“…Yet, it is equally concerning that platform-related antecedents, such as customer service, cybersecurity, quality assurance, and system functionality ( Huang et al, 2020 , Tussyadiah and Pesonen, 2018 ), were found to negatively influence the actual stays of guests (eight negative votes), which indicates that platform-related antecedents are likely to be responsible for the intention–behavior gap in home sharing. Whereas, algorithmic management in home-sharing platforms, such as Bayesian social learning and dynamic pricing, was a platform-related antecedent that had a noteworthy impact on the pricing of home sharing (six positive votes, one neutral vote, and four negative votes), which in turn, corresponds to the economic returns encountered by hosts ( Gibbs et al, 2018 , Koh et al, 2019 , Kwok and Xie, 2019 ). Finally, the absence of third-order knowledge relating to cause-and-effect is noted, and given that home-sharing platforms are technologically-enabled, it may be worthwhile for future research to pursue eye-tracking experiments that could potentially reveal novel insights with respect to the content and navigational features that guests and hosts pay most attention to when they use the platforms to book or list shared homes, thereby strengthening theory in this area.…”