Understanding Continuance of Advanced Internet-based Learning Technologies: The Role of Satisfaction, Prior Behavior, and Habit

Despite the growing interest in Internet-based learning technologies (IBLT) and the application of advanced Internet technologies in education, research investigating continued usage of these tools has been very scarce. The objective of this study is to gain a better understanding of factors influencing students’ continued usage of these learning technologies. Building upon prior literature, satisfaction and prior behavior are posited to have a direct impact on IBLT continued usage. In addition, we take into consideration the “habit” construct in order to better explain the automatic nature of IBLT continuance. The research model is tested in a longitudinal setting. Results present strong support for the existing theoretical links of IBLT continuance model, as well as for those newly hypothesized in this study. The implications are noteworthy for both researchers and practitioners.

[1]  C. Steinfield Dimensions of Electronic Mail Use in an Organizational Setting. , 1985 .

[2]  Diane M. Strong,et al.  Extending the technology acceptance model with task-technology fit constructs , 1999, Inf. Manag..

[3]  RaiArun,et al.  Assessing the Validity of IS Success Models , 2002 .

[4]  Wendy Wood,et al.  Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. , 1998 .

[5]  Detmar W. Straub,et al.  Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs , 1999, MIS Q..

[6]  Katherine N. Lemon,et al.  A Dynamic Model of Customers’ Usage of Services: Usage as an Antecedent and Consequence of Satisfaction , 1999 .

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

[8]  Fred D. Davis,et al.  Toward preprototype user acceptance testing of new information systems: implications for software project management , 2004, IEEE Transactions on Engineering Management.

[9]  Richard P. Bagozzi,et al.  A comparison of leading theories for the prediction of goal‐directed behaviours , 1995 .

[10]  Wynne W. Chin,et al.  Adoption intention in GSS: relative importance of beliefs , 1995, DATB.

[11]  R. Rust,et al.  Indirect Financial Benefits from Service Quality , 1996 .

[12]  Moez Limayem,et al.  Explaining Information Systems Adoption and Post-Adoption: Toward an Integrative Model , 2003, ICIS.

[13]  Matthew K. O. Lee,et al.  Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation , 2005, Inf. Manag..

[14]  Dennis L. Dossett,et al.  Attitude–behavior relations: A comparison of the Fishbein-Ajzen and the Bentler-Speckart models. , 1983 .

[15]  Detmar W. Straub,et al.  Measuring System Usage: Implications for IS Theory Testing , 1995 .

[16]  R. Oliver,et al.  A framework for the formation and structure of consumer expectations: Review and propositions , 1987 .

[17]  Paul Norman,et al.  The theory of planned behaviour and exercise: an investigation into the role of prior behaviour, behavioural intentions and attitude variability , 1995 .

[18]  R. Bagozzi,et al.  Trying to Consume , 1990 .

[19]  M. Conner,et al.  Extending the Theory of Planned Behavior: A Review and Avenues for Further Research , 1998 .

[20]  B. Verplanken,et al.  Predicting behavior from actions in the past : repeated decision making or a matter of habit? , 1998 .

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

[22]  Moez Limayem,et al.  Force of Habit and Information Systems Usage: Theory and Initial Validation , 2003, J. Assoc. Inf. Syst..

[23]  Ephraim R. McLean,et al.  The DeLone and McLean Model of Information Systems Success: A Ten-Year Update , 2003, J. Manag. Inf. Syst..

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

[25]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Dependent Variable , 1992, Inf. Syst. Res..

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

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

[28]  Deborah Compeau,et al.  Application of Social Cognitive Theory to Training for Computer Skills , 1995, Inf. Syst. Res..

[29]  Wynne W. Chin The partial least squares approach for structural equation modeling. , 1998 .

[30]  Xianggui Qu,et al.  Multivariate Data Analysis , 2007, Technometrics.

[31]  A. Parasuraman,et al.  Marketing to and serving customers through the internet: An overview and research agenda , 2002 .

[32]  Arun Rai,et al.  Assessing the Validity of IS Success Models: An Empirical Test and Theoretical Analysis , 2002, Inf. Syst. Res..