Big data analytics for supply chain management: A literature review and research agenda

The main objective of this study is to provide a literature review of big data analytics for supply chain management. A review of articles related to the topics was done within SCOPUS, the largest abstract and citation database of peer-reviewed literature. Our search found 17 articles. The distribution of articles per year of publication, subject area, and affiliation, as well as a summary of each paper are presented. We conclude by highlighting future research directions where the deployment of big data analytics is likely to transform supply chain management practices

The impact of big data on world-class sustainable manufacturing

Big data (BD) has attracted increasing attention from both academics and practitioners. This paper aims at illustrating the role of big data analytics in supporting world-class sustainable manufacturing (WCSM). Using an extensive literature review to identify different factors that enable the achievement of WCSM through BD and 405 usable responses from senior managers gathered through social networking sites (SNS), we propose a conceptual framework using constructs obtained using reduction of gathered data that summarizes this role; test this framework using data which is heterogeneous, diverse, voluminous, and possess high velocity; and highlight the importance for academia and practice. Finally, we conclude our research findings and further outlined future research directions