The effect of task-technology fit on purchase intention: The moderating role of perceived risks

Abstract

Electronic commerce to date has experienced rapid growth, and online purchases have become very popular among online consumers. To successfully attract online consumers and benefit from doing so, e-tail product providers should learn about consumers’ purchase intention, its antecedents, and moderators. This study proposes a research model of purchase intention using perceived performance risk and perceived privacy risk as moderators based on a perspective of task-technology fit. In the proposed model, purchase intention is positively influenced by three antecedents: task-technology fit, perceived navigation, and perceived reputation. Each model path is moderated by perceived performance risk and perceived privacy risk, respectively. Empirically testing using a survey of 749 registered members (consumers) from the database of Taiwan’s largest e-learning commercial website confirms that task-technology fit, perceived navigation, and perceived reputation positively influence purchase intention. The relationship between task-technology fit, perceived navigation and purchase intention are significantly moderated by the perceived performance risk and perceived privacy risk. Finally, managerial implications and limitations of our findings are discussed.

Keywords:

• E-commerce
• perceived risk
• purchase intention
• task-technology fit

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Corrigendum

Notes

1. SEM has been used to confirm our model paths (see Appendix 2), and their significance is consistent with that obtained via our hierarchical regression.