Analysing sustainability-orientated determinants of green HRM: a hybrid SEM-ANN modelling approach

Purpose This study aims to explore how sustainability factors, drawn from the Resource-Based View (RBV), stakeholder and institutional theory, influence the adoption of Green Human Resource Management (GHRM) and their mediating effect on improving Corporate Sustainable Performance (CSP) in Indian manufacturing firms. Design/methodology/approach The study uses a hybrid Structural Equation Modelling (SEM)-Artificial Neural Networks (ANN) model to examine both linear and non-linear relationships, using data from 279 managers across 37 ISO 14001-certified companies in Kerala gathered through a cross-sectional survey. SEM tested the hypotheses, whereas ANN focused on identifying the key predictors. Findings This study identifies stakeholder pressure (SP), green transformational leadership (GTL), green intellectual capital (GIC) and corporate social responsibility (CSR) as key determinants of GHRM. GHRM enhances CSP and fully mediates the relationship between each determinant and CSP. ANN analysis showed that SP and GTL were the most influential factors. Research limitations/implications The findings suggest that managers in Indian manufacturing companies certified with ISO 14001 should focus on SP and GTL, as these are the key drivers of GHRM adoption. Originality/value This study uniquely combines SEM and ANN methodologies to identify and rank the factors affecting GHRM adoption in India’s manufacturing sector. SEM confirms the significance and direction of impacts, while ANN quantifies their relative importance, enabling prioritisation of SP, GTL, GIC and CSR beyond traditional linear analysis. Integrating RBV, stakeholder theory and institutional theory into a validated model, it presents a comprehensive framework for understanding GHRM adoption and its influence on CSP.