Institutional effects on the intention to adopt e-learning for business studies

The present study investigates the factors that influence the adoption of e-learning among adult postgraduate university students in Hong Kong. In particular, the study addresses the question of whether institutional factors affect students' decision to adopt e-learning in their studies. A composite model of four constructs (perceived usefulness, perceived ease of use, perceived convenience and institutional effects) is proposed and tested in this quantitative survey of 125 part-time MBA students. The study finds that institutional effects and perceived convenience were the most important factors in a decision to adopt e-learning. The factors perceived usefulness and perceived ease of use did not have a significant relationship with the intention to adopt e-learning. The paper illustrates the theoretical and practical issues of social effects in the adoption of e-learning.

[1]  Roger J. Calantone,et al.  International Technology Adoption , 1994 .

[2]  T. H. Kwon,et al.  Unifying the fragmented models of information systems implementation , 1987 .

[3]  Cheng-Chang Sam Pan,et al.  Students' Attitude in a Web-enhanced Hybrid Course: A Structural Equaadon Modeling Inquiry , 2003 .

[4]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[5]  Peter A. Todd,et al.  Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication , 1992, MIS Q..

[6]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[7]  R. Buehler,et al.  Change-of-meaning effects in conformity and dissent: Observing construal processes over time. , 1994 .

[8]  Jane McKenzie,et al.  Facilitating virtual learning groups: A practical approach , 2001 .

[9]  Ali R. Montazemi,et al.  Factors Affecting Information Satisfaction in the Context of the Small Business Environment , 1988, MIS Q..

[10]  Bernadette Szajna,et al.  Software Evaluation and Choice: Predictive Validation of the Technology Acceptance Instrument , 1994, MIS Q..

[11]  G. Conole E-Learning: The Hype and the Reality , 2004 .

[12]  R. Rice,et al.  Electronic Emotion , 1987 .

[13]  Su-Chao Chang,et al.  An empirical investigation of students' behavioural intentions to use the online learning course websites , 2007, Br. J. Educ. Technol..

[14]  Eric K. W. Lau The use of an online discussion forum for case sharing in business education , 2007, Int. J. Learn. Technol..

[15]  E. Rogers Diffusion of Innovations , 1962 .

[16]  L. Festinger A Theory of Social Comparison Processes , 1954 .

[17]  Albert H. Segars,et al.  Re-examining perceived ease of use and usefulness , 1993 .

[18]  Fred D. Davis,et al.  A Model of the Antecedents of Perceived Ease of Use: Development and Test† , 1996 .

[19]  I. Ajzen,et al.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[20]  Paul Henry,et al.  E‐learning technology, content and services , 2001 .

[21]  Jean Hannon,et al.  Cultural diversity online: student engagement with learning technologies , 2007 .

[22]  Rose Mary Wentling,et al.  The Relationship between National Culture and the Usability of an E-learning System , 2004 .

[23]  L. Cronbach Coefficient alpha and the internal structure of tests , 1951 .

[24]  R. Greenwood,et al.  Understanding Radical Organizational Change: Bringing Together the Old and the New Institutionalism , 1996 .

[25]  Cynthia K. Riemenschneider,et al.  Executive Decisions About Adoption of Information Technology in Small Business: Theory and Empirical Tests , 1997, Inf. Syst. Res..

[26]  Shelley E. Taylor,et al.  Social psychology, 8th ed. , 1994 .

[27]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[28]  Charles D. Barrett Understanding Attitudes and Predicting Social Behavior , 1980 .

[29]  Fred D. Davis User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts , 1993, Int. J. Man Mach. Stud..

[30]  Kenneth L. Kraemer,et al.  Institutional Factors in Information Technology Innovation , 1994, Inf. Syst. Res..

[31]  Nelson Oly Ndubisi,et al.  Factors of Online Learning Adoption: A Comparative Juxtaposition of the Theory of Planned Behaviour and the Technology Acceptance Model. , 2006 .

[32]  A. Bandura Social learning theory , 1977 .

[33]  Shirley Taylor,et al.  Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions , 1995 .

[34]  C. Steinfield,et al.  A Social Information Processing Model of Media Use in Organizations , 1987 .

[35]  Patrick Y. K. Chau,et al.  An Empirical Assessment of a Modified Technology Acceptance Model , 1996, J. Manag. Inf. Syst..

[36]  John W. Meyer,et al.  Institutionalized Organizations: Formal Structure as Myth and Ceremony , 1977, American Journal of Sociology.

[37]  Douglas R. Wholey,et al.  Institutional Determinants Of Individual Mobility: Bringing The Professions Back In , 1996 .

[38]  E. Rogers,et al.  Communication of innovations: A cross-cultural approach, 2nd ed. , 1971 .

[39]  Richard G. Netemeyer,et al.  Measurement of Consumer Susceptibility to Interpersonal Influence , 1989 .