The impact of negative online ratings on physician effort to improve communication: Evidence from China

IF 5.5 1区 经济学 Q1 ECONOMICS
Zifan Li , Xuezheng Qin
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Abstract

How do negative online ratings affect physician effort? Despite a substantial body of literature on financial incentives, empirical evidence regarding the impact of non-financial incentives on physicians remains limited. This study investigates the influence of negative online ratings on physician effort to improve physician–patient communication, using data from a prominent online healthcare platform. Our findings indicate that negative online ratings lead to a significant increase of 18.7% in the number of online consultations replied to by physicians, a 56.6% rise in the number of words typed, a 43.4% increase in the number of dialogues between physicians and patients, and a 30.1% increase in the number of replies. Additionally, physicians exhibit a more positive tone and greater textual coherence, as evidenced by a 0.37 percentage point increase in the probability of providing high-sentiment replies and a 1.23 percentage point rise in the probability of offering high-similarity responses, indicating a noticeable increase in physician effort to improve communication. The effect is more pronounced among physicians holding senior professional titles and those with higher ratings.
负面在线评价对医生努力改善沟通的影响:来自中国的证据
负面在线评价如何影响医生的工作?尽管有大量关于财务激励的文献,但关于非财务激励对医生的影响的经验证据仍然有限。本研究调查负面在线评分对医生努力改善医患沟通的影响,使用来自一个著名的在线医疗保健平台的数据。我们的研究结果表明,负面在线评分导致医生回复的在线咨询数量显著增加了18.7%,输入的字数增加了56.6%,医生与患者之间的对话数量增加了43.4%,回复数量增加了30.1%。此外,医生表现出更积极的语气和更大的文本连贯性,提供高情绪回复的可能性增加了0.37个百分点,提供高相似回复的可能性增加了1.23个百分点,这表明医生在改善沟通方面的努力明显增加。这种影响在拥有高级职称和较高等级的医生中更为明显。
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来源期刊
中国经济评论
中国经济评论 ECONOMICS-
CiteScore
10.60
自引率
4.40%
发文量
380
期刊介绍: The China Economic Review publishes original works of scholarship which add to the knowledge of the economy of China and to economies as a discipline. We seek, in particular, papers dealing with policy, performance and institutional change. Empirical papers normally use a formal model, a data set, and standard statistical techniques. Submissions are subjected to double-blind peer review.
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