Measuring the effectiveness of suppliers performance by using data envelopment analysis and an industrial application
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2013
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Advisor: Yrd. Doç. Dr. Çiğdem Sofyalıoğlu
Abstract (EN)
In an age of intensive competiveness circumstances firms find themselves obliged to increase efficiency, decrease costs, follow up the changing needs of customers and meet the demands of customers fast. In realizing this, supply chain has to be managed effectively. As well as the prior, a performance based Supply Chain Management (SCM) is required. The suppliers providing raw materials in production processes have become important components of SCM. All of the activities of the firms have been influenced by suppliers? performances. In such regard, an assessment of suppliers? selection and performance evaluation becomes an important element.The study can be summarized in two parts. The first section covers a general background on SCM and performance measurement followed by a discussion of several methods utilized in the measurement of performance of suppliers. It?s proposed to use AHP (Analytic Hierarchy Process) used in multi-criteria decision making process and DEA (Data Envelopment Analysis) providing performance measurement when there are many inputs and outputs in common.The study, in the second section, deals with the selection and evaluation process of a firm working in white goods industry. The important supplier selection criteria for the firm are determined by using AHP. It?s concluded that quality, delivery, price, production facilities and capacity, technical capability, procedural compliance, operating controls and performance history are important criteria for the firm. According to the criteria, the performances of the firm?s important suppliers have been measured with DEA. It?s determined that 35% of the firms? suppliers have effective performance. For the inefficient suppliers essential improvement suggestions are made.
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Didem Tezsürücü
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Didem Tezsürücü (Doctorate thesis). Measuring the effectiveness of suppliers performance by using data envelopment analysis and an industrial application, 2013, Manisa Celal Bayar University.
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