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. |
