The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study

Bernhard Roßmann, Angelo Canzaniello, Heiko von der Gracht and Evi Hartmann

Technological Forecasting and Social Change, 2018, vol. 130, issue C, 135-149

Abstract: The continuously growing amount of available data has accelerated the emergence of numerous business intelligence applications that are summarized under the term Big Data Analytics (BDA). BDA is especially relevant to the domain of Supply Chain Management (SCM) as it provides the tools to support decision-making in increasingly global, volatile and dynamic value networks. However, its application challenges traditional institutional arrangements as well as roles that are related to the management of data. The underlying empirical study addresses this challenge with the application of a multi-method approach that is embedded in Organizational Information Processing Theory (OIPT). A Delphi survey was conducted to integrate expert assessments of projections up to the year 2035 and fuzzy c-means clustering was applied to identify future scenarios that span the future of BDA in SCM. The study suggests that BDA will improve demand forecasts, reduce safety stocks and improve the management of supplier performance. However, supply chain (SC) processes will become increasingly automated and traditional tasks of SCM will be partially substituted as a result. Consequently, the transition of the traditional role of SCM within organizations will increase the importance of human intuition, trust and strategic decision-making.

Keywords: Big Data Analytics; Supply Chain Management; Organizational Information Processing Theory; Delphi method; Fuzzy logic (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (60)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:130:y:2018:i:c:p:135-149

DOI: 10.1016/j.techfore.2017.10.005

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