Big Data and Knowledge Capabilities Driving CSR Performance in Manufacturing

Abstract

In today's data‐driven business environment, organizations increasingly rely on digital capabilities to achieve sustainable performance. Grounded in the Dynamic Capabilities View (DCV), this study examines the effects of big data analytics capability (BDAC) and organizational resources (OR) on corporate social responsibility (CSR) performance, while investigating the mediating roles of green innovation (GI) and absorptive capacity (AC). It also explores the moderating effect of green corporate image (GCI) on the relationships between organizational capabilities and CSR performance. Data were collected from 305 managers in manufacturing firms in Pakistan. A multi‐method approach integrating Partial Least Squares Structural Equation Modeling (PLS‐SEM), Artificial Neural Networks (ANN), Necessary Condition Analysis (NCA), and Combined Importance–Performance Map Analysis (cIPMA) was employed to provide comprehensive insights into the proposed model. The findings reveal that BDAC and OR significantly enhance CSR performance, both directly and indirectly through GI and AC. Furthermore, GCI positively moderates the relationships between OR and CSR performance, as well as between BDAC and CSR performance. ANN identifies BDAC as the most influential predictor of CSR performance, whereas NCA and cIPMA highlight the critical capability thresholds and managerial priorities for improving sustainability outcomes. This study extends the DCV by demonstrating how organizational capabilities and knowledge‐based mechanisms jointly improve CSR performance under varying levels of GCI. The findings offer practical guidance for managers seeking to leverage data‐driven capabilities to achieve sustainable business performance.