配送中心选址的主客观结合——以纯电动摩托车销售为例

Sofia Fitri Ramadani, G. W. Bhawika, I. Baihaqi
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引用次数: 0

摘要

确定配送中心的位置是公司实现销售最大化和成本最小化的战略决策。选址决策是长期的投资决策。当市场上对产品的需求增加而分配不平衡时,会造成高运输成本。因此,它要求公司做出调整,其中之一是开放的位置设施。产品在市场中的特点决定了区位的选择。决策不能用一个标准来解决,而是要用多种标准来解决,包括主观标准和客观标准。本文以纯电动摩托车配送中心为例,利用Brown-Gibson模型建立了主客观因素相结合的配送中心选址模型。利用运输模型对客观因子权重进行处理,得到运输成本最低的备选地点。进一步实现了从工厂到市场的单位数量配置。主观因素权重处理使用层次分析法(AHP)通过识别,验证标准,和问卷调查。此外,还进行了敏感性分析,以确定这两个因素对确定配送中心选址的影响程度。模型结果表明,与初始定位相比,该模型的定位精度降低了29.4%。本文的研究结果对电动汽车企业未来制定战略和选址决策标准,提高分销绩效的有效性和效率具有重要的参考价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Objective and Subjective Integration in Distribution Center Location Selection: A Case Study of Battery- electric Motorcycle Sales
Determining the distribution center location is a strategic decision for the company to maximize sales and minimize cost. Location decisions are long-term investment decisions. When the demand for products on the market increases but the distribution unbalanced, it can cause high transportation costs. Therefore, it requires the company to make adjustments, one of them by opening the location facility. Product characteristics in the market determine the location selection. The decision can not resolve by one criterion but many criteria, including subjective and objective measures. By using a case study of the distribution center of a battery-electric motorcycle, this paper offers a model for determining distribution location by integrating objective and subjective factors using the Brown-Gibson model. The objective factor weight is processed using a transportation model to obtain an alternative site with the lowest transportation cost. Furthermore, the number of unit allocation from the factory to the market achieved. The subjective factor weight processed using the Analytical Hierarchy Process (AHP) through identifications, verification of criteria, and questionnaires. Besides, the sensitivity analysis carried out to determine how much to influence the two factors to have on determining the distribution center location selection. The model results show that compared to the initial location, the proposed model decreased by 29.4%. The results of this study could be very beneficial for electric vehicle companies to determine the strategy and location decision criteria in the future to enhance effectiveness and efficiency in distribution performance.
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