Authors: Luo, Bei; Lau, Raymond Y.K.; Li, Chunping
Abstract: To reduce service staff’s burden in customer servicing and improve the performan ...
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Abstract: To reduce service staff’s burden in customer servicing and improve the performance of automatic service re covery, we propose an emotion-regulatory chatbot for service recovery applications drawing on interpersonal emotion management (IEM) theory. In addition, we develop a model to examine the underlying mechanisms through which perceived IEM strategies influence consumers’ emotions and behavioral intentions. Our experi mental results verify the effectiveness of IEM strategies. We find that appraisals and consumers’ post-recovery emotions sequentially mediate the relationship between perceived emotion regulatory strategies and positive word-of-mouth (PWOM).
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Semantic filters:
affect control theory
Topics:
behavioral intention robotic electronic commerce customer service word of mouth
Methods:
chatbot experiment experimental group structural equation modeling parametric test
Theories:
control theory trust theory affect control theory