Work

Extrapolating CSR–HRM interdependencies and employee well-being for sustainable workplaces in generative AI era

Year: 2026

Type: article

Abstract: The development of generative AI (GAI) capabilities has led corporate entities to rethink their strategic initiatives towards sustainable workforce management. This dynamism has been broadly identified as a concern for managerial teams. Despite strong consensus on the roles of organizational human resources and corporate governance in managing the deployment of GAI mechanisms, specific factors contributing to each orientation remain unidentified. The current study addresses this gap by conducting a comprehensive review of factors that may affect sustainability orientation and employee well-being in the context of GAI implementation. The study utilized total interpretive structural modeling (TISM) and cross-impact matrix multiplication applied to the classification (MICMAC) method to develop the hierarchical relationship model. The study identified 16 factors: nine attributed to human resource management (HRM) and seven to the corporate social responsibility (CSR) domain. The study develops an expert-informed structural representation of the interrelationships between the two categories of designated factors. The outcomes identify two foundational factors as independent drivers and one dependent factor related to the social assessment of technology from a CSR perspective. The findings provide a structured interpretation of the interdependence between HRM and CSR factors and their implications for sustainable workforce management and employee health in SMEs. The study offers novel managerial implications on the relative orientations of driving and dependency factors for managing a sustainable workforce while supporting new technology development in the SME context.

Source: Discover Sustainability

DOI: 10.1007/s43621-026-04810-5

Authors: Rajat Subhra Chatterjee, Ranjan Chaudhuri, Katarina Zvarikova, Demetris Vrontis, Iza Gigauri, Sheshadri Chatterjee