The strategy of wayfinding and System Performance for Recommendation intention – A Case Study of Airbnb

• Main Authors: LIU, LING-LING, 劉陵陵
• Other Authors: Sun, Lou-Hon
• Format: Others
• Language: en_US
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/hf6mdb

碩士 === 國立高雄餐旅大學 === 餐旅研究所 === 105 === Recommend suitable mobile applications (apps) for travelers will lead to travelers’ convenience and satisfaction on their trip. Distinct from other apps which have emphasized its lowest price guarantee, Airbnb.com tends to give priority to geographical location to help travelers find the closest destination to their place of stay. Nevertheless, travelers may feel lost when exposed to unfamiliar environments, which result in the need for wayfinding. This study explores how travelers connect the relationship between their accommodation and the destinations that influence the apps performance through wayfinding strategies with apps. In this study, a recommendation intention model was formulated from the perspective of S-D logic and O2O. According to snowball sampling, we require users to invite other travelers who also had user experience on Airbnb.com. In total, 416 of which were returned. The results provide meaningful support for our research hypotheses, five of which are fully supported, one is not supported. Although the results suggest that convenience of apps is not positively associated with recommendation intention, it may arise from several reasons such as lacking of Internet in travel places. Final, the apps with excellent utility makes travelers put less effort to find out the most suitable accommodation. Considering the demands of travelers before they need is the prime directive of enhancing the application utility. With satisfaction, continuance intention and hedonic benefit obtained from the apps; result in the travelers’ intention of recommendation.