期刊
INFORMATION PROCESSING & MANAGEMENT
卷 56, 期 4, 页码 1391-1408出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ipm.2018.03.009
关键词
Best places to visit; Destination recommendation; Recommender-related heuristic factors; Recommendation-related heuristic factors; Heuristic-systematic model; Recommendation popularity; Qyer.com
资金
- Ministry of Education of the Republic of Korea
- National Research Foundation of Korea [NRF-2017S1A5B8059804]
- National Research Foundation of Korea [2017S1A5B8059804] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
In online travel communities, 'Top-K best places to visit' recommendations are gaining more attention from travelers due to their ubiquitous access to the Internet, but little empirical effort has been made to investigate what factors lead to the popularity of user-curated 'best places to visit (BP2V)' recommendations. This research therefore aims to identify and validate the heuristic factors affecting the popularity of BP2V recommendations. Based on the heuristic-systematic model (HSM) of persuasion, we derive recommender-related (i.e., recommender's identity disclosure, reputation, experience, and location of residency) and recommendation-related (i.e., number of places recommended, helpfulness rating, number of comments added, and length of recommendation) heuristic characteristics of BP2V recommendations and investigate their impact on recommendation popularity. In addition, this study examines the moderating effect of destination category (i.e., attractions, food, shopping, and activities) on the relationship between heuristic characteristics and the popularity of BP2V recommendations. Our empirical results, which were based on 565 'best places to visit in the U.S.' recommendation postings from Qyer.com , a major online travel community in China, suggest that recommender's identity disclosure, reputation, number of places recommended, helpfulness rating, and length of recommendation are positively associated with recommendation popularity. We also found that the relationships between heuristic factors and the popularity of BP2V recommendations are contingent on destination category. This study will contribute to the body of knowledge on online travel communities and HSM and provide valuable implications for general travelers and managers in the tourism and hospitality industry.
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