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Advanced predictive-analysis-based decision support for collaborative logistics networks

机译:基于高级预测分析的协作物流网络决策支持

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摘要

Purpose – The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution. Design/methodology/approach – The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments. Findings – Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes. Practical implications – The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept. Originality/value – The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.
机译:目的–本文的目的是研究异构业务网络中大数据的挑战和潜力,并将其与已实施的物流解决方案相关联。设计/方法/方法–本文概述了大数据领域当前重要的挑战和机遇,特别是在异构企业网络的透明度和流程的背景下。在此背景下,本文介绍了如何将现有组件和目标驱动型研究相结合,以在全国范围内针对卡车数量少于货物的网络中实施的解决方案。结果–除了提供对当今大数据情况的扩展概述之外,研究结果还表明,当今可用的技术手段和方法可以在大型异构网络中构成可行的流程透明性解决方案,该网络中存在遗留做法,报告滞后和不完整的数据,但是流程对政策调整不足敏感。实际意义–发现本文介绍的方法对于提高流程效率,透明度和物流网络的计划具有实用价值。提出的解决方案中的特定系统设计选择允许资源处理实践的逐步引入或发展,将经验丰富的人员的现有零碎的,非结构化的或默认的知识合并到理论上建立的总体概念中。原创性/价值–本文扩展了以前对大数据潜力的高级观点,并提出了物流应用中的新应用研究和开发成果。

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