How Can Big Data Analytics Improve Outbound Logistics in The UK Retail Sector? A Qualitative Study

Ali, Mohammed; Essien, Aniekan

Abstract

Purpose – The purpose of this study is to explore how big data analytics (BDA) as a potential information technology (IT) innovation can facilitate the retail logistics supply chain (SC) from the perspective of outbound logistics operations in the United Kingdom. The authors’ goal was to better understand how BDA can be integrated to streamline SCs and logistical networks by using the technology, organisational and environmental model.
Design/methodology/approach – The authors applied existing theoretical foundations for theory building based on semi-structured interviews with 15 SC and logistics managers. Findings – The perceived benefits of using BDA in outbound retail logistics comprised the strongest predictor amongst technological, organisational and environmental issues, followed by top management support (TMS). A framework was proposed for the adoption of BDA in retail logistics. Contextual concepts from previous literature have helped us understand how environmental changes impact BDA decision-making, as such: (i) SC maturity levels and connectivity affect BDA utilisation, (ii) connected SCs improve data accessibility and information exchange, (iii) the benefits of BDAs also affect adoption and (iv) outsourcing complex tasks to
experts allows companies to focus on core businesses instead of investing in IT infrastructure. Research limitations/implications – Outside the key findings listed, this study shows that there is no
one-size-fits-it-all approach for use within all organisational settings. The proposed framework reveals that the perceived benefit of BDA is non-transferrable and requires top-level management support for successful implementation. Originality/value – The existing literature focusses on the approaches to applying BDA in SC and logistics
but fails to present a deep dive into retail outbound logistics activity. This study addresses the “how” and proposes a social-inclusive framework for a technology-enabled topic. Keywords Supply chain analytics, Big data analytics, Outbound logistics, Retail supply chain management, TOE framework

Citation

Ali, M., & Essien, A. (2023). How Can Big Data Analytics Improve Outbound Logistics in The UK Retail Sector? A Qualitative Study. Journal of Enterprise Information Management, https://doi.org/10.1108/JEIM-08-2022-0282

• Journal Article Type: Article
• Acceptance Date: Jul 1, 2023
• Online Publication Date: Jul 2, 2023
• Publication Date: Jul 4, 2023
• Deposit Date: Jul 1, 2023
• Publicly Available Date: Jul 27, 2023
• Journal: Journal of Enterprise Information Management
• Print ISSN: 1741-0398
• Publisher: Emerald
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1108/JEIM-08-2022-0282
• Keywords: Supply chain analytics, Big data analytics, Outbound logistics, Retail supply chain management, TOE framework
• Publisher URL: https://www.emerald.com/insight/content/doi/10.1108/JEIM-08-2022-0282/full/html