Toward socially-aware Personal Comfort Models: Integrating group dynamics into building thermal management systems

This review examines the role of social dynamics in shaping thermal comfort within shared indoor environments, with attention to psychological processes that underlie interpersonal interactions and group influence. While traditional thermal comfort research has emphasized physical and individual psychological factors—such as temperature, age, and personality— this paper extends the discussion to consider how peer dynamics may interact with individual thermal sensitivity and adaptive behaviors. By drawing conceptual parallels with established psychological research on social influence, the review highlights the ways individuals perceive and respond to thermal conditions in shared settings. The paper follows a structured interdisciplinary literature review methodology, including psychology and thermal comfort studies, across major academic databases, ultimately reviewing empirical and theoretical work spanning from 1955 to 2024. Results suggest that social dynamics represent a potentially influential, yet underexplored, dimension of indoor environmental experience, particularly in commercial and academic buildings. Accordingly, a framework for socially-responsive thermal comfort management is proposed, organized around three interconnected pillars: enhancing system intelligence, empowering social interaction, and fostering collective responsibility. The framework addresses limitations in both traditional thermal models and contemporary Personal Comfort Models (PCMs) by including contextual, behavioral, and psychological components shaped by group interactions. The paper also discusses considerations for the integration of the proposed PCM into building management systems, identifying potential challenges and offering directions to support real-time, occupant-centric control and energy-efficient operation. • Traditional comfort models overlook social effects in shared environments • Self-reported comfort data can be biased by social conformity pressures • A framework for socially-aware comfort models is proposed • The model integrates social, psychological, and behavioral factors • Field validation requires interdisciplinary, real-world collaboration