Big data analytics in supply chain and logistics: an empirical approach
The International Journal of Logistics Management
ISSN: 0957-4093
Article publication date: 14 May 2018
Abstract
Purpose
The purpose of this paper is to recognise the current state of big data analytics (BDA) on different organisational and supply chain management (SCM) levels in Brazilian firms. Specifically, the paper focuses on understanding BDA awareness in Brazilian firms and proposes a framework to analyse firms’ maturity in implementing BDA projects in logistics/SCM.
Design/methodology/approach
A survey on SCM levels of 1,000 firms was conducted via questionnaires. Of the 272 questionnaires received, 155 were considered valid, representing a 15.5 per cent response rate.
Findings
The knowledge of Brazilian firms regarding BDA, the difficulties and barriers to BDA project adoption, and the relationship between supply chain levels and BDA knowledge were identified. A framework was proposed for the adoption of BDA projects in SCM.
Research limitations/implications
This study does not offer external validity due to restrictions for the generalisation of the results even in the Brazilian context, which stems from the conducted sampling. Future studies should improve the comprehension in this research field and focus on the impact of big data on supply chains or networks in emerging world regions, such as Latin America.
Practical implications
This paper provides insights for practitioners to develop activities involving big data and SCM, and proposes functional and consistent guidance through the BDA-SCM triangle framework as an additional tool in the implementation of BDA projects in the SCM context.
Originality/value
This study is the first to analyse BDA on different organisational and SCM levels in emerging countries, offering instrumentalisation for BDA-SCM projects.
Keywords
Citation
Queiroz, M.M. and Telles, R. (2018), "Big data analytics in supply chain and logistics: an empirical approach", The International Journal of Logistics Management, Vol. 29 No. 2, pp. 767-783. https://doi.org/10.1108/IJLM-05-2017-0116
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited