A systematic literature review with bibliometric analysis of big data analytics adoption from period 2014 to 2018. Issue 1 (31st March 2020)

• Record Type: Journal Article
• Authors: Inamdar, Zeeshan; Raut, Rakesh; Narwane, Vaibhav S.; Gardas, Bhaskar; Narkhede, Balkrishna; Sagnak, Muhittin
• Is Part Of: Journal of enterprise information management. Volume 34:Issue 1(2021)
• Page Start: 101
• Page End: 139
• Publication Date: 2020-03-31
• Subjects: Big-data analytics (BDA) -- Supply chain management -- Systematic literature review (SLR) -- Bibliometric analysis (BA) -- Adoption -- Sustainable supply chain management; Management information systems -- Periodicals; Business logistics -- Periodicals; Business -- Data processing -- Periodicals; Management -- Data processing -- Periodicals; 658.05
• DOI: 10.1108/JEIM-09-2019-0267
• Languages: English
• ISSNs: 1741-0398

Abstract

Abstract : Purpose: The volume of data being generated by various sectors in recent years has increased exponentially. Consequently, professionals struggle to process essential data in the current competitive world. The purpose of the study is to explore and provide insights into the Big Data Analytics (BDA) studies in different sectors. Design/methodology/approach: This study performs a systematic literature review (SLR) with bibliometric analysis of BDA adoption (BDAA) in the supply chain and its applications in various sectors from 2014 to 2018. This paper focuses on BDAA studies have been carried out across different countries and sectors. Also, the paper explores different tools and techniques used in BDAA studies. Findings: The benefits of adopting BDA, coupled with a lack of adequate research in the field, have motivated this study. This literature review categorizes paper into seven main areas and found that most of the studies were carried out in manufacturing and service. Practical implications: This research insight and observations can provide practitioners and academia with guidance on implementing BDA in different sustainable supply chain sectors. The article indicates a few remarkable gaps in the future direction and trends regarding the integration of BDA and sustainable supply chain development. Originality/value: The study derives a new categorization of BDA, which investigates how data is generated, organized, captured, interpreted and evaluated to give valuable insights to manage the sustainable supply chain.