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Performance measurement of a manufacturing company using fuzzy analytical network process

机译:使用模糊分析网络过程的制造公司绩效评估

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摘要

Performance measurement (PM) is a combination of characteristics of a company that are numerically expressed. The aim of the PM is to provide a feedback about success of current activities and provide insight about future performance. Performance of a company depends on its vision and goals, so the definition of performance can vary within time. While the PM literature provides various models for PM, the most accepted model is balanced scorecard (BSC). BSC supplies four inter-related perspectives that the companies can define indicators for performance. These perspectives are: financial, internal business processes, customer and finally learning and growth perspectives. In this study, PM is transformed to a multi attribute decision making (MADM) problem and a performance measurement model based on fuzzy analytical network process (FANP) is proposed. The performance measurement criteria are built with respect to four perspectives of BSC. The proposed model utilises FANP in order to determine the relative importance of perspectives and indicators. The performance scores for each indicator are determined based on the predefined goals. A numerical example, representing performance measurement for two periods, is given for a manufacturing company.
机译:绩效评估(PM)是数字表示的公司特征的组合。 PM的目的是提供有关当前活动成功的反馈,并提供有关未来绩效的见解。公司的绩效取决于其愿景和目标,因此绩效的定义会随时间变化。虽然PM文献为PM提供了各种模型,但最被接受的模型是平衡计分卡(BSC)。 BSC提供了四个相互关联的观点,公司可以定义绩效指标。这些观点包括:财务,内部业务流程,客户以及最终的学习和增长观点。在这项研究中,将PM转换为多属性决策(MADM)问题,并提出了一种基于模糊分析网络过程(FANP)的绩效评估模型。绩效评估标准是针对BSC的四个方面建立的。所提出的模型利用FANP来确定观点和指标的相对重要性。根据预定义的目标确定每个指标的绩效得分。对于一家制造公司,给出了一个代表两个时期的绩效评估的数值示例。

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