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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