Back in Business: Operations Research in Support of Big Data Analytics for Operations and Supply Chain Management
Document Type
Article
Publication Date
11-2018
Abstract
Few topics have generated more discourse in recent years than big data analytics. Given their knowledge of analytical and mathematical methods, operations research (OR) scholars would seem well poised to take a lead role in this discussion. Unfortunately, some have suggested there is a misalignment between the work of OR scholars and the needs of practicing managers, especially those in the field of operations and supply chain management where data-driven decision-making is a key component of most job descriptions. In this paper, we attempt to address this misalignment. We examine both applied and scholarly applications of OR-based big data analytical tools and techniques within an operations and supply chain management context to highlight their future potential in this domain. This paper contributes by providing suggestions for scholars, educators, and practitioners that aid to illustrate how OR can be instrumental in solving big data analytics problems in support of operations and supply chain management.
DOI
10.1007/s10479-016-2226-0
Source Publication
Annals of Operations Research
Recommended Citation
Hazen, B.T., Skipper, J.B., Boone, C.A. et al. Back in business: operations research in support of big data analytics for operations and supply chain management. Ann Oper Res 270, 201–211 (2018). https://doi.org/10.1007/s10479-016-2226-0
Comments
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