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Performance Evaluation of An Apparel Retailer's Stores by Using Stochastic Imprecise DEA

机译:基于随机不精确DEA的服装零售商店铺绩效评估

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In today's competitive environment evaluating firms' performance is an important issue not only for investors and creditors but also for the stores of the firms to increase their efficiencies and take place in the sector. Determining the competitiveness of the firms and evaluating the financial performance of them is also crucial for the sector's development and this depends on their stores' performances.The aim of this study is developing a data envelopment analysis model to evaluate the performance of the stores of a well-known apparel retailer in Turkey. In conventional data envelopment analysis models, a performance measure whether as an input or output usually has to be known. However, in some cases, the type of a performance measure is not clear and we may not decide on whether the criteria is input or output which is called flexible measure. In addition to this, we believe that future planning is more important than past evaluation, so that we present a stochastic imprecise DEA model (SIDEA) that incorporates future planning with flexible measures. To document the practicality of this proposed model SIDEA, it is applied on a well-known apparel retailer in Turkey and get insights on the performance of the stores of this retailer.
机译:在当今竞争激烈的环境中,评估公司的业绩不仅是投资者和债权人的重要问题,而且对于提高公司效率并在行业中发挥作用的公司商店而言,也是一个重要问题。确定企业的竞争力并评估其财务绩效对于该行业的发展也至关重要,这取决于其商店的绩效。本研究的目的是建立一个数据包络分析模型来评估一家商店的绩效。土耳其的知名服装零售商。在传统的数据包络分析模型中,通常必须知道性能指标是输入还是输出。但是,在某些情况下,绩效指标的类型尚不清楚,我们可能无法决定标准是输入还是输出,这称为弹性指标。除此之外,我们认为未来的计划比过去的评估更为重要,因此我们提出了一种随机的不精确DEA模型(SIDEA),该模型将未来的计划与灵活的措施结合在一起。为了证明此提议的模型SIDEA的实用性,将其应用于土耳其的知名服装零售商,并获得了对该零售商商店业绩的见解。

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