Saber Shiripour; Ameneh Adib
Abstract
Supply chain is a network consists of several parts and their inter-relationships. To achieve continuous improvement in supply chain, it is necessary to continually evaluate supply chain performance. One of the important points in evaluating the performance, identify weaknesses subunits, considering ...
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Supply chain is a network consists of several parts and their inter-relationships. To achieve continuous improvement in supply chain, it is necessary to continually evaluate supply chain performance. One of the important points in evaluating the performance, identify weaknesses subunits, considering the relations between the units in system management and balance between the sectors. In this paper, Network Data Envelopment Analysis technique is used for performance evaluation. Identification of inefficient units in the supply chain and improve their performance is of utmost importance. Since the supply chain is made up of different units, improving several unit is impossible. So, setting priorities is necessary to improve the unit. In addition, the selection of Pattern units is important to get an idea on how to improve inefficient units. So, in this work, using Fuzzy Data, a systematic method is defined for benchmarking supply chain, which in addition to evaluating the performance of the entire supply chain and determine efficient and inefficient decision making units, the efficiency of each of the parts of the supply chain is also calculated. This method is used for performance evaluation of the supply chains of Polyethylene pipes and so the communications and the processes of internal wards of their supply chain is reviewed. In the end, using benchmarking technique, improvement priorities are determined for different levels of the supply chain.
M.R. Mehregan; M. Rahmani
Volume 1, Issue 3 , January 2003, , Pages 1-30
Abstract
The paper investigates excesses and deficits in Iranian industrial productivity for the years by combining data envelopment analysis with other management science approaches such as analytical hierarchy process. The application also identifies factors that affect the productivity of Iranian industry ...
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The paper investigates excesses and deficits in Iranian industrial productivity for the years by combining data envelopment analysis with other management science approaches such as analytical hierarchy process. The application also identifies factors that affect the productivity of Iranian industry in a positive or negative way i.e., simultaneously identifies both excesses and deficits. The current study demonstrates that DEA can be combined with other methods to yield more valid results insights and recommendations such as : 1- the trend of Iranian industrial productivity in this 21 year period demonstrates some periods of fall and rise that is due to the conditions of the time 2- in the main factors of productivity we see some continuous trends of weakness; this means that it is necessary to think about this point in the strategic plans for industrial development plans can be set and corrections and revisions can be made.
