款待
私人信息检索
Boosting(机器学习)
出租
业务
面板数据
同侪效应
信息不对称
计量经济学
计算机科学
心理学
经济
旅游
社会心理学
财务
机器学习
政治学
法学
计算机安全
作者
Zuolong Zheng,Ziying Li,Xuwen Zhang,Sai Liang,Rob Law,Jiasu Lei
标识
DOI:10.1016/j.jbusres.2023.113822
摘要
Prior studies have attributed and confirmed the importance of hosts’ information disclosure on boosting their performance due to the prominent information asymmetry on peer-to-peer rental platforms. This study takes a step further by analyzing how hosts and neighbors’ disclosure of descriptions simultaneously and interactively influences the review volume and performance of Airbnb listings. Based on a panel dataset and fixed effect regression models, the results confirmed the findings of prior studies that self-disclosure of descriptions has a positive effect on the review volume and performance. We also initially find a substitute effect between self-disclosure of descriptions and neighbors’ disclosure of public information, with a complementary effect between self-disclosure of descriptions and neighbors’ disclosure of private information. As a novel attempt to analyze the effect of neighbors’ information disclosure on property performance, this study provides important implications for relevant literature and for hospitality professionals to improve information disclosure strategies.
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