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How can big data analytics improve outbound logistics in the UK retail sector? A qualitative study

    Research output: Contribution to journalArticle (Academic Journal)peer-review

    18 Citations (Scopus)

    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.
    Original languageEnglish
    Pages (from-to)424-449
    Number of pages26
    JournalJournal of Enterprise Information Management
    Volume38
    Issue number2
    Early online date4 Jul 2023
    DOIs
    Publication statusPublished - 25 Feb 2025

    Bibliographical note

    Publisher Copyright:
    © 2023, Emerald Publishing Limited.

    Keywords

    • Big data analytics
    • Outbound logistics
    • Retail supply chain management
    • Supply chain analytics
    • TOE framework

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