Evaluating the efficiency of the supply chain using fuzzy data envelopment analysis and balanced scorecard model

Number of pages: 107 File Format: Not Specified File Code: 29541
Year: Not Specified University Degree: Not Specified Category: Industrial Engineering
Tags/Keywords: Industries
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  • Summary of Evaluating the efficiency of the supply chain using fuzzy data envelopment analysis and balanced scorecard model

    Dissertation

    Master's degree

    Field: Industrial Engineering – Industries

    Summer 2013

    Abstract

     

    Supply chain is a collection of suppliers, manufacturers, distributors and customers that shows the logical relationship between them. Performance evaluation plays an important role in supply chain management. performs Data envelopment analysis [1] is also a non-parametric method based on linear programming that measures the performance of different decision-making units. This method can have multiple inputs and outputs. To evaluate the performance of the supply chain, different criteria can be considered. The balanced scorecard of your indicators into four financial perspectives; processes; The customer and the learning and development of human resources have developed and seek to create a balance between financial goals as a result of past performance (retrospective indicators) and three other indicators (prospective indicators). In this research, an integrated model of fuzzy data coverage analysis and balanced scorecard has been presented, based on which the inputs and outputs have been extracted from the balanced scorecard. Performance evaluation is also done by fuzzy data envelopment analysis model. Finally, the application of the mentioned model for supply chains in one of the country's industries has been investigated and implemented. Persian keywords: supply chain, performance evaluation, balanced scorecard, fuzzy data envelopment analysis, linear programming, uncertainty Chapter 1: Introduction and generalities of the research 1.1 Introduction

    In recent years, supply chain management[1]  Due to the increasing competition in global markets, it has become one of the most important fields in the field of production management. Supply chain management, as a tool that was created in the early 1990s and includes planning and management of operations and production, transfer and distribution of goods until they reach the customer, offers a way to improve the production environment and make it competitive. A supply chain is a set of facilities, suppliers, customers, products and methods of inventory control, sales and distribution that connects suppliers to customers and starts with the production of raw materials by suppliers and ends with the consumption of the product by customers (Gonaskaran et al., 2001). Because the supply chain plays an important role in the production management process, the performance evaluation of the supply chain is considered as an important element of the company's (organization's) performance. Performance evaluation is defined as a quantification process or, more precisely, a quantification process and analysis of effectiveness and efficiency. Based on this, supply chain efficiency is defined as a measure of the performance of the company's resources in the entire context of the supply chain to achieve its specific goals. The issues of evaluating the performance of the supply chain cover a wide range from evaluating the performance of independent units of a supply chain to evaluating the overall performance. It includes the supply chain. The problem of evaluating the performance of the supply chain is one of the most comprehensive strategic decision-making problems that must be considered for the long-term efficiency of the entire supply chain. 2.1 Statement of the problem Supply chain management is a set of approaches that try to It effectively integrates suppliers, manufacturers, warehouses, and consumers so that goods are produced and distributed in the right quantity, at the right place, and at the right time. These approaches seek to minimize system costs while satisfying a certain level of service (Beeman, 1999). It has been proven that the effective management of a supply chain is a very effective mechanism for fast and reliable delivery of high quality goods and services at a minimal cost (Gunaskaran et al., 2004). Previously, marketing, distribution, planning, production and sales units operated in an independent supply chain.Correspondingly, evaluating the performance of a supply chain means evaluating the performance of marketing, distribution, planning, production and sales units independently. In the past, some researchers evaluated the performance of independent units of a supply chain, such as performance evaluation of distribution centers (DC [2]) (Ross [3] and Drogue [4], 2002), sales performance evaluation (Easton [5] et al., 2002), supplier performance evaluation (Toleria [6] et al., 2006) and so on. However, these independent units in the supply chain have their own goals, and these goals often conflict with each other. Therefore, the need for a performance evaluation framework in which the performance of these independent units are integrated and evaluated simultaneously is felt. To achieve an efficient supply chain, it is very important to evaluate the performance of the entire supply chain. In this dissertation, the supply chain is viewed as a whole and considered as a system. In this thesis, a three-level supply chain including supplier, manufacturer and customer is considered and this chain is evaluated as a decision-making unit at the producer level.

    To evaluate the supply chain, various indicators are used such as cost, time, profit, service level and so on. are measured. Supply chain evaluation is done using different methods. Data envelopment analysis as a non-parametric method is based on linear programming technique and measures the performance of different units in proportion. Wang [7] and Wang (2007) believe that data envelopment analysis is a suitable method for supply chain management by giving appropriate evidence and reasons. Data coverage analysis can have multiple inputs and outputs and use quantitative and qualitative indicators (Wen et al., 2010). In this thesis, indicators such as cost, delivery On time and procurement time[8] is considered to evaluate the performance of the supply chain and  Performance evaluation is done at the producer level, while the supply chain is usually looked at as a system and holistically; This means that the performance evaluation indicators are measured for the producer unit (the second level of the chain) and in relation to the supplier and the customer, and the whole supply chain is maintained. The supply chain includes various techniques from simple weighted scoring methods to complex mathematical programming and from deterministic evaluation models to models under conditions of uncertainty. Recently, various methods have been proposed to deal with the problem of supply chain performance evaluation. 16 categories of these methods were reviewed by Stamp [9] and colleagues (2010). These methods include activity-based costing, balanced scorecard, supply chain operational reference model, logistics research framework, log audit[10], EFQM, etc. The results of this research are presented in Appendix (P).

    To evaluate the performance of the supply chain, various indicators are provided in categories such as cost, time, profit, service level, and so on. are measured. Thomas [11] and Griffin [12] (1996) considered the cost of transportation equal to more than half of the costs of a supply chain. and used it for evaluation. Lee[13] and Bellington[14] (1992) considered the level of customer satisfaction to be an important factor in companies that have customers from all over the world. And they have pointed out that if the adopted strategies are not aimed at satisfying the customers, they will be very expensive. Mapes[15] and colleagues (1997) considered the level of production to be a very important factor in production cost, quality and flexibility. and have pointed out that the performance of production processes as an important part of a supply chain must be measured and improved. Most of the existing studies on the evaluation of supply chain performance are based on the framework of the evaluation index system.

  • Contents & References of Evaluating the efficiency of the supply chain using fuzzy data envelopment analysis and balanced scorecard model

    Chapter One: Introduction to Research Advocacy. 1

    1.1 Introduction. 2

    2.1 statement of the problem. 2

    3.1 Background and necessity of conducting research. 4

    4.1 Research assumptions. 6

    5.1 Research objectives. 6

    Chapter Two: Research literature. 8

    1.2 Introduction. 9

    2.2 supply chain management. 9

    1.2.2 Supply chain performance evaluation process. 12

    2.2.2 data coverage analysis 12

    3.2 Definition of performance and set of production possibilities. 13

    1.3.2 Input-oriented and output-oriented model 20

    2.3.2 Advantages and disadvantages of data coverage analysis 20

    3.3.2 Balanced scoring card model. 22

    4.3.2 The general concept of balanced scorecard. 23

    5.3.2 Introduction of balance points card funds. 25

    4.2 Background of the research. 28

    1.4.2 Supply chain performance evaluation criteria. 33

    1.1.4.2 Chen evaluation indicators. 33

    2.1.4.2 Research indicators of Gunaskaran et al. 40

    The third chapter: research method. 43

    1.3 Charnes, Cooper and Rhodes model. 44

    2.3 fuzzy data envelope analysis model. 45

    1.2.3 Fuzzy linear systems. 45

    3.3 Research methodology. 51

    1.3.3 BSC-FDEA hybrid model. 52

    Chapter four: calculations and research findings. 56

    1.4 Description of the problem. 57

    2.4 extraction of indicators 58

    1.2.4 statistical population. 58

    2.2.4 statistical sample. 59

    3.2.4 Questionnaire design. 60

    3.4 Evaluation indicators. 65

    4.4 Problem data. 66

    5.4 fuzzy data envelope analysis model. 68

    4. 6 results of fuzzy data envelopment analysis model. 69

    4.7 Sensitivity analysis. 71

    Chapter five: conclusions and suggestions. 74

    1.5 Introduction. 75

    2.5 Results. 75

    3.5 discussion. 78

    4.5 Practical research suggestions. 80

    5.5 Research limitations. 81

    6.5 Future Offers. 81

    Appendix. 83

    Appendix A: Chen evaluation indicators. 84

    Appendix B: The framework provided by Gunaskaran et al. for evaluation criteria 87

    Appendix P: Supply chain efficiency evaluation models and their specifications 88

    Appendix T: Shepherd and Gunter evaluation indicators. 93

    Resources 99

Evaluating the efficiency of the supply chain using fuzzy data envelopment analysis and balanced scorecard model