A System Dynamics Framework for Data-Driven ESG Risk Mitigation in Service-Oriented Real Estate Portfolios

Abstract

The integration of Environmental, Social, and Governance (ESG) considerations has become a critical managerial challenge for commercial property portfolios operating under increasing regulatory, climate, and market uncertainty. From a service science perspective, ESG risk mitigation can be understood as a complex service system that links data, governance, investment decisions, and stakeholder interactions. This study develops a data-driven framework for evaluating ESG risk mitigation strategies in commercial real estate portfolios, combining quantitative risk assessment, system dynamics simulation, and comparative analysis across four global cities—London, New York, Singapore, and Hong Kong. Using portfolio-level data from 2020–2025, the analysis introduces a dynamic ESG Risk Mitigation Index (ESG-RMI) to capture non-linear relationships between ESG investment intensity, financial performance, and risk reduction. The results show that portfolios with integrated ESG strategies experience significantly lower insurance losses, faster recovery from shocks, and higher asset valuations, with an optimal ESG investment intensity of approximately 40% of medium-term capital expenditure. However, the effectiveness of ESG risk mitigation varies substantially across regulatory and governance contexts, highlighting the importance of adaptive, service-oriented management approaches. This study contributes to the literature by reframing ESG risk mitigation as a data-enabled service system and by providing a decision-support framework that helps portfolio managers transition from compliance-driven ESG practices to value-creating and resilient service strategies.