Consumer Behavior

Exploring the Impact of Textual Paralanguage in AI Customer Agent: Emotional Pathways and Service Outcomes

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Abstract

This research investigates how textual paralanguage functions as a social–emotional cue in AI customer service. Using the S-O-R framework and CASA paradigm, a between-subjects experiment (N = 192) compared high versus low paralanguage conditions. SEM results show that textual paralanguage significantly increases emotional contagion, which subsequently improves satisfaction, perceived service quality, and problem resolution. Perspective-taking and empathic concern were not significant mediators. Multi-group analysis across low- and high–Need for Affect consumers demonstrated structural invariance, indicating that NFA does not moderate these pathways. TheseNeed for Affect findings deepen understanding of emotional mechanisms in AI–human interaction and highlight emotional contagion as the key driver of positive service evaluations

Keywords: Textual Paralanguage, AI Service Communication, Emotional Contagion, CASA Paradigm, Ai Chatbot, Need for Affect, Human–AI Interaction

How to Cite:

Lin, X., Xu, Y. & Ding, Y., (2025) “Exploring the Impact of Textual Paralanguage in AI Customer Agent: Emotional Pathways and Service Outcomes”, International Textile and Apparel Association Annual Conference Proceedings 82(1). doi: https://doi.org/10.31274/itaa.22042