Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice

By Deepak Arunachalam, Niraj Kumar, John Paul Kawalek. Transportation Research Part E: Logistics and Transportation Review, 2017

465 citations recorded by the source corpus.

In the era of Big Data, many organisations have successfully leveraged Big Data Analytics (BDA) capabilities to improve their performance. However, past literature on BDA have put limited focus on understanding the capabilities required to extract value from big data. In this context, this paper aims to provide a systematic literature review of BDA capabilities in supply chain and develop the capabilities maturity model. The paper presents the bibliometric and thematic analysis of research papers from 2008 to 2016. This paper contributes in theorizing BDA capabilities in context of supply chain, and provides future direction of research in this field.

Subfields: Management Information Systems, Management of Technology and Innovation, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/709228f4b89e5f4a24137b75a6d325f5e342f8bf

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In Management Information Systems

1. Ming-Dung Fu
2. Miying Yang
3. Zihan Zhang

Citations in the corpus

• The adoption of digital technologies in supply chains: Drivers, process and impact (2021, background): “Manufacturing firms are putting more focus on how to use supply chain data to predict market demand, provide predictive maintenance and optimise production and logistics (Arunachalam et al., 2018).”