Exploring the effect of heuristic factors on the popularity of user-curated ‘Best places to visit’ recommendations in an online travel community

Crowded and popular: The two sides of the coin affecting theme-park experience, satisfaction, and loyalty

“…Past research suggests a positive relationship between perceived crowding and perceived popularity. Even though a clear definition and measure of popularity does not exist in the literature ( Li, Lee, & Yang, 2019 ; Peng & Huang, 2017 ; Sæþórsdóttir, 2013 ), different measures are proposed as indicators of popularity. Gordon (2011) suggests statistics to understand historical and present tourism patterns, while social media has gained traction in the generation and dissemination of tourist information in recent years.…”

Customer Value Framework and Recommendation Intention: The Moderating Role of Customer Characteristics in an Online Travel Community

“…Thus, functional value, hedonic value and social value showed positive relationships with recommendation intention. Value is at the fabric of consumers' relationships with service providers and destinations; as such, services or places that are perceived to offer value will ultimately be recommended [12]. Additionally, functional value demonstrated the strongest relationship with recommendation intention compared to social and hedonic value.…”

“…For instance, [11] found that males and females differ significantly regarding satisfaction, relationship maintenance, entertainment and disconfirmation of entertainment with Facebook. Understanding how customer value impacts recommendation intention in OTCs is critical because the sustainability of OTCs depends on new members who join the platform, of whom a significant number have often been motivated by the recommendations of existing users [12]. Accordingly, this study has two main objectives: examining the effect of the customer value framework on recommendation intention and understanding the role of the customer value framework on a participant's characteristics in relation to recommendation intention.…”

Point-of-interest lists and their potential in recommendation systems

“…Finally, an interesting work that aimed to identify and validate the heuristic factors affecting the popularity of “best places to visit” recommendations was presented in Li et al. ( 2019 ). This empirical study focused on the explicit best places to visit listings in Qyer.com, a concept that is also a subset of Foursquare lists which contain opinionated recommendations (“Best places to visit in...”).…”