声誉
出租
款待
酒店业
营销
共享经济
透视图(图形)
业务
独创性
信誉制度
旅游
心理学
社会心理学
社会学
计算机科学
地理
万维网
工程类
社会科学
土木工程
考古
人工智能
创造力
作者
Qiang Ye,Sai Liang,Zaiyan Wei,Rob Law
标识
DOI:10.1108/ijchm-09-2022-1170
摘要
Purpose From the perspective of two-sided review systems, this study aims to investigate how guests’ prior reputation influences their subsequent satisfaction on Airbnb. Design/methodology/approach This study applied a conceptual framework based on social capital theory to explain the effect of guests’ reputation decided by hosts’ prior evaluations on their subsequent satisfaction. The authors collected 96,204 guest reviews posted for 17,325 properties on Airbnb and used the review polarity to measure guest satisfaction. All historical evaluations generated by hosts for each guest were collected and treated as a proxy of guest reputation. Ordinary least squares regressions were conducted to estimate the effect of guests’ reputation on their subsequent satisfaction. Findings Results show that guests whose historical evaluations have higher valences or larger variations tend to be more satisfied in their subsequent bookings. However, the number of reviews that guests received from hosts in the past does not influence their subsequent satisfaction. Research limitations/implications This study provides new insights into the hospitality literature by identifying the influencing factors of guest satisfaction on peer-to-peer rental platforms from the perspective of two-sided review systems. Results also present practical implications to property owners and website designers to gain a deeper understanding of the determinants of guest satisfaction and the consequences of social interactions between hosts and guests. Originality/value This study is a novel attempt that analyzes the effect of guests’ reputation on their satisfaction with subsequent bookings based on two-sided review systems on peer-to-peer rental platforms. Thus, this study provides a starting point for investigating how two-sided review systems affect use behavior on peer-to-peer rental platforms.
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