Data-driven digital transformation for supply chain carbon neutrality: Insights from cross-sector supply chain

Abstract

Following the growing pressure on firms and supply chains regarding their environmental impact, carbon neutrality of supply chains is gaining substantial attention among scholars and practitioners. Data-driven digital transformation supports supply chains in achieving higher carbon reduction while improving efficiency and economic performance. However, the conditions under which data-driven digital transformation can provide the desired effect remain unclear due to a lack of empirical evidence. This study aims to address this gap by examining how data-driven digital transformation, enabled by data analytics capabilities, contributes to establishing a win-win situation between carbon and economic performance in the face of several sources of carbon uncertainty through fostering supply chain carbon transparency. Drawing upon the organizational information-processing theory, we posit that the fit between information needs to reduce carbon uncertainties and the information capabilities provided by data-driven digital transformation is critical for enhancing supply chain carbon transparency and balancing supply chains' economic and carbon performance. We examine these relationships using regression tests based on survey data from 437 manufacturing companies from different regions (i.e., Europe, Africa, and Asia). Our results reveal that data analytics capabilities alone cannot enhance supply chain carbon transparency until integrated into a comprehensive business transformation. In that case, carbon transparency would positively mediate overcoming carbon uncertainties and improve the supply chains' carbon and economic performance.