Review 14
Empirical Review 36
Summary of Literature 42
Hypotheses 45

Chapter Three

Method 47
Participants 47
Instruments 47
Procedure 50
Design /statistics 50

Chapter Four

Results 59
Summary of the findings 66

Chapter Five

Discussion 68
Implications of the study 71
Limitations of the study 72
Suggestions for further studies 73
Summary and conclusion 74
Appendix A


Over the past decades, organizations have been driven by investments in technology innovations especially in information and communication technology. This investment is aimed at increasing individual productivity that will contribute to the overall organizational productivity.

Notwithstanding the enormous investment, there has been recent debate if there is any benefit in academia and business as return on investment at all. Johansen and Swigard (1996), Moore (1991), Norman (1993) and Weiner (1993), decry the extent to which these emerging information technologies have fallen below expectation.

An appreciation of the factors that influence the acceptance of technology innovation becomes indispensable.

This research aims to deepen our understanding on the inherent factors that could probably influence technology acceptance, its adoption and usage decisions among consumers, like the Civil servants.

Technology innovation has an extensive role to play in efficient and speedy delivery of goods and services. This call for constant review and improvement on the status quo.

Improving on these services can otherwise be referred to as innovation. Innovation is a product, process or service, either with unprecedented performance characteristics or familiar characteristics that offer significant improvements in performance or cost which transforms the existing markets or create new ones (Conescu & Adam ,2013).

Another form of innovation which can be regarded as incremental innovation represents the “adapting, refining, simplifying and improving of the products and/or the existing systems of production and distribution” (Assink, 2006). Innovation encourages change which entails moving from the familiar to the unfamiliar.


Agboola, A. A., & Salawu, R. O. (2011). Managing deviant behavior and resistance to change: International journal of business and management, 6 (1). Canadian Center of science &Education.

Ahmad, S. A., Abubakar, Y., & Dabo, J. I. (2013). Information and Communication Technology acceptance for teaching and learning among secondary school Teachers in Nigeria. Asian Journal of management sciences and Education, (2)

Ajzen, I. (1985). From intentions to actions: a theory of planned behavior. In Kuhl, & J. Beckmann (Eds.), Action control from cognition to behavior. New York: Springer-Verlag.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Process, 50 (2), 179-211.

Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. N.J:Prentice-Hall, Eaglewood cliffs.

By admin

Leave a Reply

Your email address will not be published. Required fields are marked *