SUPPLY CHAIN MANAGEMENT AND A STUDY ON SUPPLIER SELECTION in TURKEY

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1 SUPPLY CHAIN MANAGEMENT AND A STUDY ON SUPPLIER SELECTION in TURKEY Pelin Alcan, Hüseyin Başlıgil, Melih Coşkun Yildiz Technical University, Besiktas, İstanbul, Turkey Abstract This study mainly focuses on supplier selection problem and also supply chain management in developing countries. The application is implied to choose the best thread supplier for a textile firm and multi criteria decision making methods, fuzzy AHP and VIKOR, are used to solve the problem. The reason of using fuzzy logic is to get realistic results which are more related to real environment. Keywords: Supply chain management, supplier selection, multi criteria decision making, fuzzy AHP, VIKOR 1. Introduction In today's world, Supply Chain Management is becoming more and more important for companies. Suppliers that have critical roles in supply chain are crucial for companies in order to reach their goals. Due to this reason, companies have to be cautious when determining the best supplier. The supplier selection problem is a multi criteria decision making problem which includes quantitive or qualitative criteria that could conflict with each other. In their paper, Shemshadi et al.(2011) treat supplier selection as a group multiple criteria decision making (GMCDM) problem and obtain decision makers opinions in the form of linguistic terms.kılınccı and Önal (2011) investigate a supplier selection problem of a wellknown washing machine company in Turkey and use a fuzzy analytic hierarchy process based methodology is used to select the best supplier firm providing the most customer satisfaction for the criteria determined.the main objective of Lee s study (2009) is to propose an analytical approach to select suppliers under a fuzzy environment.a fuzzy analytic hierarchy process (FAHP) model, which incorporates the benefits, opportunities, costs and risks (BOCR) concept, is constructed to evaluate various aspects of suppliers.in the paper of Roshandel et al., (2013), four suppliers of imported raw material Tripolyphosphate (TPP) (primary material to produce the detergent powder with a case study in Iran) are evaluated based on 25 effective criteria using the hierarchical fuzzy TOPSIS (HFTOPSIS) approach.önüt et al. (2009) develop a supplier evaluation approach based on the analytic network process (ANP) and the technique for order performance by similarity to ideal solution (TOPSIS) methods to help a telecommunication company in the GSM sector in Turkey under the fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterized by triangular fuzzy numbers.on the other hand, Rogers and Tibben-Lembke (2001) discussreverse logistics activities and key reverse logistics management methodologiesas well as their benefits and the barriers to successful implementation. This article is applied to choose the best thread supplier for a textile firm and multi criteria decision making methods, fuzzy AHP and VIKOR, are used to solve the problem. The Criteria which are quality, price, delivery, flexibility and service, are determined by the decision makers based on literature reviews. Depending on these criteria, decision makers evaluate four supplier alternatives.

2 The paper is organized as follows: In Section 2, Supply Chain Management (SCM) and Transport Systems in Developing Countries are explained. Fuzzy Analytic hierarchy process (FAHP) and VIKOR are detailed in Section 3. Application is presented in Section 4.Conclusion is summarized in Section Supply Chain Management (SCM) and Transport Systems in Developing Countries Supply chain management has increasingly attracted attention as a systematic approach to integrate the supply chain in order to planning and controlling the materials and information from suppliers to customers. One of the most important issues in supply chain management is selection of the appropriate supplier which has significant effect on purchasing cost decrease and increase in the organization s competition ability (Roshandel et al., 2013). Traditional supply chains in developing countries typically involve many players, and are tightly linked with long-standing social structures.as developing countries enter into World Trade Organization arrangements their agricultural industries will be subject to increasing competition in their domestic markets, and have greater incentives to meet global standards in export markets. SCM provides one approach to planning the improvements needed in the management of their agricultural production and marketing systems to meet future challenges (Johnson and Hofman, 2004). SCM is a holistic approach that moves past the level of the individual manager or business to address all the processes from the initial assembly of raw materials to the final retail processes that provide the customer with access to the product. In that sense, it is a systems approach (Beers et al. 1999) Logistics Costs and Economic Development Transport systems are closely related to socio-economic changes.there is a relationship between the level of development as well as the composition of a national economy and the logistics costs. While logistics costs can amount to 25% of delivered costs in some developing economies, they can go as low as 8 to 9% in advanced economies. Many factors can influence this cost structure [http://people.hofstra.edu/geotrans/eng/ch5en/conc5en/logisticsecodev.html]: Transportation infrastructures. Influences transport costs, capacity and reliability. Interest rates. Mostly impact transactional and inventory carrying costs. Level of competition. Monopolistic and oligopolistic markets tend to have higher logistics costs as stakeholders have less incentives to innovate and use infrastructure (e.g. ports) from a rent seeking perspective. Telecommunication infrastructures. Reduce transactional and inventory management costs. Legal system. Enforcement of contracts and protection of private property (e.g. terminals, warehouses). Regulations and taxation. The level of constraints the transport sector is subject to, such as environmental regulations, as well as its taxation level.

3 Figure 1. Supply Chain Management: New Directions for Developing Economies [http://people.hofstra.edu/geotrans/eng/ch5en/conc5en/logisticsecodev.html] 2.2. Logistics in Turkey Logistics overall is a young sector in Turkey which has made progress in recent years. Turkey, being advantageously positioned between the Middle East and Europe, serves as a transfer centre between these regions. Many authorities claim it will become a logistics base; some assert it already serves this role.the Turkish logistics market has experienced a 20% growth rate during the last five years and is forecast to increase to US$ 120 bn by 2015.In Turkey, privatisation in the transportation & logistics industry is a key trend driving on-going discussions. [http://www.pwc.com/en_gx/gx/transportation-logistics/tl2030/emergingmarkets/pdf/tl2030_vol3_final.pdf] 3. Fuzzy Analytic hierarchy process (FAHP) and VIKOR 3.1. Fuzzy Analytic hierarchy process (FAHP) AHP was intended by Saaty (1980, 1994). It is a useful approach to solve complex decision problems and methodologies. The Analytic Hierarchy Process (AHP) is a theory of measurement through pairwise comparisons and relies on the judgements of experts to derive priority scales (Saaty, 2008).Buckley (1985) incorporated the fuzzy theory into the AHP, called the FAHP. It generalizes the calculation of the consistent ratio (CR) into a fuzzy matrix. The procedure of FAHP for determining the evaluation weights are explained as follows (Rostamy et al., 2012): Step 1: Construct fuzzy pair-wise comparison matrices.

4 Fig. 2. Membership functions of the linguistics variables for criteria comparisons (Rostamy et al., 2012) Step 2: Examine the consistency of the fuzzy pair-wise comparison matrices. 1 a12... a1 n 1/ a a2n A / a1 n 1/ a2n... 1 Step 3: Compute the fuzzy geometric mean for each criterion. 1/ r ( ) n i ai ai ain Step 4: Compute the fuzzy weights by normalization. w r ( r r... r ) i i 1 2 n Step 5: Performance evaluation of the alternatives. BNP [( U L ) ( M L )]/ 3 L w w w w w w i i i i i i VIKOR The VIKOR method was developed to solve multiple criteria decision making (MCDM) problems with conflicting and non-commensurable criteria assuming that compromising is acceptable to resolve conflicts (Shemshadi et al., 2011).Vlsekriterijumska Optimizacija I Kompromisno Resenje (i.e. VIKOR) method was developed by Opricovic in 1998 for multi-criteria optimization of complex systems (Opricovic, 1998 and Opricovic and Tzeng, 2002).The steps of the VIKOR approach are given in the following: 1) Determining of the best and the worst values of allcriterion functions. Accepting that th criterion function represents a benefit; 2) For each alternative, and values are calculated. Here, value represents the weight of the criteria. 3) Calculate the values for, which are definedas; ( ) ( ) 4) In this step, the results of, and values are ordered. 5)In according to the obtained result, two conditions must be provided. These conditions can be expressed as follows; Condition 1- Acceptable advantage: The best and closest maxim isthe most distinct difference between getting that proof that the condition. Condition 2- Acceptable stability: Alternative must also be the best ranked by or/and.

5 4. Application In this paper, the application is implied to choose the best thread supplier for a textile firm and multi criteria decision making methods, fuzzy AHP and VIKOR, are used to solve the problem. Also, supplier site selection has been donein Denizli in Turkey. Hierarchy schema is showed as below; Figure 2. Hierarchy schema The Criteria which are quality, price, delivery, flexibility and service, are determined by the decision makers based on literature reviews. Criteria weights has been investigated with the help of Fuzzy AHP. Table 1. fuzzy importance scale PAIRED COMPARISON IMPORTANCE RATING CONJUGATE IMPORTANCE RATING Equivalently important (1,1,1) (1,1,1) Intermediate value (1,2,3) (1/3,1/2,1) More important (2,3,4) (1/4,1/3,1/2) Intermediate value (3,4,5) (1/5,1/4,1/3) Significantly important (4,5,6) (1/6,1/5,1/4) Intermediate value (5,6,7) (1/7,1/6,1/5) Very strong important (6,7,8) (1/8,1/7,1/6) Intermediate value (7,8,9) (1/9,1/8,1/7) Extremely important (8,9,9) (1/9,1/9,1/8) Fuzzy pairwise comparisons are found based on fuzzy importance scale as Table 2; Table 2. Fuzzy pairwise comparisons quality price delivery flexibility service quality (1,1,1) (2,3,4) (4,5,6) (6,7,8) (2,3,4) price (1/4,1/3,1/2) (1,1,1) (2,3,4) (4,5,6) (1,2,3) delivery (1/6,1/5,1/4) (1/4,1/3,1/2) (1,1,1) (1,2,3) (1,2,3) flexibility (1/8,1/7,1/6) (1/6,1/5,1/4) (1/3,1/2,1) (1,1,1) (1,1,1) service (1/4,1/3,1/2) (1/3,1/2,1) (1/3,1/2,1) (1,1,1) (1,1,1) Laterly, consistency rate analysis and defuzzification process are established. Geometric means of each lines are calculated with the help of normalized pairwise comparisons matrix. Hereby, priority vector is obtained as below;

6 0,466 0,239 V 0,122 0,068 0,101 Following this process, weighted matrix is achieved, , 466 2, 572 0, , 239 1, 309 0, 203 0, * 0,122 0, 638 0,144 0, 203 0, , 068 0, 352 0, 347 0, 556 0, ,101 0, 531 Consistency index is calculated with CI ( max n) / (n1) formula. After all of the processes are applied to the application as Section 3, final table is obtained as Table 3; Table 3. Final table Alternatives Q j S j R j Q j S j R j A1 1 0,7152 0, A2 0,1963 0,3831 0, A3 0 0,3666 0, A4 0,8361 0,6009 0, Results The results show that A3 is the best supplier of this appliacation. So, the facility principally has to work with this supplier. Also, the reason of using fuzzy logic is to get realistic results which are more related to real environment. Besides, in Turkey, privatisation in the transportation and logistics industry is a key trend driving on going some arguments. Following a package of legislative reforms, the legal system for international road transport is now stable with the EU policy.. Literature Beers, G., Beulens, A. and van Dalen, J., 1999, Chain science as an emerging discipline. In: Proceedings of the Third International Conference on Chain Management in Agribusiness and the Food Industry, Wageningen Agricultural University, The Netherlands. Johnson G.I. and HofmanP.J., 2004, Agriproduct Supply-Chain Management in Developing Countries, Australian Centre for International Agricultural Research Canberra. Kılınçcı Ö. and Önal S.A., 2011, Fuzzy AHP Approach for Supplier Selection in a Washing Machine Company, Expert Systems with Applications, 38, 8, Lee, A., 2009, A Fuzzy Supplier Selection Model with The Consideration of Benefits, Opportunities, Costs and Risks, Expert Systems with Applications, 36, 2, Opricovic, S., 1998, Multi-criteria optimization of civil engineering systems. Belgrade: Faculty of Civil Engineering.

7 Opricovic S., Tzeng G-H., 2002, Multicriteria planning of post-earthquake sustainable reconstruction Computer-Aided Civil and Infrastructure Engineering, 17, 3, Rogers, D.S. and Tibben-Lembke, R.S., 2001, An Examination of Reverse Logistics Practices, Journal of Business Logistics, 22, 2, Roshandel, J., Miri-Nargesi, S.S., and Hatami-Shirkouhi, L., 2013, Evaluating and Selecting The Supplier in Detergant Production Industry Using Hierarchical Fuzzy TOPSIS, Applied Mathematical Modelling, 37, 24, Rostamy A.A.A., Shaverdi M., Amiri B. and Takanlou F.B., 2012, Using fuzzy analytical hierarchy process to evaluate main dimensions of business process reengineering, Journal of Applied Operational Research, 4, 2, Saaty T.L., 2008, Decision making with the analytic hierarchy process, Int. J. Services Sciences, 1, 1. Shemshadi A., Shirazi, H., Toreihi, M., ve Tarokh, M.J., 2011, "A Fuzzy VIKOR Method for Supplier Selection Based on Entropy Measure for Objective Weighting", Expert Systems with Applications, Vol.30 No.10, ss Önüt, S., Kara, S.S., and Işık, E., 2009, Long Term Supplier Selection Using a Combined Fuzzy MCDM Approach: A Case Study for a Telecommunication Company, Expert Systems with Applications, 36, 2, [http://people.hofstra.edu/geotrans/eng/ch5en/conc5en/logisticsecodev.html] [http://www.pwc.com/en_gx/gx/transportation-logistics/tl2030/emerging markets/pdf/tl2030_vol3_final.pdf]

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