Digital Innovation, Data Analytics, and Supply Chain Resiliency: A Bibliometric-based Systematic Literature Review

• Published in: Annals of operations research Vol. 333; no. 2-3; pp. 825 - 848
• Main Authors: Iftikhar, Anas, Ali, Imran, Arslan, Ahmad, Tarba, Shlomo
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2024; Springer Nature B.V
• Subjects: Bibliometrics; Business and Management; Clusters; Combinatorics; Data analysis; Innovations; Literature reviews; Mathematical analysis; Operations Research/Decision Theory; Original Research; Reliability analysis; Resilience; Supply chains; Theory of Computation; Digital innovation; Data analytics; Digital technology; Bibliometrics; Supply chain resilience
• ISSN: 0254-5330; 1572-9338
• DOI: 10.1007/s10479-022-04765-6

In recent times, the literature has seen considerable growth in research at the intersection of digital innovation, data analytics, and supply chain resilience. While the number of studies on the topic has been burgeoning, due to the absence of a comprehensive literature review, it remains unclear what aspects of the subject have already been investigated and what are the avenues for impactful future research. Integrating bibliometric analysis with a systematic review approach, this paper offers the review of 262 articles at the nexus of innovative technologies, data analytics, and supply chain resiliency. The analysis uncovers the critical research clusters, the evolution of research over time, knowledge trajectories and methodological development in the area. Our thorough analysis enriches contemporary knowledge on the subject by consolidating the dispersed literature on the significance of innovative technologies, data analytics and supply chain resilience thereby recognizing major research clusters or domains and fruitful paths for future research. The review also helps improve practitioners’ awareness of the recent research on the topic by recapping key findings of a large amount of literature in one place.