{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T22:06:02Z","timestamp":1767650762409,"version":"3.41.2"},"reference-count":54,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2018,2,2]],"date-time":"2018-02-02T00:00:00Z","timestamp":1517529600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["K"],"published-print":{"date-parts":[[2018,5,2]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>The purpose of this study is to establish a comprehensive service recovery mechanism by analyzing different behaviors of customers with different personality traits after service failures and by proposing different service recovery measures that service providers could adopt based on diverse customer personality traits.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>This paper constructs a service recovery mechanism based on a signaling game theory by considering customers and service providers as two players in the game and analyzing possible outcomes under both separating and pooling equilibria to achieve an optimized strategy and set of actions that allow the highest payoffs for both service providers and customers.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>This study successfully simulated the separating equilibrium and pooling equilibrium between service providers and customers in a signaling game with incomplete information. It also provides a reference for service providers to design service recovery strategies after service failures. By using this model, when facing problems related to service failures and service recovery, service providers will have a better chance of increasing the service recovery success rate, improving customer satisfaction and achieving optimal payoffs for both themselves and their customers.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>Based on concepts of service science, this study designed a service recovery mechanism by applying the signaling game from game theory and introducing personality traits theory to the service recovery scenario so that service providers are able to execute service recovery after service failures more effectively. This study proposed a service recovery mechanism based on the perspectives of both service providers and customers, considering the mutual influence of key variables related to both of them, as well as the context of service failures, customers\u2019 personality traits and service providers\u2019 available resources. Many studies have applied personality traits to different fields; however, to the best of authors\u2019 knowledge, few studies have applied this concept to service-related subjects, and only the influence of employees\u2019 personality traits on service providers has been discussed.<\/jats:p><\/jats:sec>","DOI":"10.1108\/k-05-2017-0171","type":"journal-article","created":{"date-parts":[[2018,2,2]],"date-time":"2018-02-02T04:15:51Z","timestamp":1517544951000},"page":"888-919","source":"Crossref","is-referenced-by-count":7,"title":["Modeling dynamic service recovery strategies: a signaling game 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