Exploring the effect of heuristic factors on the popularity of user-curated ‘Best places to visit’ recommendations in an online travel community
作者：
Highlights：
• This paper is among the first empirical studies on user-curated ‘best places to visit (BP2V)’ recommendations.
• We identify eight heuristic factors embedded in user-curated BP2V recommendations and investigate which heuristic characteristics have a significant effect on recommendation popularity.
• We test the moderating effect of destination category (i.e., attractions, food, shopping, and activities) on the relationship between heuristic characteristics and user-curated BP2V recommendation popularity.
• Our findings help managers of online travel communities by highlighting certain heuristic cues in order to facilitate user experience.
• Our findings contribute to the body of knowledge on smart tourism and the heuristic-systematic model.
摘要
•This paper is among the first empirical studies on user-curated ‘best places to visit (BP2V)’ recommendations.•We identify eight heuristic factors embedded in user-curated BP2V recommendations and investigate which heuristic characteristics have a significant effect on recommendation popularity.•We test the moderating effect of destination category (i.e., attractions, food, shopping, and activities) on the relationship between heuristic characteristics and user-curated BP2V recommendation popularity.•Our findings help managers of online travel communities by highlighting certain heuristic cues in order to facilitate user experience.•Our findings contribute to the body of knowledge on smart tourism and the heuristic-systematic model.
论文关键词：Best places to visit,Destination recommendation,Recommender-related heuristic factors,Recommendation-related heuristic factors,Heuristic-systematic model,Recommendation popularity,Qyer.com
论文评审过程：Received 31 October 2017, Revised 21 January 2018, Accepted 17 March 2018, Available online 31 March 2018, Version of Record 14 May 2019.
论文官网地址：https://doi.org/10.1016/j.ipm.2018.03.009
