From rational to emotional: A human-centric operations research framework integrating emotion artifical intelligence

Authors : Can Mavruk

Pages : 368-382

Doi:10.30783/nevsosbilen.1739466

View : 41 | Download : 104

Publication Date : 2025-12-07

Article Type : Research Paper

Abstract :The rise of Emotion Artificial Intelligence (EAI) presents new opportunities for enhancing decision-making in Operations Research (OR) by incorporating human emotional states into analytical models. This study explores how emotional data, such as customer sentiment, can be operationalized in OR models for improved outcomes in service systems. Using simulation and synthetic datasets in Python programming language, the research demonstrates the value of emotion-aware optimization in a call center scenario, yielding improvements in satisfaction and operational efficiency. A second simulation data is generated for emotion detection in call center scenario (neutral, frustrated, happy and angry) to explore how customer satisfaction varies within each detected emotion group and which emotion leads to longer calls. The paper proposes a three-layered conceptual framework, evaluates the implications through statistical analysis, and outlines ethical considerations for implementation. The results indicate that in the call center scenario (n = 100 simulated cases), integrating emotional data resulted in 17% reduction in call escalations, average satisfaction increased from 3.4 to 4.1, and improved routing efficiency without increasing staff. The findings support a new direction for OR that is adaptive, empathetic, and behaviorally informed, and for the nascent yet promising convergence.
Keywords : Duygu yapay zeka, Yöneylem araştırması, İnsan merkezli optimizasyon, Karar modelleme, Duygusal iletişim

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