State-of-the-art perspectives on data-driven sustainable supply chain: A bibliometric and network analysis approach

Abstract

In today's competitive world, gathering precise context knowledge is a critical barrier for industry practitioners, professionals, and researchers in supply chain management, impeding their capacity to acquire expertise and give effective management awareness. In this regard, this study aimed to identify the data-driven capabilities of supply chain management. Realising the abovementioned issues, the existing literature on supply chain management needs to be further reviewed to explore the data-driven capabilities for sustainable supply chains. The study presented a systematic literature review on a data-driven sustainable supply chain to achieve this goal. One hundred ninety-seven documents from various publications were identified for bibliometric and network analysis from the Scopus database using specific keywords related to the research concept published during 2013–2023 through inclusion and exclusion criteria. The emerging themes were identified using the “R” package and reviewed the papers were reviewed in theme directions. The study showed that implementing data-driven and sustainable technologies could assist strategic decision-making. Also, Data-driven solutions can effectively improve sustainability in supply chain network operations performance. The study demonstrates that big data can contribute to achieving sustainability goals through bibliometric analysis and critique of previous papers published in the specialised field.