BIG DATA IN SUPPLY CHAIN MANAGEMENT: AN EXPLORATORY STUDY

Gheorghe Militaru, Massimo Pollifroni and Alexandra Ioanid
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Gheorghe Militaru: Politehnica University of Bucharest, Romania
Alexandra Ioanid: Politehnica University of Bucharest, Romania

Network Intelligence Studies, 2015, issue 6, 103-108

Abstract: The objective of this paper is to set a framework for examining the conditions under which the big data can create long-term profitability through developing dynamic operations and digital supply networks in supply chain. We investigate the extent to which big data analytics has the power to change the competitive landscape of industries that could offer operational, strategic and competitive advantages. This paper is based upon a qualitative study of the convergence of predictive analytics and big data in the field of supply chain management. Our findings indicate a need for manufacturers to introduce analytics tools, real-time data, and more flexible production techniques to improve their productivity in line with the new business model. By gathering and analysing vast volumes of data, analytics tools help companies to resource allocation and capital spends more effectively based on risk assessment. Finally, implications and directions for future research are discussed.

Keywords: big data; supply chain; competitive advantage (search for similar items in EconPapers)
JEL-codes: C55 M19 O20 (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:cmj:networ:y:2015:i:5:p:103-108

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