INDUSTRY 4.0 TECHNOLOGIES STUDY IN SUPPLY CHAIN OPERATION MANAGEMENT-A BIBLIOMETRIC ANALYSIS PERSPECTIVE

Abstract

This study aims to review the significant works by previous authors toward Industry 4.0 (I4.0) in the form of contributing countries, universities, authors, subject areas, journals, and citations. The study adopted a bibliometric analysis methodology to conduct a systematic literature review to investigate the concept of I4.0. After refining the extracted results, a number of 224 papers retrieved from Scopus database from 2011 to 2023 (12 February) were considered for further analysis with selected keywords including Industry 4.0 (I4.0), artificial intelligence (AI), digital transformation (DT), Internet of Things (IoT), Radio Frequency Identification (RFID), Machine Learning (ML), automation, and operation management (OM). The applied filters were (date range; document type; subject area; language, and Source). The retrieved articles were analyzed by using VOSViewer keywords co-occurrences clustering to address study questions. VOSViewer clustering analysis results revealed several significant themes in the area of I4.0. Created clusters include Cluster 1: industry 4.0, supply chain management, and operation management; Cluster 2: industry 4.0 and supply chain management; Cluster 3: industry 4.0 and operation management; Cluster 4: artificial intelligence and operation management; Cluster 5: industry 4.0 and sustainable development and Cluster 6: industry 4.0 and industrial revolution. To the best of my knowledge, this study is one of the few attempts to investigate I4.0. from 2011 to 2023 (February 12) in which future researchers and policy-makers could benefit from study findings. Moreover, future studies may investigate the results of this study empirically to support cluster analysis findings.