Predicting the continuance usage of information systems: a comparison of three alternative models

  • Authors:

  • S. C. Wang;Y. S. Lii;K. T. Fang

  • Affiliations:

  • Department of Information Management, National Yunlin University of Science and Technology, Yunlin, Taiwan R.O.C.;Department of International Trade, Feng Chia University, Taichung, Taiwan R.O.C.;Department of Information Management, National Yunlin University of Science and Technology, Yunlin, Taiwan R.O.C.

  • Venue:
  • WSEAS Transactions on Information Science and Applications
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

This study seeks to examine, through empirical evidence, the relative explanatory power of three prospective models in predicting users' continuous adoption of information system (IS). The three models include: Expectation-Confirmation Theory Model (ECTM, Model 1), the integration of ECTM with Technology Acceptance Model (TAM) (ECT-TAM model, Model 2), and a hybrid model integrating ECT, TAM and emotions (Model 3). Three hundred and fifty web portal site users were obtained from a survey. The paper assessed the psychometric properties of the measures through confirmatory factor analysis and then employed structural equation modeling analysis in order to examine and compare the ability of the three prospective models to better predict users' continuous adoption of IS. Data analysis using LISREL shows that all three models meet the various goodness-of-fit criteria. In terms of variance explained for intention to continue IS usage, all three models perform equally well. As for the explanatory power of satisfaction, Model 3 has the highest R2 (71%), followed by Model 2 (69%), and Model 1 (68%). This result confirms the erstwhile discussion of continuance intention behavior in which adding emotion factors to the cognitive process model will enhance the predictive power of the satisfaction. Perceived usefulness and perceived ease of use predict the level of user satisfaction better than emotions and perceived usefulness is the stronger predictor of user satisfaction than other variables. The Model 3 provides additional information to increase our understanding of IS continuance intention behavior.