House rules are essential for P2P accommodation hosts to regulate guest behavior and manage their properties; however, they can also represent a double-edged sword for guests. This research proposes to examine the joint effects of house rules from the perspective of human territoriality, and highlights two psychological mechanisms—uncertainty reduction and psychological reactance—that underline the nonlinear relationship between the number of house rules and rental performance. A sample of 12,108 Airbnb listings was processed using semi-supervised machine learning techniques as well as ordinary least squares and Bayesian estimations. Findings revealed an inverted U-shaped relationship: the number of house rules initially had a positive impact on rental performance, but this effect turned negative beyond a certain threshold. This relationship was mitigated by customer review volume. Conditions for the existence of an inverted U-shaped relationship were formally tested via Bayesian posterior distributions. Experimental evidence provided further support for the proposed mechanisms.

中文翻译：

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引导但受约束：家规对 P2P 住宿租赁表现的倒 U 型效应


入住须知对于 P2P 住宿房东规范房客行为和管理房源至关重要;然而，他们也可以代表客人的双刃剑。本研究建议从人类领土的角度考察家规的联合效应，并强调两种心理机制——不确定性减少和心理抗抗——它们强调了家规数量与租金表现之间的非线性关系。12,108 个 Airbnb 房源的样本使用半监督机器学习技术以及普通最小二乘法和贝叶斯估计进行处理。研究结果揭示了一个倒 U 形的关系：入住须知的数量最初对租金表现有积极影响，但超过某个阈值后，这种影响变成了负面影响。这种关系因买家评论量而得到缓解。通过贝叶斯后验分布正式检验了存在倒 U 形关系的条件。实验证据为所提出的机制提供了进一步的支持。