Role of bigdata analytics in improving drivers of omni-channel retailing for improving logistics experience

IF 4.5 Q1 MANAGEMENT

Benchmarking-An International Journal Pub Date : 2023-10-11 DOI:10.1108/bij-03-2023-0166

Ruchi Mishra, Hemlata Gangwar, Saumyaranjan Sahoo

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引用次数: 0

Abstract

Purpose The objective of this research is to evaluate and rank the factors influencing omnichannel (OC) logistics, while also investigating the significant impact of big data analytics in improving these drivers of OC logistics. Design/methodology/approach Using exploratory sequential mixed method design, an in-person interview survey was conducted to identify and stratifies the enablers of OC retailing. These interviews were supplemented with a case study in an apparel firm to prioritise the enablers of OC logistics. Further, a survey was conducted to understand the role of big data analytics in improving drivers of OC logistics as well as the role of Individual capability and organisational capability in big data usage for omnichannel retailing. Findings Findings represent that information management is the most important driver followed by inventory management and network design for improving OC logistics. Further, significant relationship between big data analytics and drivers of omnichannel logistics has been reported. Practical implications This study identifies and classifies the drivers of OC retailing relating to their level of criticality in OC logistics which will assists practitioners to prioritise their tasks for the successful development of OC logistics. The study will also help practitioners to use BDA for developing the drivers of OC. Originality/value The study substantiates and adds to the BDA literature by emphasising the positive role of BDA in development of OC driver and highlighting the significant role of drivers of BDA in its usage.

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大数据分析在提升全渠道零售驱动、提升物流体验中的作用

本研究的目的是评估和排序影响全渠道(OC)物流的因素，同时也调查大数据分析在改善OC物流这些驱动因素方面的重大影响。设计/方法/方法采用探索性顺序混合方法设计，进行了一次面对面的访谈调查，以识别和分层OC零售的推动因素。这些访谈辅以对一家服装公司的案例研究，以优先考虑OC物流的促成因素。此外，我们还进行了一项调查，以了解大数据分析在改善OC物流驱动因素方面的作用，以及个人能力和组织能力在全渠道零售大数据使用中的作用。研究结果表明，信息管理是改善OC物流最重要的驱动因素，其次是库存管理和网络设计。此外，大数据分析与全渠道物流驱动因素之间的重要关系已被报道。本研究确定并分类了与OC物流关键程度相关的OC零售驱动因素，这将有助于从业者优先考虑OC物流成功发展的任务。本研究亦有助从业员运用BDA来发展强迫症的驱动因素。独创性/价值本研究通过强调BDA在OC驱动程序发展中的积极作用以及BDA驱动程序在其使用中的重要作用来充实和补充BDA文献。

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

Benchmarking-An International Journal MANAGEMENT-

CiteScore

10.40

自引率

16.10%

发文量

154

期刊介绍： Benchmarking is big news for companies committed to total quality programmes. Its enthusiastic reception by many prominent business figures has created high levels of interest in a technique which promises big rewards for co-operating partners. Yet, like total quality itself, it must be understood in its proper context, and implemented single mindedly if it is to be effective - this journal helps companies to decide if benchmarking is right for them, and shows them how to go about it successfully.