企业策略如何影响在线评论中的消费者偏见

IF 1.9 4区 管理学 Q3 BUSINESS
Frances Xinhua Wang, C. Anderson
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引用次数: 2

摘要

在线评论对消费者和企业都变得越来越重要,因此也引起了相当多的研究关注。然而,并非所有评论都是平等的,因为消费者留下评论的倾向可能会有所不同,这通常是他们满意度的一个函数。为了确保更有代表性的客户声音,公司通常使用不同的策略来缓和在线评论中的偏见。许多酒店公司采用的策略在收集评论的方式和发布评论的位置上都有很大的不同。本研究调查了主要酒店公司的四种评论收集策略,并分析了每种策略如何影响评论评级和长度。我们发现发布评审所需要的努力会影响评审的特征。我们发现,通过自我激励方法收集的评论往往评分较低且篇幅较长,而通过离职后电子邮件从公司征求的评论往往表现出不同的特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How Firm Strategies Affect Consumer Biases in Online Reviews
Online reviews have become increasingly important to both consumers and businesses and, as a result, have attracted considerable research attention. However, all reviews are not created equal as consumers may differ in their propensities to leave reviews, often as a function of their satisfaction. To ensure a more representative customer voice, companies often utilize different strategies to moderate the biases in online reviews. The strategies deployed by many hospitality firms differ dramatically in both how reviews are collected and where they are posted. This study investigates four review-collection strategies of major hospitality companies and analyzes how each strategy affects review ratings and length. We find that the effort required to post a review impacts review characteristics. We show that reviews collected through self-motivation methods tend to be lower rated and longer, whereas reviews solicited from companies through poststay emails tend to exhibit different characteristics.
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来源期刊
Service Science
Service Science Multiple-
CiteScore
3.30
自引率
4.30%
发文量
22
期刊介绍: Service Science publishes innovative and original papers on all topics related to service, including work that crosses traditional disciplinary boundaries. It is the primary forum for presenting new theories and new empirical results in the emerging, interdisciplinary science of service, incorporating research, education, and practice, documenting empirical, modeling, and theoretical studies of service and service systems. Topics covered include but are not limited to the following: Service Management, Operations, Engineering, Economics, Design, and Marketing Service System Analysis and Computational Simulation Service Theories and Research Methods Case Studies and Application Areas, such as healthcare, energy, finance, information technology, logistics, and public services.
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