Reducing the Bias in Online Reviews Using Propensity Score Adjustment

IF 3.4 4区管理学 Q1 HOSPITALITY, LEISURE, SPORT & TOURISM

Cornell Hospitality Quarterly Pub Date : 2024-01-08 DOI:10.1177/19389655231223364

Saram Han, Daria Mikhailova

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引用次数: 0

Abstract

Online hotel reviews on platforms like TripAdvisor are crucial in shaping customer choices and steering business strategies in the hospitality sector. However, the effectiveness of these platforms is partially hindered by the self-selection bias found in voluntary reviews. This bias can create false expectations and unsatisfactory experiences, mainly as the feedback generally comes from a non-representative group of self-motivated reviewers (SMRs). A common strategy to mitigate this bias is increasing the number of reviews through customer surveys, generating retailer-prompted reviews (RPRs). However, these RPRs, despite reducing selection bias, tend to lack the depth and insight of SMRs, resulting in a credibility gap and reduced representativeness. To address this, our study presents a novel approach using the propensity score adjustment (PSA) technique. This method leverages the distribution of RPRs to refine the accuracy of text data from SMRs, aiming to enhance the reliability and representativeness of online reviews. By combining the strengths of both RPRs and SMRs, we aim to create an online review environment that is both accurate and reliable. In conclusion, this research marks an important step toward improving online review platforms, aiming for a more transparent and trustworthy environment for reviews.

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利用倾向得分调整减少在线评论中的偏差

TripAdvisor 等平台上的在线酒店评论对于影响客户选择和指导酒店业的业务战略至关重要。然而，自愿评论中的自我选择偏差部分阻碍了这些平台的有效性。这种偏差可能会造成错误的预期和不满意的体验，主要是因为反馈通常来自非代表性的自发评论者（SMR）群体。减少这种偏差的常见策略是通过客户调查增加评论数量，产生零售商提示评论（RPR）。然而，这些 RPR 虽然减少了选择偏差，但往往缺乏 SMR 的深度和洞察力，从而导致可信度差距和代表性降低。为了解决这个问题，我们的研究提出了一种使用倾向得分调整（PSA）技术的新方法。这种方法利用 RPRs 的分布来完善 SMRs 文本数据的准确性，旨在提高在线评论的可靠性和代表性。通过结合 RPR 和 SMR 的优势，我们旨在创建一个既准确又可靠的在线评论环境。总之，这项研究标志着我们在改进在线评论平台方面迈出了重要的一步，旨在创造一个更加透明和可信的评论环境。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cornell Hospitality Quarterly Multiple-

CiteScore

8.50

自引率

2.90%

发文量

期刊介绍： Cornell Hospitality Quarterly (CQ) publishes research in all business disciplines that contribute to management practice in the hospitality and tourism industries. Like the hospitality industry itself, the editorial content of CQ is broad, including topics in strategic management, consumer behavior, marketing, financial management, real-estate, accounting, operations management, planning and design, human resources management, applied economics, information technology, international development, communications, travel and tourism, and more general management. The audience is academics, hospitality managers, developers, consultants, investors, and students.