Implementation Challenges of Affective Computing in Customer Relationship Management (CRM) Platforms: A Systematic and Bibliometric Review

Advancing technologies of affective computing have been prompted by the swift development of Artificial Intelligence (AI) to identify, interpret, and react to customers' feelings using multimodal data in Customer Relationship Management (CRM) systems. In spite of the great potential that affective computing has for improving customer engagement and personalised services, there are technical, ethical and organisational challenges that needs are not thoroughly synthesized in the literature. Based on this, the aim of this study is to systematically investigate the issues associated with implementing affective computing in CRM systems and draw the 'concept' map of this research field from 2023 to 2026. The research was carried out by using 61 peer-reviewed publications collected from the Scopus database and carried out by Systematic Literature Review (SLR) and Bibliometric analysis. To identify publication trends, thematic clusters and knowledge structures, bibliometric techniques such as keyword co-occurrence analysis and bibliographic coupling were used. The findings reveal four major research themes: (1) multimodal emotion recognition and technical architectures, (2) CRM integration, customer engagement, and personalization, (3) ethical governance, privacy, and responsible artificial intelligence, and (4) emerging technologies, including Large Language Models (LLMs) and Generative AI. The review also reveals that four theories are dominate this research domain: Technology Acceptance Model (TAM), Privacy Calculus Theory (PCT), Explainable Artificial Intelligence (XAI) and Trust Theory. One of the conclusions was the continued duality of technical and ethics that needs to be addressed in order to make technology a bit more transparent, to protect the privacy user, to be fair, and build trust. This study adds value by offering the first comprehensive Biblio-Metric mapping of Affective Computing implementation challenges in CRM in from 2023 to 2026, and provides practical insights for researchers, CRM practitioners and decision makers in building emotion-aware CRM systems trustworthy, explainable, and privacy-preserving.

Affective computing, Customer relationship management (CRM), Multimodal emotion recognition

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