基于因素的供应链协同预测方法

T. Shu, Shou Chen, Shouyang Wang, K. Lai
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引用次数: 2

摘要

本文提出了基于因素的供应链协同预测方法,并进行了相关实证研究。结合以往实际销售数据,对春运、停工检修、小修等因素进行不同层次、不同领域的提取和量化。同时,在企业的销售预测中进行了回归。实证研究表明,因素在供应链销售预测中起着重要作用。它们的应用大大提高了具体预测和一般预测的精度,体现了协同预测的思想。它们可以促进供应链内涵和突出的信息应用;它们有助于积极利用供应链企业潜在的负面约束;它们可以作为一个信息整体,为供应链的管理做出贡献。这些都可以看作是经济信息过滤器在不同层次和模块中的扩展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Supply chain collaborative forecasting methods on the basis of factors
This paper proposes the supply chain collaborative forecasting methods on the basis of factors and presents the relevant empirical studies. In the light of the past actual sales data, factors of Spring Festival transportation, shutting down for examinations and repairs and minor repairs are extracted and quantified in different hierarchies and domains. At the same time, they are reverted in the corporate sales forecasting. The empirical studies indicate that factors play an important part in supply chain sales forecasting. Their application can greatly improve the specific and general forecasting accuracy and represents the thought of collaborative forecasting. They can contribute to the supply chain implication and prominent information application; they can contribute to positively employing the potential negative constraints of supply chain enterprises; they can contribute to the management of supply chain as the information whole. All these can be considered as an extension of the economic information filter in different hierarchies and modules.
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