Blockchain technology for sustainable supply chains: a network cluster analysis and future research propositions

• Published in: Environmental science and pollution research international Vol. 30; no. 24; pp. 64779 - 64799
• Main Authors: Yadav, Nidhi, Luthra, Sunil, Garg, Dixit
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2023; Springer Nature B.V
• Subjects: Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; bibliometric analysis; Bibliometrics; Blockchain; Cluster Analysis; Cryptography; Databases, Factual; domain; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental Health; Environmental science; Humans; Literature reviews; Network analysis; researchers; Review; Review Article; supply chain; supply chain management; Supply chain sustainability; Supply chains; Sustainability; Technology; Waste Water Technology; Water Management; Water Pollution Control; Cluster analysis; Blockchain technology (BCT); Sustainable supply chain (SSC); Future research directions; Research propositions; Network analysis
• ISSN: 1614-7499; 0944-1344; 1614-7499
• DOI: 10.1007/s11356-023-27049-3

Achieving the sustainable goals of the United Nations requires improving supply chain sustainability (SSC). Blockchain technology (BCT) has attracted attention on a global level with the ability to transform supply chain management and sustainability efforts. Recognizing this, this study investigates how BCT plays a role in SSC. The current study looks into the importance of BCT in order to move supply networks towards sustainability by performing bibliometric analysis, and network cluster analysis. Through the literature review, the current literature was analyzed and future research directions were concluded. We begin our study by selecting 297 papers on the relevant subjects by applying various filters to the Web of Science (WoS) database. Influential individuals, journals, and organizations in this field were identified using bibliometric analysis. A network analysis was performed to identify influential co-author, and keywords, and for page rank, and cluster analysis. The network analysis was revealed ten distinct study clusters, and ten propositions were suggested from the analysis of these clusters. Additionally, a conceptual framework for the research was proposed, which can advise managers, practitioners, and researcher communities on the key trends and topics in this emerging research domain. Furthermore, to guide research scholars in this field, 33 future research directions were suggested.