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Measuring logistics performance of OECD countries via fuzzy linear regression

机译:通过模糊线性回归测量经合组织国家的物流绩效

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摘要

In logistics, performance measurement has been considered as a key competency to acquire world class performance. In light of this, we presented a robust methodology to establish an analysis framework for measuring logistics performance. The proposed hybrid methodology is a combination of criteria importance through intercritera correlation (CRITIC), simple additive weighting (SAW), and Peters' fuzzy regression methods. To the best of our knowledge, country-based logistics performance is seldom studied in the literature. Therefore, we measured the logistics performance of Organization for Economic Cooperation and Development (OECD) countries using the devised model based on the data of Logistics Performance Index 2014 provided by the World Bank. The introduced methodology, which is suitable to model imprecise relationships among system parameters, appears to be a practical alternative approach for the assessment of logistics performance. It should be noted that the evaluation framework presented in this paper is not confined to performance measurement case and can also be exploited in addressing other multiple criteria decision-making problems incorporating uncertainty.
机译:在物流中,绩效衡量被认为是获得世界级绩效的关键能力。鉴于此,我们提出了一种强大的方法来建立测量物流效果的分析框架。所提出的混合方法是通过Intercritera相关性(评论家),简单的添加剂加权(SAW)和PETERS的模糊回归方法的标准重要性的组合。据我们所知,在文献中,基于国家的物流绩效很少研究。因此,我们根据世界银行提供的物流绩效指数2014年数据的数据,衡量了经济合作与发展组织(经合组织)国家的后勤绩效。介绍的方法,适合在系统参数之间模拟不精确的关系,似乎是对物流绩效评估的实用替代方法。应当注意,本文提出的评估框架不限于性能测量案例,也可以利用解决不确定性的其他多标准决策问题。

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