Thomas De Cleen, Philippe Baecke, Frank Goedertier
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引用次数: 0
Abstract
We study the impact of customer sentiment, agent sentiment, and emotional matching (i.e., call center agents matching emotional expressive states of customers) on satisfaction and recommendation intentions in a utilitarian service context. We methodologically contribute by text mining observed data using advanced transformer-based NLP algorithms and compare findings with those of previous survey-based research. An analysis of 25,008 call center conversations reveals that positive (vs negative) customer sentiment more strongly impacts satisfaction and recommendation. For recommendation (vs satisfaction) we observe that negative emotional expressions have a relatively stronger weight, albeit less strong than that of positive ones. We find that emotional expressions of call center agents (vs those of clients) have a smaller impact on these outcomes. Emotional matching is observed as beneficial, but not necessarily when faced with negative high-arousal emotional expressions. As conceptual grounding, we refer to theorizing around delight, formality, source credibility, emotional arousal and loss aversion.
期刊介绍:
The Journal of Business Research aims to publish research that is rigorous, relevant, and potentially impactful. It examines a wide variety of business decision contexts, processes, and activities, developing insights that are meaningful for theory, practice, and/or society at large. The research is intended to generate meaningful debates in academia and practice, that are thought provoking and have the potential to make a difference to conceptual thinking and/or practice. The Journal is published for a broad range of stakeholders, including scholars, researchers, executives, and policy makers. It aids the application of its research to practical situations and theoretical findings to the reality of the business world as well as to society. The Journal is abstracted and indexed in several databases, including Social Sciences Citation Index, ANBAR, Current Contents, Management Contents, Management Literature in Brief, PsycINFO, Information Service, RePEc, Academic Journal Guide, ABI/Inform, INSPEC, etc.