This study sought to examine the effect of the quality of chatbot services on customer satisfaction, repurchase intention, and positive word-of-mouth by comparing two groups, namely chatbots with and without emotion words. An online survey was conducted for 2 weeks in May 2021. A total of 380 responses were collected and analyzed using structural equation modeling to test the hypothesis. The theoretical basis of the study was the SERVQUAL theory, which is widely used in measuring and managing service quality in various industries. The results showed that the assurance and reliability of chatbots positively impact customer satisfaction for both groups. However, empathy and interactivity positively affect customer satisfaction only for chatbots with emotion words. Responsiveness did not have an impact on customer satisfaction for both groups. Customer satisfaction positively impacts repurchase intention and positive word-of-mouth for both groups. The findings of this study can serve as a priori research to empirically prove the effectiveness of chatbots with emotion words.

The role of employee’s emotions are examined as influencers of job satisfaction, affective organizational commitment, and turnover intentions within a frontline employee context. Using a sample of 126 retail employees, structural equation modeling is used to test the theoretically developed model. Findings suggest that deep acting emotions and emotional exhaustion significantly impact job satisfaction, whereas both deep acting emotions and job satisfaction predict affective organizational commitment. When predicting turnover intentions, surface and deep acting emotions, along with emotional exhaustion, each significantly impact turnover intentions; however, neither job satisfaction nor affective organizational commitment are significant predictors.