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PURPOSE: This study aims to examine the antecedents and consequences of organizational resilience in healthcare organizations. Drawing on dynamic capabilities theory (DCT), the study investigates how sensing, seizing and reconfiguring capabilities influence organizational resilience, operationalized through adaptability and agility and how these resilience dimensions contribute to environmental, social and governance (ESG) performance in healthcare organizations. DESIGN/METHODOLOGY/APPROACH: A cross-sectional quantitative research design was employed using survey data collected from 558 healthcare professionals working in primary, secondary and tertiary healthcare organizations in India. Confirmatory factor analysis (CFA) was conducted to assess the reliability and validity of the measurement model, followed by structural equation modeling (SEM) to test the hypothesized relationships and the moderating role of digital transformation. FINDINGS: The findings demonstrate that sensing, seizing and reconfiguring capabilities positively influence both adaptability and agility. The results further show that adaptability and agility significantly enhance ESG performance across ESG dimensions. In addition, digital transformation strengthens the relationship between reconfiguring capability and organizational agility. The study confirms that organizational resilience functions as a capability-based process that supports sustainable performance outcomes in healthcare organizations. ORIGINALITY/VALUE: This study contributes to the organizational resilience literature by empirically validating resilience as a capability-based process within healthcare organizations. It extends existing research by linking organizational resilience with ESG performance and by examining the moderating role of digital transformation in strengthening resilience capabilities. The study also advances the application of DCT in healthcare by providing a theoretically grounded framework for understanding how healthcare organizations build resilience under conditions of uncertainty and disruption.
Mishra et al. (Fri,) studied this question.