Purpose

Building upon uncertainty reduction theory, this work aims to explore how four uncertainty reduction factors (i.e. online property review, online textual description, online visual description and online instant messenger) mitigate property quality uncertainty and property fit uncertainty, which further influence Airbnb use intention.

Design/methodology/approach

This work tests the proposed research model using a structural equation modeling approach with 335 Airbnb users.

Findings

The findings reveal that the online property review, online textual description, online visual description and online instant messenger can efficiently mitigate property quality uncertainty and property fit uncertainty, which ultimately influence Airbnb use intention.

Research limitations/implications

This study provides useful insights on mitigating property uncertainty in the peer-to-peer (P2P) accommodation platforms. Researchers are encouraged to investigate the boundary conditions that influence the effectiveness of uncertainty reduction strategies in alleviating property uncertainty.

Practical implications

P2P accommodation service providers are suggested to take actionable uncertainty reduction strategies to mitigate property uncertainty in online P2P accommodation platforms.

Originality/value

First, this study advances research on P2P accommodation by identifying two key types of property uncertainty, namely, property quality uncertainty and property fit uncertainty. Second, this study extends research on P2P accommodation by proposing contextualized passive, active and interactive uncertainty reduction strategies in mitigating property uncertainty. Third, this study extends uncertainty reduction theory to the P2P accommodation context. Fourth, this study enriches uncertainty reduction theory by verifying the mediating effects of property quality uncertainty and property fit uncertainty.

中文翻译：

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减轻在线点对点住宿平台中的财产质量不确定性和财产适合不确定性：不确定性减少理论的观点

目的

基于不确定性降低理论，这项工作旨在探索四个不确定性降低因素（即在线房产评论、在线文本描述、在线视觉描述和在线即时消息）如何降低房产质量不确定性和房产适合性不确定性，从而进一步影响 Airbnb 使用意愿。

设计/方法/途径

这项工作使用结构方程建模方法对 335 个 Airbnb 用户测试了所提出的研究模型。

发现

研究结果表明，在线房产评论、在线文本描述、在线视觉描述和在线即时通讯工具可以有效地缓解房产质量不确定性和房产契合度不确定性，最终影响Airbnb的使用意愿。

研究局限性/影响

这项研究提供了有关减轻对等 (P2P) 住宿平台中财产不确定性的有用见解。鼓励研究人员研究影响不确定性降低策略在减轻属性不确定性方面有效性的边界条件。

实际影响

建议 P2P 住宿服务提供商采取可操作的不确定性减少策略，以减轻在线 P2P 住宿平台中的财产不确定性。

原创性/价值

首先，本研究通过确定财产不确定性的两种关键类型，即财产质量不确定性和财产适合不确定性，推进了 P2P 住宿的研究。其次，本研究通过提出情境化的被动、主动和交互式不确定性减少策略来减轻财产不确定性，从而扩展了对 P2P 住宿的研究。第三，本研究将不确定性减少理论扩展到 P2P 住宿环境。第四，本研究通过验证财产质量不确定性和财产匹配不确定性的中介作用，丰富了不确定性减少理论。