This study aims to examine the effect of chatbots’ emotional
expressions on customer satisfaction with service recovery in digital
service failure contexts. The research investigates the mediating roles of expectancy violations, perceived empathy, and trust, in addition to
examining the moderating effects of chatbot identity disclosure and service failure severity. The study is grounded in several contemporary theoretical
frameworks, including the Computers Are Social Actors (CASA)
paradigm, the Emotions as Social Information (EASI) theory, Expectancy Violations Theory (EVT), Expectation Disconfirmation Theory (EDT), and Emotional Contagion Theory (ECT). The research utilized a sample of 326 respondents from users of digital platforms in the telecommunications, electronic banking, e-commerce, and digital government services sectors in Egypt, collected through an online directed random sampling technique. The findings reveal a significant positive effect of chatbots’ emotional expressions on customer satisfaction with service recovery. The results further show that emotional expressions reduce expectancy violations, and that expectancy violations mediate the relationship between emotional expressions and service recovery satisfaction. Additionally, perceived empathy and trust were found to mediate this relationship. The study also demonstrates that chatbot identity disclosure moderates the positive effect of emotional expressions on both perceived empathy and trust. Finally, the results indicate that service failure severity moderates the relationship between chatbots’ emotional expressions and service recovery satisfaction.
This study contributes to the theoretical understanding of the role of
emotional expressions in digital service recovery and offers practical recommendations for organizations and developers on enhancing service recovery mechanisms through chatbots by incorporating emotional
expression strategies, increasing transparency, and considering the severity level of service failures. |
