Hazır giyim tedarikçilerinin performans değerlendirmesi için bir model önerisi
A model for evaluating the performance of clothing suppliers
- Tez No: 517551
- Danışmanlar: DOÇ. DR. CANAN SARIÇAM
- Tez Türü: Yüksek Lisans
- Konular: Tekstil ve Tekstil Mühendisliği, Textile and Textile Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2018
- Dil: Türkçe
- Üniversite: İstanbul Teknik Üniversitesi
- Enstitü: Fen Bilimleri Enstitüsü
- Ana Bilim Dalı: Tekstil Mühendisliği Ana Bilim Dalı
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 110
Özet
Bu çalışmada tedarikçi seçimi ve performans ölçümü için çok kriterli karar verme ve performans ölçüm yöntemleri kombinasyonundan oluşan bir yöntem önerisi yapılmış ve söz konusu öneri VZAHPTOPSIS olarak isimlendirilerek, gerçek bir vaka üzerinde uygulanarak sonuçların nasıl elde edildiği gösterilmiştir. Çalışmada öncelikle bu üç yöntemin temel ilkeleri ayrı ayrı anlatılmış, sonrasında bu yöntemlerin kullanıldığı literatürden çalışma örnekleri verilerek açıklanmış ve uygulama bölümünde, hazır giyim sektöründe faaliyet göstermekte olan uluslararası bir perakendeci şirketin ana tedarikçilerinin ve ana tedarikçilere bağlı fabrikaların performansları ölçülmüştür. Giriş kısmında sektör ve bu çalışma ile ilgili detaylı ön bilgiler verilmiştir. İkinci bölümde AHP, topsis ve VZA yöntemlerin temel prensipleri, tarihçeleri, avantaj ve dezavantajları hakkında bilgiler verilmiştir. Bu bölümde ayrıca bu yöntemlerin kullanıldığı literatürdeki diğer çalışmalarla ilgili kapsamlı bilgi verilmiştir.“Metot”bölümünde AHP, Topsis ve veri zarflama analizi yöntemlerinin birlikte bu uygulamada nasıl bir araya getirildikleri ve bir araya getirilme aşamaları açıklanmıştır. Uygulama kısmını içeren dördüncü bölümde, seçilen altı hazır giyim tedarikçisi ve bu tedarikçilere bağlı 23 fabrikayı değerlendirmek üzere kalitatif nitelikteki performans kriterleri ve bu kriterlerin öncelikleri AHP yöntemi ile belirlenmiş, elde edilen öncelik değerlerinin ağırlıkları kullanılarak topsis yöntemi ile ana tedarikçilerin bu kriterlerde gösterdikleri performans skorları kantitatif olarak elde edilmiştir. Uygulamanın son adımında, fabrikaların genel performansları, girdi yönelimli VZA yöntemi kullanılarak, ölçeğe göre sabit getiri ve ölçeğe göre değişken getiri yaklaşımlarıyla hesaplanmıştır. Çalışmada VZA yönteminde çıktı parametreleri olarak Ahp / Topsis yöntemleri ile elde edilen performans skorları, perakendeci şirket için üretilen yıllık adet ve üretilen farklı model sayısı kullanılmıştır. Diğer yandan, girdi parametreleri olarak, çalışan sayısı ve yıllık toplam üretim hacmi verileri kullanılmıştır. Hesaplamalar sonucu verimli ve verimsiz üreticiler belirlenmiş ve sonuçlar yorumlanmıştır. Fabrikaların saf teknik etkinlik skorlarının, toplam teknik etkinlik skorlarına göre daha yüksek olduğu görülmüştür. Ayrıca, verimsiz işletmelerin verimli hale gelebilmeleri için girdilerinde negatif yönlü ve yüksek miktarlarda iyileştirmeye gitmeleri gerektiği görülmüştür. Sonuç bölümünde çalışmanın sonuçları genel olarak değerlendirilmiş, yorum ve öneriler yapılmıştır.
Özet (Çeviri)
The selection of the convenient suppliers and the evaluation of them periodically according to their ability to provide a constant and even increasing performance is very important for the textile and apparel value chain. The retailers which takes place at the very end of this value chain should develop and use a customized, understandable, systematic, and quantifiable tool to make the selection and performance evaluation for themselves in an efficient and effective manner. Considering these points, the purpose of this study to present an efficient, systematic and quantifiable tool or model for the supplier selection and performance evaluation and to present the application of this model. Within this respect, a model for supplier selection and performance evaluation, which combines different methods from the multi-criteria decision making and the performance evaluation, was suggested. Referring the methods in combination the model was named as DEAHPTOPSIS and it was applied on a real case to show how the procedures are executed within the application. The steps which followed throughout the study were reported within the thesis and were explained accordingly as below. In the introduction part, a brief information about the apparel retail industry was given with the industry dynamics covering the parameters that have created the highly competitive market environment such as the changing customer trends and the strategies applied by the retailers themselves. The introduction part was concluded with the objective of this study. In the second part, the fundamental principles of the three methods used in the suggested model, which were AHP (Analytical Hierarchy Process), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and DEA (Data Envelopment Analysis) were introduced by giving some information about their historical development, their advantages and the disadvantages. Besides, a broad literature review containing the application of these methods either separately or with each other in the textile and apparel industry for the supplier selection and evaluation was given. Many different examples from literature were summarized but it was realized that there was no study within the literature which used these three methods together. In the third part, the model which combined AHP, TOPSIS and DEA methods was explained with the indication of the purposes of each method within the model. Within this respect, it was explained that AHP method was stated to be used for the determination of the criteria and the calculation of the priority levels of the selected qualitative criteria based on the retail company's strategies. Thus, AHP was used to give quantitative weights for the evaluation criteria of the qualitative type of parameters in the supplier selection. The theory and the mathematical calculation steps of AHP method were given in detail including the calculations and parameters, which were used to check the consistency of the results, the“Consistency Ratio”and the“Consistency Index”. After then, it was stated that TOPSIS method was used for the ranking of the suppliers quantitatively according to the criteria which had been determined and prioritized in AHP. TOPSIS provided a score for each supplier in terms of qualitative type of parameters in supplier selection and evaluation. The theory and the mathematical calculations behind the TOPSIS method was given in detail and the scale used for the evaluation of the suppliers was given with the numerical intervals and verbal expressions. Finally, DEA method and its application purposes were explained. It was stated that DEA was used to compare the suppliers in terms of their performances by using some quantitative inputs and outputs. It was added that the quantitative scores of each supplier in terms of qualitative criteria, which were calculated using with AHP and TOPSIS methods, were taken as an output for the DEA calculation. Then the two versions of DEA which are“input oriented DEA”and“output oriented DEA”and the two different assumptions for DEA, which are CCR (constant return to scale) and BCC (variable return to scale) assumptions, were explained. It was stated that in this study input oriented DEA based on both CCR and BCC assumptions were applied. The efficiency types provided by DEA,“overall technical efficiency”calculated as a result of CCR assumption,“pure technical efficiency”calculated as a result of BCC assumption and“scale efficiency”calculated as the division of the overall technical efficiency scores by pure technical efficiency scores were explained with the calculation of the improvement ratios. Then the formulas of DEA to be used in this study for both constant return to scale (CCR) assumption and variable return to scale (BCC) were given. In the fourth part, the application of the suggested model was shown on the real case. Within this respect, firstly it was stated that the real case was applied on an international retail company, which was based in UK with many stores in UK, Europe and Far East, having liaison offices in different countries. Regarding the company, the historical development, the organizational structure and the ways of working were explained with a brief information about Turkey liaison office, its structure and workflow. The importance of supplier consolidation strategy for the retail company and accordingly the significance of selecting and working with the efficient suppliers were emphasized. Secondly, the details for 6 clothing suppliers and 23 sub-contractors selected for the performance evaluations were given with the explanation of the reason for the selection of these suppliers and sub-contractors. Following the introduction of the retail company and their suppliers, the experts from the company were introduced who put a significant contribution on the evaluation of the priorities and the suppliers. Within this regard, the information about the experts such as their back ground, their positions and their experiences in the company were given. In the following sections of the fourth part, the application of AHP, TOPSIS and DEA methods were given and the results obtained were presented. In the application of the AHP, first of all, the selected qualitative criteria were introduced one by one and the hierarchical structure composed of these criteria were given. It was explained what these criteria mean for the retail company, in what way they were important for the retail company, how they were related with company's strategies and goals. Using AHP method, the priority levels of selected criteria were evaluated using the mathematical calculations of the data taken from the workshop carried out by the group of experts. According to the results, it was found out that“Quality system and certification”was found to be the most important second level sub-criteria for the first level criteria“The characteristics of the supplier”. Whereas“Product price”and“Product quality”were found to be the most important second level sub-criteria for the first level criteria regarding“Product performance criteria”and finally“Timeliness”,“Presenting technical service for the product and production modifications”and“Reliability and accuracy”became the most important second level sub-criteria for the first level criteria“Service performance criteria”. When all the sub-criteria were considered, it was observed that the top three criteria in the supplier selection and evaluation became“Quality system and certification”,“Product price”and“Product quality”. Then the performance score of each supplier, 6 suppliers and 23 sub–contractors, in terms of qualitative criteria was calculated using TOPSIS method in which the evaluations of the experts and the priority weight determined in AHP were used. It was found out that, the performance scores of the suppliers especially the ones, which were assigned higher scores in terms of providing for the AHP criteria, got higher score in TOPSIS also. Finally, the overall performances of sub-contractors were calculated using input oriented DEA models both with constant return to scale (CCR) and variable return to scale (BCC) assumptions. Within the DEA calculations, the output parameters were selected as“Performance scores obtained from AHP/Topsis steps”,“Business volumes of the sub-contractors”and the input parameters were selected as“The number of different styles produced for the retail company”,“The number of employees”and“The total volume produced”. The data for the quantitative type of input and output parameters were taken from the records of the supplier and retailer within the time period between February 2016 and February 2017. As a result of DEA calculations, the efficient and inefficient sub-contractors were determined and the overall results were given. It was observed that 3 sub-contractors were efficient in terms of the overall technical efficiency, 8 sub-contractors were efficient in terms of the pure technical efficiency and 3 sub-contractors were efficient in terms of the scale efficiency. It was stated that the pure technical efficiency scores of sub-contractors were generally better than their overall technical efficiency scores, which meant that most of the factories were not producing in the appropriate scale as the pure technical efficiency was the efficiency type ignoring the scale of the decision making unit which corresponded to the sub-contractors. Only 2 sub-contractors were found to be efficient in all three efficiency types. Using the DEA model, it was further determined the reference sub-contractors for inefficient sub-contractors in case that the inefficient sub-contractors could follow the input levels of reference ones in order to increase their efficiencies. It was pointed out that the 3 sub-contractors, which were efficient in all three efficiency type, were mostly determined as references for inefficient sub-contractors. Within the results of DEA, it was discussed that the inefficient sub-contractors should reduce their input levels to be efficient which were calculated as large amounts according to improvement ratio calculations. This point was clarified with the fact that although the operational dynamics of the sub-contractors were similar, there were big differences in the scales of the sub-contractors. In the conclusion part, the importance of supplier selection and performance evaluation was re-emphasized and the results of the study were summarized. It was put forward again that, this study was offering a model for supplier selection and performance evaluation, especially for companies operating in the apparel industry. Although, it was not possible to use the results of the comparison of the suppliers, it was stated that the hierarchical structure of the criteria and the priority degrees of them could be used by the companies acting in the apparel industry. Furthermore, it was pointed out that this study made a great contribution to the literature as it combined three different methods together which was not suggested before within the literature. Nonetheless, the limitations and some recommendations were also depicted and it was stated that the development of an application tool was suggested to ease the application of these methods and the fuzzy numbers could be integrated in calculating the quantitative performance scores from the qualitative parameters.
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