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A Conceptual Approach for Optimizing Distribution Logistics using Big Data

机译：大数据优化物流配送的概念方法

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Big data analytics creates new opportunities and potentials in the field of supply chain management (SCM). Specifically, linking inter-firm supply chain processes of two entities such as freight forwarder and final customer were identified as relevant areas for performance improvements. Automatic analysis of data from sources such as mobile equipment, sensor networks, and geospatial devices can significantly improve accuracy of SCM transportation processes; thus contributing to supply chain performance by minimizing delivery attempts, and ensures higher customer satisfaction, as deliveries are carried out when customers are able to receive them. Therefore, we develop a distribution concept targeted at realization of this potential. We chose the online shopping domain for our concept, as current research provides evidence that delivery of goods acquired in online stores often causes multiple delivery attempts, and many firms struggle with providing good service to the customers. Finally, we discuss limitations, implications and possibilities for future research.
机译：大数据分析在供应链管理（SCM）领域创造了新的机会和潜力。具体来说，将两个实体（例如货运代理人和最终客户）的公司间供应链过程联系起来是确定绩效改进的相关领域。自动分析来自移动设备，传感器网络和地理空间设备等来源的数据，可以显着提高SCM运输过程的准确性;因此，通过最大程度地减少交付尝试，有助于提高供应链的绩效，并确保更高的客户满意度，因为在客户能够收到订单时便进行了交付。因此，我们开发了一种旨在实现这种潜力的分销概念。我们选择了在线购物领域作为我们的概念，因为当前的研究提供了证据，表明在在线商店中购买商品的交付通常会导致多次交付尝试，并且许多公司都在努力为客户提供优质服务。最后，我们讨论了未来研究的局限性，影响和可能性。

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