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物流园区服务范围确定方法 被引量:8

Determining method of service scope for logistics park
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摘要 考虑了多个物流园区的竞争关系以及客户对物流园区的选择需求,分析了现有方法解决物流园区服务范围问题的不足,提出了融合断裂点模型和哈夫概率模型的物流园区服务范围的分步确定方法。以DEMATEL方法为基础,运用改进的断裂点模型,分析和遴选出对物流园区服务范围影响程度大的关键因素,并获得初始空间服务范围。运用改进后的哈夫概率模型,确定了合理阈值,并修正了初始空间服务范围。分析结果表明:对物流园区服务范围影响程度较大的因素分别为政府对物流业的扶持程度、客户物流需求量、区域经济发展水平、物流园区规模、客户服务水平;运用该方法,物流园区的单位面积营业额和物流强度分别为10.25×104元.km-2和8.39×104 t.km.km-2,均大于传统方法的指标值10.18×104元.km-2和8.28×104 t.km.km-2。可见,本文提出的方法有效。 Competition relationships among several logistics parks and the selection demand of customer on a certain logistics park were considered. The lack of present method solving the service scope problem of logistics park was analyzed. The step-divided determining method fused with breaking point model and Huff probability model was presented for service scope of logistics park. On the basis of DEMATEL method, the improved breaking point model was utilized to analyze and choose the key factors with high influence on the service scope of logistics park, and initial space service scope was obtained. By using the improved Huff probability model, rational threshold values were identified, and initial space service scope was modified. Analysis result shows that the key factors with high influence on the service scope of logistics park are government supporting to logistics industry, logistics demand of customer, region economy, scale of logistics park and service level of customer respe method, the per unit area turnover and logistics strength of logistics park are 10. and 8.39 × 10^4 t · km· km^-2 respectively, while the values are 10. 18 × 10^4 t · km· km^-2 by using traditional method. So the determining 5 tabs, 2 figs, 12 refs. development level of ctively. By using the P.5 × 10^4 t · km· km^-2 yuan km^-2 and method is effective.
出处 《交通运输工程学报》 EI CSCD 北大核心 2011年第6期82-88,共7页 Journal of Traffic and Transportation Engineering
基金 国家自然科学基金项目(50978115) 吉林省科技发展计划项目(20080526) 中央高校基本科研业务费专项资金项目(2009JC046)
关键词 物流园区 服务范围 断裂点模型 哈夫概率模型 DEMATEL方法 回归分析 logistics park service scope breaking point model Huff probability model
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