User-generated Features Research Articles

Examining the determinants of the count of customer reviews in peer-to-peer home-sharing platforms using clustering and count regression techniques

The sharing economy has experienced massive growth in the short-term shared-home rental industry. However, few studies have investigated the determinants of the number of customer reviews received by these shared-homes. To fill this gap, we were motivated to propose an analytical framework that identified these determinants, both explicit and implicit. We applied Poisson, Quasi-Poisson, and Negative Binomial regressions with a dataset consisting of Airbnb properties from ten different cities worldwide, while successful bookings were proxied by the count of customer reviews posted by guests. We performed a cluster analysis based on the properties to generate homogeneous “cluster cities” and performed the regressions separately for each cluster. Among host-generated features, superhost, host duration, bedrooms, and amenities became significant. Among user-generated features, overall review scores and negative sentiments were significant. We also found that the “superhost” badge moderated the effects of host-generated content on the count of customer reviews. Consequently, guests paid a higher “price per night” for “superhost” properties, while they overlooked crucial attributes such as “website features.” Through these novel “cluster-specific” recommendations, our study extends the existing theories and contributes to the literature of decision analytics and tourism management. Finally, we performed a sensitivity analysis to check for the timeliness and robustness of these determinants.

Web 2.0 for Health Promotion: Reviewing the Current Evidence

As Web 2.0 and social media make the communication landscape increasingly participatory, empirical evidence is needed regarding their impact on and utility for health promotion. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we searched 4 medical and social science databases for literature (2004-present) on the intersection of Web 2.0 and health. A total of 514 unique publications matched our criteria. We classified references as commentaries and reviews (n = 267), descriptive studies (n = 213), and pilot intervention studies (n = 34). The scarcity of empirical evidence points to the need for more interventions with participatory and user-generated features. Innovative study designs and measurement methods are needed to understand the communication landscape and to critically assess intervention effectiveness. To address health disparities, interventions must consider accessibility for vulnerable populations.