https://orcid.org/0000-0003-2415-3223
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ABSTRACT
The widely publicized impact of user-generated review (UGR) sites on sales has spawned a large number of studies on user behaviors on UGR sites. These existing studies center on conversions of visitors into paying customers, and the creation and dissemination of online reviews. UGR site visitors will consider emotional cues in reviews more seriously if the product offered is more enjoyment-based, hedonic, than utilitarian. This study examines the impact of user enjoyment, when reading reviews on hedonic products, on dissemination of those reviews with their personal social circles. Specifically, to examine user enjoyment on UGR sites, we apply the concept of flow – enjoyable experiences that are intense and enticing enough to convert visitors to endorsers. We conducted two online surveys to contrast our suggested flow-based explanation on dissemination against alternative rationality-based one. The findings from our surveys show that the flow state increases their intentions to recommend the establishments, while the objectivity of reviews and expertise of reviewers are limited in explaining such.
Notes
1. To further demonstrate the model fit, we ran a covariance-based structural equation modeling (SEM), using the lavaan package in R, to provide fit indices used for assessing the fit of covariance-based SEMs (Kline, Citation2015). Recall that our model is based on PLS-based SEM; thus, these additional steps are not necessary. However, to ensure the appropriateness of our model fit, we provide this additional set of model fit indices. The three most common indices for covariance-based SEM are comparative fit index (CFI), root mean square error of approximation (RMSEA), and SRMR (Kline, Citation2015). CFI should be greater than 0.90; both RMSEA and SRMR should not be greater than 0.08 (Hu & Bentler, Citation1999; Kline, Citation2015). Our CFI is 0.91; RMSEA and SRMR are 0.08 and 0.07, all of which indicate our model fit is appropriate.
2. In addition, we offer fit indices appropriate for covariance-based structural equation modeling: The comparative fit index was .95, greater than the suggested level of .90; RMSEA and SRMR were both .07 and .04, respectively, less than the benchmark level of 0.8, thus indicating that the model fit was appropriate (Hu & Bentler, Citation1999; Kline, Citation2015).
Additional information
Notes on contributors
Young Anna Argyris
Young Anna Argyris is Assistant Professor of Media and Information, Michigan State University. She has received a PhD from the Sauder School of Business, University of British Columbia. Her work has appeared in MIS Quarterly, Information Systems Research, Communication of the ACM, and ACM Transactions on Computer-Human Interaction, among others.
Aziz Muqaddam
Aziz Muqaddam is a PhD candidate of Information and Media at Michigan State University. His research areas primarily revolve around consumer psychology. The three main domains Aziz investigates are: the interaction between personality and influence, social-comparison behavior, and social media effects on attitudes.
Yuyang Liang
Yuyang Liang is a PhD candidate of Information and Media at Michigan State University. His areas of interest include knowledge sharing and collaboration via online communities and social media, and computational modeling of social systems. His work has appeared in top computer-supported cooperative work and information system conferences.