The study aims to examine the effects of ulterior motives in peer and expert supplementary online hotel reviews on consumers' perceived deception, dissatisfaction, and its downstream effects on altruistic response and repurchase intentions. The research also examines the moderating role of hotel attribute performance on perceived deception and its consequents.
This study used convenient non-probability sampling and collected data from 448 inbound tourists in China. It used partial least square structural equation modeling technique and SmartPLS 3.0 for analyzing the main and moderating effects of the variables.
The ulterior motives in peer and expert supplementary reviews significantly affect perceived deception, further leading to consumers' dissatisfaction and engagement in altruistic response. Noticeably, consumers' dissatisfaction is positively associated with repeat purchase intentions. Hotel attribute performance significantly moderates the relationship between the ulterior motives in supplementary reviews and consumers' perceived deception.
The study examines the key issue in online hotel reviews using the expectancy disconfirmation theory and identifies consumers' altruistic behavior because of their dissatisfaction, contributing to ethics and consumer behavior literature. Moreover, the research offers prolific implications for hotel and travel websites and hoteliers in the study context.
We would like to thank the Editor-in-Chief Ian Phau and two anonymous reviewers for their honest, helpful, and constructive comments. This research was funded by grants from the National Natural Science Foundation of China awarded to Jin Sun (Grant No. 71772040) and also supported by the Program for Excellent Talents in UIBE (Grant No. 17JQ03).
Siddiqi, U., Sun, J. and Akhtar, N. (2020), "Ulterior motives in peer and expert supplementary online reviews and consumers' perceived deception", Asia Pacific Journal of Marketing and Logistics, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/APJML-06-2019-0399Download as .RIS
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