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

IF 7.4 3区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Journal of Enterprise Information Management Pub Date : 2023-07-04 DOI:10.1108/jeim-08-2022-0282

Mohammed Ali, Aniekan Essien

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引用次数: 0

Abstract

PurposeThe 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/approachThe authors applied existing theoretical foundations for theory building based on semi-structured interviews with 15 SC and logistics managers.FindingsThe 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/implicationsOutside 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/valueThe 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.

查看原文本刊更多论文

大数据分析如何改善英国零售业的出站物流?定性研究

目的本研究的目的是从英国出境物流运营的角度探讨大数据分析（BDA）作为一种潜在的信息技术创新如何促进零售物流供应链。作者的目标是更好地了解BDA如何通过使用技术、组织和环境模型来整合SC和物流网络。设计/方法论/方法基于对15名供应链和物流经理的半结构化访谈，作者将现有的理论基础应用于理论构建。发现在技术、组织和环境问题中，BDA在出境零售物流中的预期效益最强，其次是最高管理层支持（TMS）。提出了在零售物流中采用BDA的框架。先前文献中的上下文概念有助于我们理解环境变化如何影响BDA决策，例如：（i）SC成熟度水平和连通性影响BDA的利用，（ii）连通SC改善数据可访问性和信息交换，（iii）BDA的好处也会影响采用，（iv）将复杂的任务外包给专家，使公司能够专注于核心业务，而不是投资于IT基础设施。研究局限性/含义除了列出的关键发现之外，这项研究表明，在所有组织环境中都不存在一刀切的方法。拟议的框架表明，BDA的感知利益是不可转移的，需要最高管理层的支持才能成功实施。独创性/价值现有文献侧重于在供应链和物流中应用BDA的方法，但未能深入探讨零售出境物流活动。这项研究探讨了“如何”，并提出了一个技术赋能主题的社会包容性框架。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Enterprise Information Management Multiple-

CiteScore

14.80

自引率

6.20%

发文量

期刊介绍： The Journal of Enterprise Information Management (JEIM) is a significant contributor to the normative literature, offering both conceptual and practical insights supported by innovative discoveries that enrich the existing body of knowledge. Within its pages, JEIM presents research findings sourced from globally renowned experts. These contributions encompass scholarly examinations of cutting-edge theories and practices originating from leading research institutions. Additionally, the journal features inputs from senior business executives and consultants, who share their insights gleaned from specific enterprise case studies. Through these reports, readers benefit from a comparative analysis of different environmental contexts, facilitating valuable learning experiences. JEIM's distinctive blend of theoretical analysis and practical application fosters comprehensive discussions on commercial discoveries. This approach enhances the audience's comprehension of contemporary, applied, and rigorous information management practices, which extend across entire enterprises and their intricate supply chains.