患者满意度
背景(考古学)
匹配(统计)
心理学
服务(商务)
口头传述的
独创性
价值(数学)
经验证据
实证研究
医学
营销
社会心理学
护理部
业务
计算机科学
古生物学
哲学
认识论
病理
机器学习
创造力
生物
作者
Hao Wang,Shan Liu,Baojun Gao,Arslan Aziz
出处
期刊:Information Technology & People
[Emerald (MCB UP)]
日期:2024-07-31
标识
DOI:10.1108/itp-04-2023-0332
摘要
Purpose This study aims to explore whether seeking recommendations for doctors from offline word-of-mouth or online reviews influences patient satisfaction after treatment, and how the source of recommendation affects this effect. Design/methodology/approach Using a unique dataset of more than three million reviews from a popular Chinese online health community, this study used the coarsened exact matching method and built fixed-effect models to conduct empirical analysis. Findings The results suggest that selecting doctors according to recommendations can improve patient satisfaction and mitigate their dissatisfaction when encountering service failures. However, online recommendations were found to be less effective than offline sources in improving patient satisfaction. Originality/value This study provides important insights into patient satisfaction and doctor-patient relationships by revealing the antecedents of satisfaction and the potential for improving this relationship. It also contributes to the understanding of how recommendations in the healthcare context can improve patient satisfaction and alleviate the negative impact of service failures.
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