Journals / Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty / 2018 / Volume: 5 Issue: 3

ANALYTIC HIERARCHY PROCESS AND DATA ENVELOPMENT ANALYSIS METHODS BASED MODEL PROPOSAL FOR IMPROVING SUPPLIER EFFICIENCIES AND A CASE STUDY

TEDARİKÇİLERİN ETKİNLİKLERİNİN İYİLEŞTİRİLMESİNE YÖNELİK ANALİTİK HİYERARŞİ SÜRECİ VE VERİ ZARFLAMA ANALİZİ YÖNTEMLERİNE DAYANAN MODEL ÖNERİSİ VE BİR VAKA ÇALIŞMASI

Semih Coşkun(PAMUKKALE ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ, ENDÜSTRİ MÜHENDİSLİĞİ BÖLÜMÜ)0000-0001-5201-6563
Olcay Polat(PAMUKKALE ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ, ENDÜSTRİ MÜHENDİSLİĞİ BÖLÜMÜ)0000-0003-2642-0233
Leyla Özgür Polat(PAMUKKALE ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ, ENDÜSTRİ MÜHENDİSLİĞİ BÖLÜMÜ)0000-0002-5143-359X
Pages
—
Publication Date
2018-12-27
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Factors affecting the overall performance of the supply chains and the evaluation of the success criteria of all actors have become a part of sustainability.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:With the continuous development of the information systems allowing faster data communication and providing an opportunity to work on big data, it is now more possible for enterprises to implement analytical approaches on decision-making processes.
📊
Key Findings & Data:Factors affecting the overall performance of the supply chains and the evaluation of the success criteria of all actors have become a part of sustainability.
💡
Conclusion & Impact:According to the findings obtained from the DEA method, evaluations for the improvement of suppliers are presented.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Supply Chain Management · Data Envelopment Analysis · Efficiency

Abstract

With the continuous development of the information systems allowing faster data communication and providing an opportunity to work on big data, it is now more possible for enterprises to implement analytical approaches on decision-making processes. Following these advancements, a systematic approach that address supplier, enterprise, and customer factors to successfully deal with inputs, outputs and process management is required. To survive in competing markets, enterprises must improve themselves by considering not only their own system but also the entire supply chain. Factors affecting the overall performance of the supply chains and the evaluation of the success criteria of all actors have become a part of sustainability. In this study, a decision model based on Data Envelopment Analysis (DEA) has been developed for the evaluation of suppliers’ efficiencies in the enterprises. The proposed model has been applied to evaluate the performances of suppliers of an enterprise in the textile industry. According to the findings obtained from the DEA method, evaluations for the improvement of suppliers are presented.

Özet

Daha hızlı veri iletişimine izin veren ve büyük veri üzerinde çalışmaya fırsat sağlayan bilgi sistemlerinin sürekli gelişimi ile birlikte, işletmelerin karar alma süreçlerinde analitik yaklaşımları uygulamaları daha mümkün hale gelmiştir. Bu gelişmeleri takiben, girdiler, çıktılar ve süreçlerin yönetiminde başarılı olabilmek için tedarikçi, işletme ve müşteri faktörlerini ele alan sistematik bir yaklaşım gereklidir. İşletmeler rekabetçi pazarda hayatta kalabilmek için, sadece kendi sistemlerini değil, tedarik zincirinin bütününü dikkate olarak kendilerini geliştirmek zorundadır. Tedarik zincirlerinin genel performansını etkileyen faktörler ile bu zincirlerdeki aktörlerin başarı kriterlerinin değerlendirilmesi, sürdürülebilirliğin bir parçası haline gelmiştir. Bu çalışma kapsamında firmaların var olan tedarikçilerinin etkinliklerinin değerlendirilmesi için Veri Zarflama Analizi (VZA) temelli bir karar modeli oluşturulmuştur. Oluşturulan model, tekstil endüstrisinde yer alan bir işletmenin tedarikçilerinin performanslarının değerlendirilmesine yönelik olarak uygulanmıştır. VZA yönteminden elde edilen bulgulara göre tedarikçilerin geliştirilmesine yönelik değerlendirmelerde bulunulmuştur.

🔖

Cite This Article

Coşkun, S., Polat, O., Polat, L. Ö. (2018). ANALYTIC HIERARCHY PROCESS AND DATA ENVELOPMENT ANALYSIS METHODS BASED MODEL PROPOSAL FOR IMPROVING SUPPLIER EFFICIENCIES AND A CASE STUDY. Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty, Volume: 5 Issue: 3. https://doi.org/10.30798/makuiibf.415919

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (26)

  1. AKSOY, A., & ÖZTÜRK, N. (2011). Supplier selection and performance evaluation in just-in-time production environments. Expert Systems with Applications, 38(5), 6351-6359.
  2. AWASTHI, A., NOSHAD, K., & CHAUHAN, S. S. (2014). Supplier performance evaluation using a hybrid fuzzy data envelopment analysis approach Performance measurement with fuzzy data envelopment analysis (pp. 271-285): Springer.
  3. CHARNES, A., COOPER, W. W., & RHODES, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
  4. CHEN, Y. J., & DENG, M. (2015). Information Sharing in a Manufacturer–Supplier Relationship: Suppliers' Incentive and Production Efficiency. Production and Operations Management, 24(4), 619-633.
  5. COOPER, W. W., SEIFORD, L. M., & ZHU, J. (2011). Data envelopment analysis: History, models, and interpretations Handbook on data envelopment analysis (pp. 1-39): Springer.
  6. COSTANTINO, N., DOTOLI, M., EPICOCO, N., FALAGARIO, M., & SCIANCALEPORE, F. (2012). A cross efficiency fuzzy Data Envelopment Analysis technique for supplier evaluation under uncertainty. Paper presented at the Emerging Technologies & Factory Automation (ETFA), 2012 IEEE 17th Conference on.
  7. COŞKUN, S., POLAT, O., & KARA, B. (2015). A Decision Model for Supplier Selection based on Business System Management and Safety Criteria and Application of the Model. Pamukkale Univ Muh Bilim Derg, 21(4), 134-144.
  8. ÇELEBI, D., & BAYRAKTAR, D. (2008). An integrated neural network and data envelopment analysis for supplier evaluation under incomplete information. Expert Systems with Applications, 35(4), 1698-1710.
  9. DAĞDEVIREN, M., DÖNMEZ, N., & MUSTAFA, K. (2006). Bir İşletmede Tedarikçi Değerlendirme Süreci İçin Yeni Bir Model Tasarimi Ve Uygulamasi. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 21(2).
  10. DE BOER, L., LABRO, E., & MORLACCHI, P. (2001). A review of methods supporting supplier selection. European Journal of Purchasing & Supply Management, 7(2), 75-89.
  11. DOTOLI, M., EPICOCO, N., FALAGARIO, M., & SCIANCALEPORE, F. (2016). A stochastic cross‐efficiency data envelopment analysis approach for supplier selection under uncertainty. International Transactions in Operational Research, 23(4), 725-748.
  12. FIRAT, S. Ü. O., AKAN, M. Ö. A., ERSOY, E., GÖK, S., & ÜNAL, U. (2017). A Six Sigma DMAIC Process for Supplier Performance Evaluation using AHP and Kano's Model. International Journal of Business Analytics (IJBAN), 4(2), 37-61.
  13. GOVINDAN, K., RAJENDRAN, S., SARKIS, J., & MURUGESAN, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: a literature review. Journal of Cleaner Production, 98, 66-83.
  14. GÖRENER, A., AYVAZ, B., KUŞAKCI, A. O., & ALTINOK, E. (2017). A hybrid type-2 fuzzy based supplier performance evaluation methodology: The Turkish Airlines technic case. Applied Soft Computing, 56, 436-445.
  15. GÜNGÖR, A., & COŞKUN, S. (2009). A Supplier Selection,Evaluation and Re-evaluation Model For Textile Retail Organizations. Tekstil Ve Konfeksiyon, s 181-187.
  16. HO, W., XU, X., & DEY, P. K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 202(1), 16-24.
  17. KIM, H. J., SON, J., & KIM, S. W. (2016). Strategy for Improving Efficiency of Supply Chain Quality Management in Buyer-Supplier Dyads: The Suppliers’ Perspective. Mathematical Problems in Engineering, 2016.
  18. LI, C., FUN, Y., & HUNG, J. (1997). A new measure for supplier performance evaluation. IIE Transactions, 29(9), 753-758.
  19. LIU, J., DING, F.-Y., & LALL, V. (2000). Using data envelopment analysis to compare suppliers for supplier selection and performance improvement. Supply Chain Management: An International Journal, 5(3), 143-150.
  20. MONCZKA, R. M., & TRECHA, S. J. (1988). Cost‐based supplier performance evaluation. Journal of supply chain management, 24(1), 2-7.
  21. NARASIMHAN, R., TALLURI, S., & MENDEZ, D. (2001). Supplier evaluation and rationalization via data envelopment analysis: an empirical examination. Journal of supply chain management, 37(2), 28-37.
  22. PATRO, C. S. (2016). Evaluation of Supplier Performance and Efficiency: A Critical Analysis. Data Envelopment Analysis and Effective Performance Assessment, 184.
  23. SARKAR, A., & MOHAPATRA, P. K. (2006). Evaluation of supplier capability and performance: A method for supply base reduction. Journal of Purchasing and Supply Management, 12(3), 148-163.
  24. TAVANA, M., SHABANPOUR, H., YOUSEFI, S., & SAEN, R. F. (2017). A hybrid goal programming and dynamic data envelopment analysis framework for sustainable supplier evaluation. Neural Computing and Applications, 28(12), 3683-3696.
  25. TEZSÜRÜCÜ, D., & SOFYALIOGLU, Ç. (2015). AHS-VZA Yöntemi ile Tedarikçilerin Performans Degerlendirmesi: Beyaz Esya Sektöründe Bir Uygulama. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 33, 113-128.
  26. WU, D. D. (2010). A systematic stochastic efficiency analysis model and application to international supplier performance evaluation. Expert Systems with Applications, 37(9), 6257-6264.