中心性
透视图(图形)
服务补救
服务(商务)
社会网络分析
主题分析
领域(数学)
知识管理
计算机科学
数据科学
业务
营销
社会学
社会化媒体
服务质量
万维网
定性研究
社会科学
人工智能
数学
组合数学
纯数学
作者
Dong Liu,Yanhui Zhao,Guocai Wang,Wyatt A. Schrock,Clay M. Voorhees
标识
DOI:10.1177/10946705231194006
摘要
Service failure and recovery (SFR) is a well-established area of research that has made considerable progress over the past 30 years. In this study, we used a combination of text mining, co-word analysis, and social network analysis (SNA) to explore the relationships among keywords in SFR research. We analyzed a dataset of 533 SFR articles published between 1990 and 2020, extracting the most frequently used keywords using text-mining techniques. These keywords were then subjected to co-word analysis and SNA to understand the development of themes and topics in SFR research. By examining changes in network centrality measures, we gained insights into the evolution of research in this field. Furthermore, by identifying gaps or disconnections in the keyword networks, we identified future research opportunities related to the impact of service recovery strategies on customer reactions, employee reactions, and firm outcomes, as well as the relationship between customer and employee responses.
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