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

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.

Accurately or accidentally? Recommendation agent and search experience in over-the-top (OTT) services

PurposeOver-the-top (OTT) services, which provide streaming media through all devices in online setting, have surpassed the traditional content providers in the market. However, there is still no clear empirical evidence that indicates what recommendation agent values affect the users' search experience while using the OTT services and how it leads to continuous subscription. To address this gap, this study aims to examine recommendation agent values influencing search experience, which in turn affects decision satisfaction and continuance intention.Design/methodology/approachThis study empirically develops and tests a research model with data obtained from 212 survey respondents in Korea. Structural equation modeling with partial least square approach was used to analyze the data.Findings(1) Recommendation agent variables such as match score accuracy, recommended content variety and thumbnail image appeal affect search experience variables such as perceived diagnosticity and perceived serendipity; (2) perceived diagnosticity and perceived serendipity of search experience increase decision satisfaction; and (3) decision satisfaction increases intention to continue to subscribe to OTT services.Originality/valueDespite the widespread use of recommendation agents in OTT services, limited attention has been paid to understand what specific values of recommendation agents lead subscribers to continue their subscription. The findings of this study clarify subscribers' continuous subscription behavior in OTT services in terms of the recommendation agent values and search experience perspective.