Big Data Analytics Driven Supply Chain Transformation

Mondher Feki ()
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Mondher Feki: LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - IEMN-IAE Nantes - Institut d'Économie et de Management de Nantes - Institut d'Administration des Entreprises - Nantes - UN - Université de Nantes

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Abstract: Big data has emerged as the new frontier in supply chain management; however, few firms know how to embrace big data and capitalize on its value. The non-stop production of massive amounts of data on various digital platforms has prompted academics and practitioners to focus on the data economy. Companies must rethink how to harness big data and take full advantage of its possibilities. Big data analytics can help them in giving valuable insights. This chapter provides an overview of big data analytics use in the supply chain field and underlines its potential role in the supply chain transformation. The results show that big data analytics techniques can be categorized into three types: descriptive, predictive, and prescriptive. These techniques influence supply chain processes and create business value. This study sets out future research directions.

Keywords: E-business; Business sciences (search for similar items in EconPapers)
Date: 2019
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Published in Business Transformations in the Era of Digitalization, IGI Global, pp.106-124, 2019, Advances in E-Business Research, ⟨10.4018/978-1-5225-7262-6.ch007⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04465723

DOI: 10.4018/978-1-5225-7262-6.ch007

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