The Impact of Restaurant Recommendation Information and Recommendation Agent in the Tourism Website on the Satisfaction, Continuous Usage, and Destination Visit Intention

Bibliographic Data

ID3245566
AuthorsYan Chao Shi (0000-0002-3222-168X), Yan Shi (0000-0003-0320-3244, Linyi University), U K Lee (0000-0003-1649-4706, University of Suwon, corresponding author)
Year2021
Volume11
Issue4
Publication date2021-10-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSAGE Open (JOURNAL)
Journal identifiersISSN: 2158-2440 • E-ISSN: 2158-2440
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/21582440211046947
OpenAlexW3211478248
LanguageEN
Citations received5
References cited111

Enjoying local food could be one of the motives for tourism, and local food and restaurant recommendation information would be important for tourists to decide their destination. Recommendation agents are the sorting and searching function to find the best local food and restaurant among the complexity of information, and they could also be helpful for the tourist to decide their destination. Online tourism websites (e.g., Ctrip.com ) started to provide restaurant recommendations containing food-related information and recommendation agents to attract tourists. However, few studies have investigated their impact on the destination visit intention of potential Chinese tourists. This study aims to empirically validate how restaurant recommendation information, including food-related information and recommendation agents, could impact online tourists' reactions, such as satisfaction, continuous website usage, and destination visits. We developed our hypothesis based on the information system (IS) success model. We gathered 202 data points from potential tourists using quasi-experimental methods, and these data were analyzed by the PLS algorithm. The results indicate that restaurant recommendation information and recommendation agents significantly increase the perceived information quality and perceived system quality. Increased perceived information quality and system quality could significantly increase potential tourists' satisfaction, website continuous usage intention, and destination visit intention. The results of this study could contribute to making tourism websites more attractive by using local food and restaurant information and recommendation agents

Advertising · Business · Geography · Information quality · Information system · Recommender system · Tourism · World Wide Web · Computer Science · Customer Service Quality and Loyalty · Digital Marketing and Social Media · Diverse Aspects of Tourism Research · Marketing

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