Paper Type
ERF
Abstract
Artificial Emotional Intelligence (AEI) chatbots increasingly support users under stress, yet Information Systems research lacks theoretical clarity regarding how distinct empathic capabilities influence stress reduction and the underlying mechanisms. Building on CASA, ELM, and stress/social support theory, we develop a moderated mediation model in which empathy detection (recognizing and labeling users’ emotions) and empathy generation (delivering supportive, context-specific responses) influence stress reduction indirectly through perceived emotional authenticity (PEA). We further theorize that issue involvement conditions their relative effectiveness, such that empathy detection is more influential under low involvement, whereas empathy generation becomes more influential under high involvement. The model will be tested using a 2×2 vignette-based, between-subjects experiment with students at a U.S. university. The study contributes to IS research by conceptualizing AEI as separable technology capabilities, identifying PEA as a key explanatory mechanism, and offering theory-driven guidance for designing empathic conversational agents that support user well-being.
Paper Number
1679
Recommended Citation
Islam, Mohammad Arif Ul and Iyer, Lakshmi, "Bridging Stress and Conversational Agents: The Role of Empathy, Issue Involvement, and Perceived Emotional Authenticity in Artificial Emotional Intelligence (AEI)" (2026). AMCIS 2026 Proceedings. 6.
https://aisel.aisnet.org/amcis2026/ai_aiaa/ai_aiaa/6
Bridging Stress and Conversational Agents: The Role of Empathy, Issue Involvement, and Perceived Emotional Authenticity in Artificial Emotional Intelligence (AEI)
Artificial Emotional Intelligence (AEI) chatbots increasingly support users under stress, yet Information Systems research lacks theoretical clarity regarding how distinct empathic capabilities influence stress reduction and the underlying mechanisms. Building on CASA, ELM, and stress/social support theory, we develop a moderated mediation model in which empathy detection (recognizing and labeling users’ emotions) and empathy generation (delivering supportive, context-specific responses) influence stress reduction indirectly through perceived emotional authenticity (PEA). We further theorize that issue involvement conditions their relative effectiveness, such that empathy detection is more influential under low involvement, whereas empathy generation becomes more influential under high involvement. The model will be tested using a 2×2 vignette-based, between-subjects experiment with students at a U.S. university. The study contributes to IS research by conceptualizing AEI as separable technology capabilities, identifying PEA as a key explanatory mechanism, and offering theory-driven guidance for designing empathic conversational agents that support user well-being.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.
Comments
SIG AIAA