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Sentiment and guest satisfaction with peer-to-peer accommodation: When are online ratings more trustworthy?
Institution:1. Shenzhen University, School of Economics, China;2. Shenzhen University, Shenzhen Audencia Business School, China;3. Curtin University, School of Marketing, Curtin Business School, Perth, Australia;1. Nottingham Business School, Nottingham Trent University, Nottingham, United Kingdom;2. University of Sadat City, Sadat City, Menofia, Egypt;3. United Arab Emirates University, P.O. Box 15551, Al-Ain, United Arab Emirates;1. School of Hospitality and Tourism Management, University of Surrey, 56AP02 Austin Pearce Building, Guildford, GU2 7XH, United Kingdom;2. School of Hotel and Tourism Management, The Hong Kong Polytechnic University, 17 Science Museum Road, TST East, Kowloon, Hong Kong;1. School of Hospitality and Tourism Management, Oklahoma State University, 365 Human Sciences, Stillwater, OK, 74078, USA;2. Shanghai Business School, 123 Fengpu Ave, Fengxian Qu, Shanghai, China;3. School of Hospitality and Tourism Management, Oklahoma State University, 367E Human Sciences, Stillwater, OK, 74078, USA;4. Dedman School of Hospitality, Florida State University, 288 Champions Way, B4113 University Center, PO Box 3062541, Tallahassee, FL 32306, USA;5. Dedman School of Hospitality, Florida State University, 288 Champions Way, B4114 University Center, PO Box 3062541, Tallahassee, FL 32306, USA;1. School of Management, Shenzhen Polytechnic College, Xili, Nanshan Dist., Shenzhen, China;2. SHTM, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
Abstract:This study aims to decode guest satisfaction with peer-to-peer accommodations by analyzing the relationship between guests’ sentiment and online ratings and examining how analytical thinking and authenticity influence this relationship. Based on reviews of 4602 Airbnb listings in San Francisco, we empirically find that positive (negative) sentiment is linked to a high (low) rating. We further show that this link is stronger when guests manifest a higher extent of analytical thinking and authenticity. Both Tobit and ordered logit models yield consistent estimation results, showing the robustness of our findings. Our study contributes to the tourism and hospitality literature by theoretically explaining the association between sentiment and ratings. In addition, this paper enriches our knowledge regarding the trustworthiness of Airbnb ratings.
Keywords:Peer-to-peer accommodation  Guest satisfaction  Online ratings  Sentiment analysis  Analytical thinking  Authenticity
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