e-Learning continuance intention: Moderating effects of user e-learning experience

This study explores the determinants of the e-learning continuance intention of users with different levels of e-learning experience and examines the moderating effects of e-learning experience on the relationships among the determinants. The research hypotheses are empirically validated using the responses received from a survey of 256 users. The results reveal that negative critical incidents and attitude are the main determinants of the users' intention to continue using the e-learning, irrespective of their level of e-learning experience. In addition, the findings show that the user's experience of the e-learning service plays a moderating role. The impact of negative critical incidents on perceived ease of use is greater for less experienced users. By contrast, the impact of negative critical incidents on perceived usefulness is greater for more experienced users. Perceived ease of use has a more critical effect on the attitude and continuance intention of less experienced users, whereas perceived usefulness is found to be a stronger determinant of the attitude and behavioral intention of more experienced users. Moreover, the relationship between satisfaction and continuance intention is stronger for less experienced users than for more experienced users. The implications of the present findings for research and managerial practice are analyzed and discussed.

[1]  Cees de Bont,et al.  The effects of product expertise on consumer evaluations of new-product concepts , 1995 .

[2]  Hung-Pin Shih,et al.  An empirical study on predicting user acceptance of e-shopping on the Web , 2004, Inf. Manag..

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

[4]  Shelly Chaiken,et al.  The heuristic-systematic model in its broader context. , 1999 .

[5]  Chang Liu,et al.  Learning style, learning patterns, and learning performance in a WebCT-based MIS course , 2003, Inf. Manag..

[6]  Janette R. Hill,et al.  Improving online learning: Student perceptions of useful and challenging characteristics , 2004, Internet High. Educ..

[7]  Linda Ellis Johnson,et al.  An innovative pedagogy for teaching and evaluating computer literacy , 2000, Inf. Technol. Manag..

[8]  J. Petrick,et al.  The Utilization of Critical Incident Technique to Examine Cruise Passengers’ Repurchase Intentions , 2006 .

[9]  Brian D. Till,et al.  The Match-Up Hypothesis: Physical Attractiveness, Expertise, and the Role of Fit on Brand Attitude, Purchase Intent and Brand Beliefs , 2000 .

[10]  Anol Bhattacherjee,et al.  Understanding Changes in Belief and Attitude Toward Information Technology Usage: A Theoretical Model and Longitudinal Test , 2004, MIS Q..

[11]  S. Alexander E‐learning developments and experiences , 2001 .

[12]  Reza Barkhi,et al.  The impact of personality type on purchasing decisions in virtual stores , 2007, Inf. Technol. Manag..

[13]  Wanda J. Orlikowski,et al.  Research Commentary: Desperately Seeking the "IT" in IT Research - A Call to Theorizing the IT Artifact , 2001, Inf. Syst. Res..

[14]  K. Kaplan On the ambivalence-indifference problem in attitude theory and measurement: A suggested modification of the semantic differential technique. , 1972 .

[15]  Anol Bhattacherjee,et al.  Influence Processes for Information Technology Acceptance: An Elaboration Likelihood Model , 2006, MIS Q..

[16]  P. Deans,et al.  E-Commerce and M-Commerce Technologies , 2004 .

[17]  John Ingham,et al.  Why do people use information technology? A critical review of the technology acceptance model , 2003, Inf. Manag..

[18]  Anol Bhattacherjee,et al.  Understanding Information Systems Continuance: An Expectation-Confirmation Model , 2001, MIS Q..

[19]  R. Bagozzi,et al.  ON THE EVALUATION OF STRUCTURE EQUATION MODELS , 1998 .

[20]  Viswanath Venkatesh,et al.  Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..

[21]  Margareta Friman,et al.  The structure of affective reactions to critical incidents , 2004 .

[22]  A. A. Mitchell,et al.  The Assessment of Alternative Measures of Consumer Expertise , 1996 .

[23]  Francisco Muñoz-Leiva,et al.  Web Acceptance Model (WAM): Moderating effects of user experience , 2007, Inf. Manag..

[24]  Heiner Evanschitzky,et al.  An Examination of Moderator Effects in the Four-Stage Loyalty Model , 2006 .

[25]  Young-Gul Kim,et al.  Extending the TAM for a World-Wide-Web context , 2000, Inf. Manag..

[26]  Thavamalar Govindasamy,et al.  Successful implementation of e-Learning: Pedagogical considerations , 2001, Internet High. Educ..

[27]  Eric W. K. Tsang Acquiring Knowledge by Foreign Partners from International Joint Ventures in a Transition Economy: Learning-by-Doing and Learning Myopia , 2002 .

[28]  T. Gärling,et al.  FREQUENCY OF NEGATIVE CRITICAL INCIDENTS AND SATISFACTION WITH PUBLIC TRANSPORT SERVICES , 2001 .

[29]  Stephen Carey The Use of WebCT for a Highly Interactive Virtual Graduate Seminar , 1999 .

[30]  Nian-Shing Chen,et al.  Understanding e-learning continuance intention: a negative critical incidents perspective , 2011, Behav. Inf. Technol..

[31]  Kwoting Fang,et al.  Loyalty Differences in the Effect of Negative Critical Incidents and Quality Attributes Satisfaction: An Empirical Study of Online Shopping , 2004 .

[32]  Douglas R. Vogel,et al.  Will virtual education initiatives succeed? , 2000, Inf. Technol. Manag..

[33]  Eric T. G. Wang,et al.  Understanding Web-based learning continuance intention: The role of subjective task value , 2008, Inf. Manag..

[34]  Nian-Shing Chen,et al.  Analysing users’ satisfaction with e‐learning using a negative critical incidents approach , 2008 .

[35]  Szu-Yuan Sun,et al.  Usability, quality, value and e-learning continuance decisions , 2005, Comput. Educ..

[36]  Anol Bhattacherjee,et al.  An empirical analysis of the antecedents of electronic commerce service continuance , 2001, Decis. Support Syst..

[37]  K. M. Lin,et al.  Exploring learning problems of cyber university , 2001, Proceedings IEEE International Conference on Advanced Learning Technologies.

[38]  Chao-Min Chiu,et al.  Predicting electronic service continuance with a decomposed theory of planned behaviour , 2004, Behav. Inf. Technol..

[39]  T. J. Gerpott,et al.  Customer retention, loyalty, and satisfaction in the German mobile cellular telecommunications market , 2001 .

[40]  J. Arbaugh Learning to learn online: A study of perceptual changes between multiple online course experiences , 2004, Internet High. Educ..

[41]  I. Ajzen The theory of planned behavior , 1991 .

[42]  Bo Edvardsson,et al.  Service Break-Downs a Study of Critical Incidents in an Airline , 1992 .

[43]  Leslie Stoel,et al.  Modeling the effect of experience on student acceptance of Web-based courseware , 2003, Internet Res..

[44]  J. Hair Multivariate data analysis , 1972 .

[45]  Peter A. Todd,et al.  Assessing IT usage: the role of prior experience , 1995 .

[46]  David C. Yen,et al.  Theory of planning behavior (TPB) and customer satisfaction in the continued use of e-service: An integrated model , 2007, Comput. Hum. Behav..

[47]  Dwayne D. Gremler The Critical Incident Technique in Service Research , 2004 .

[48]  A. Parasuraman,et al.  A Conceptual Model of Service Quality and Its Implications for Future Research , 1985 .

[49]  Bernard C. Y. Tan,et al.  A Cross-Cultural Study on Escalation of Commitment Behavior in Software Projects , 2000, MIS Q..

[50]  Christian Homburg,et al.  Relationship Characteristics as Moderators of the Satisfaction-Loyalty Link: Findings in a Business-to-Business Context , 2003 .

[51]  Norman R. Ellis,et al.  Memory for frequency of occurrence: Intelligence level and retrieval cues , 1989 .

[52]  Honglei Li,et al.  Technology acceptance model for internet banking: an invariance analysis , 2005, Inf. Manag..

[53]  Yi-Shun Wang,et al.  Measuring e-learning systems success in an organizational context: Scale development and validation , 2007, Comput. Hum. Behav..

[54]  Chao-Min Chiu,et al.  Understanding e-learning continuance intention: An extension of the Technology Acceptance Model , 2006, Int. J. Hum. Comput. Stud..

[55]  T. Keiningham,et al.  A Longitudinal Analysis of Customer Satisfaction and Share of Wallet: Investigating the Moderating Effect of Customer Characteristics , 2007 .

[56]  Szu-Yuan Sun,et al.  An empirical analysis of the antecedents of web-based learning continuance , 2007, Comput. Educ..

[57]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[58]  H. Marsh,et al.  Application of confirmatory factor analysis to the study of self-concept: First- and higher order factor models and their invariance across groups. , 1985 .

[59]  S. Chaiken,et al.  Dual-process theories in social psychology , 1999 .

[60]  Bernadette Szajna,et al.  Empirical evaluation of the revised technology acceptance model , 1996 .

[61]  Terry Anderson,et al.  The Theory and Practice of Online Learning , 2009 .

[62]  R. Bagozzi,et al.  On the evaluation of structural equation models , 1988 .

[63]  Jay F. Nunamaker,et al.  Can e-learning replace classroom learning? , 2004, CACM.

[64]  Chao-Min Chiu,et al.  A longitudinal investigation of continued online shopping behavior: An extension of the theory of planned behavior , 2006, Int. J. Hum. Comput. Stud..