Impacts of User Expectation and Disconfirmation on Satisfaction and Behavior Intention: The Moderating Effect of Expectation Levels

Abstract

Vast existing user experience (UX) studies have considered expectation and disconfirmation/confirmation in predicting UX satisfaction and behavioral intention. Moreover, both theoretical and empirical findings indicate the asymmetrical effect of positive and negative disconfirmation. However, few studies have compared the effect of different UX aspects or moderators of these effects. To make further exploration, the current article proposes hypotheses based on the expectation-confirmation model and expectation-confirmation theory. The hypotheses are tested in two mobile e-banking app UX studies. A retrospective questionnaire was used to collect data in the first study. The analyzing results confirmed the impact of expectation and the asymmetrical effect of disconfirmation on UX satisfaction and behavioral intention. The second experimental study manipulated user expectation levels by information priming, and expectation level was found to show a moderating effect in predicting user satisfaction and behavioral intention. The conclusions from the current article provide both theoretical and practical implications for UX study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Natural Science Foundation of China (NSFC, grant number: 72021001 and 72171015).

Notes on contributors

Xiaorui Wang

Xiaorui Wang is a lecturer at the School of Economics and Management, Beijing University of Chemical Technology, China. Her research interests include human factors and behavioral decision-making. She is currently focusing on behavioral decision-making issues in user experience and consumption.

Ronggang Zhou

Ronggang Zhou is a professor at the School of Economics and Management, Beihang University, China. He received his PhD degree at the Institute of Psychology, Chinese Academy of Sciences, in 2005. His research interests include human factors, behavioral decision-making, human-AI interaction, road safety, and health.