Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2020, Cilt: 26 Sayı: 4, 758 - 767, 20.08.2020

Öz

Kaynakça

  • Dağdeviren M, Eraslan E. “Promethee siralama yöntemi ile tedarikçi seçimi”. Journal of the Faculty of Engineering and Architecture of Gazi University, 23(1), 69-75, 2008.
  • Torun H, Canbulut G. “İki aşamalı tedarik zinciri koordinasyonunun bulanık talep altında analizi”. Journal of the Faculty of Engineering and Architecture of Gazi University, baskıda, 2019.
  • Saen, RF. “Developing a new data envelopment analysis methodology for supplier selection in the presence of both undesirable outputs and imprecise data”. The International Journal of Advanced Manufacturing Technology, 51, 1243-1250, 2010.
  • Kilincci O, Onal SA. “Fuzzy AHP approach for supplier selection in a washing machine company”. Expert Systems with Applications, 38(8), 9656-9664, 2011.
  • Sevkli M, Lenny Koh S, Zaim S, Demirbag M, Tatoglu E. “An application of data envelopment analytic hierarchy process for supplier selection: A case study of BEKO in Turkey”. International Journal of Production Research, 45(9), 1973-2003, 2007.
  • Lin CT, Chen CB, Ting YC. “An ERP model for supplier selection in electronics industry”. Expert Systems with Applications, 38(3), 1760-1765, 2011.
  • Güneri AF, Ertay T, Yücel A. “An approach based on ANFIS input selection and modeling for supplier selection problem”. Expert Systems with Applications, 38(12), 14907-1491, 2011.
  • Soheilirad S, Govindan K, Mardani A, Zavadskas EK, Nilashi M, Zakuan N. “Application of data envelopment analysis models in supply chain management: a systematic review and meta-analysis”. Annals of Operations Research, 271, 915-969, 2018.
  • Charnes A, Cooper WW, Rhodes E. “Measuring the efficiency of DMUs”. European Journal of Operational Research, 2, 429-444, 1978.
  • Easton L, Murphy DJ, Pearson JN. “Purchasing performance evaluation with data envelopment analysis”. European Journal of Purchasing & Supply Management, 8(3), 123-134, 2002.
  • Çelebi D, Bayraktar D. “An integrated neural network and data envelopment analysis for supplier evaluation under incomplete information”. Expert Systems with Applications, 35(4), 1698-1710, 2008.
  • Zeydan M, Çolpan C, Çobanoglu C. “A combined methodology for supplier selection and performance evaluation”. Expert Systems with Applications, 38(3), 2741-2751, 2011.
  • Ribeiro Soriano D, Ross AD, Parker H, del Mar Benavides-Espinosa M, Droge C. “Sustainability and supply chain infrastructure development”. Management Decision, 50(10), 1891-1910, 2012.
  • Karsak EE, Dursun M. “An integrated supplier selection methodology incorporating QFD and DEA with imprecise data”. Expert Systems with Applications, 41(16), 6995-7004, 2014.
  • Egilmez G, Kucukvar M, Tatari O, Bhutta MKS. “Supply chain sustainability assessment of the US. food manufacturing sectors: A life cycle-based frontier approach”. Resources, Conservation and Recycling, 82, 8-20, 2014.
  • Azadi M, Shabani A, Khodakarami M, Saen RF. “Planning in feasible region by two-stage target-setting DEA methods: An application in green supply chain management of public transportation service providers”. Transportation Research Part E: Logistics and Transportation Review, 70, 324-338, 2014.
  • Mirhedayatian SM, Azadi M, Saen RF. “A novel network data envelopment analysis model for evaluating green supply chain management”. International Journal of Production Economics, 147(Part B), 544-554, 2014.
  • Khodakarami M, Shabani A, Saen RF, Azadi M. “Developing distinctive two-stage data envelopment analysis models: An application in evaluating the sustainability of supply chain management”. Measurement, 70, 62-74, 2015.
  • Tajbakhsh A, Hassini E. “A data envelopment analysis approach to evaluate sustainability in supply chain networks”. Journal of Cleaner Production, 105, 74-85, 2015.
  • Shi P, Yan B, Shi S, Ke C. “A decision support system to select suppliers for a sustainable supply chain based on a systematic DEA approach”. Information Technology and Management, 16(1), 39-49, 2015.
  • Shabani A, Saen RF. “Developing a novel data envelopment analysis model to determine prospective benchmarks of green supply chain in the presence of dual-role factor”. Benchmarking: An International Journal, 22(4), 711-730, 2015.
  • Mahdiloo M, Saen RF, Lee KH. “Technical, environmental and eco-efficiency measurement for supplier selection: An extension and application of data envelopment analysis”. International Journal of Production Economics, 168, 279-289, 2015.
  • Ji X, Wu J, Zhu Q. “Eco-design of transportation in sustainable supply chain management: A DEA-likemethod”. Transportation Research Part D: Transport and Environment, 48, 451-459, 2016.
  • Zarbakhshnia N, Jaghdani TJ. “Sustainable supplier evaluation and selection with a novel two-stage DEA model in the presence of uncontrollable inputs and undesirable outputs: a plastic case study”. The International Journal of Advanced Manufacturing Technology, 97(5-8), 2933-2945, 2018.
  • Chen Y, Zhu J. “Measuring information technology's indirect impact on firm performance”. Information Technology and Management, 5(1), 9-22, 2004.
  • Wanke P, Barros C. “Two-stage DEA: An application to major Brazilian banks”. Expert Systems with Applications, 41(5), 2337-2344, 2014.
  • Wang K, Huang W, Wu J, Liu YN. “Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA”. Omega, 44, 5-20, 2014.
  • Premachandra IM, Zhu J, Watson J, Galagedera DU. “Best-performing US mutual fund families from 1993 to 2008: Evidence from a novel two-stage DEA model for efficiency decomposition”. Journal of Banking & Finance, 36(12), 3302-3317, 2012.
  • Kao C, Hwang SN. “Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan”. European Journal of Operational Research, 185(1), 418-429, 2008.
  • Chen Y, Cook WD, Li N, Zhu J. “Additive efficiency decomposition in two-stage DEA”. European Journal of Operational Research, 196(3), 1170-1176, 2009.
  • Moreno P, Lozano S. “A network DEA assessment of team efficiency in the NBA”. Annals of Operations Research, 214(1), 99-124, 2014.
  • Li Y, Lei X, Dai Q, Liang L. “Performance evaluation of participating nations at the 2012 London Summer Olympics by a two-stage data envelopment analysis”. European Journal of Operational Research, 243(3), 964-973, 2015.
  • Sexton TR, Silkman RH, Hogan AJ. “Data envelopment analysis: Critique and extensions”. New Directions for Evaluation, (32), 73-105, 1986.
  • Andersen P, Petersen NC. “A procedure for ranking efficient units in data envelopment analysis”. Management Science, 39(10), 1261-1264, 1993.
  • Amin GR, Toloo M. “Finding the most efficient DMUs in DEA: An improved integrated model”. Computers & Industrial Engineering, 52(1), 71-77, 2007.
  • Amin GR. “Comments on finding the most efficient DMUs in DEA: An improved integrated model”. Computers & Industrial Engineering, 56(4), 1701-1702, 2009.
  • Foroughi AA. “A new mixed integer linear model for selecting the best decision making units in data envelopment analysis”. Computers & Industrial Engineering, 60(4), 550-554, 2011.
  • Wang YM, Jiang P. “Alternative mixed integer linear programming models for identifying the most efficient decision making unit in data envelopment analysis”. Computers & Industrial Engineering, 62(2), 546-553, 2012.
  • Toloo M. “Alternative minimax model for finding the most efficient unit in data envelopment analysis”. Computers & Industrial Engineering, 81, 186-194, 2015.
  • Liu JS, Lu WM, Yang C, Chuang M. “A network-based approach for increasing discrimination in data envelopment analysis”. Journal of the Operational Research Society, 60(11), 1502-1510, 2009.
  • Liu JS, Lu WM. “DEA and ranking with the network-based approach: a case of R&D performance”. Omega, 38(6), 453-464, 2010.
  • Seiford LM, Zhu J. “Profitability and marketability of the top 55 US commercial banks”. Management Science, 45(9), 1270-1288, 1999.
  • Kao C, Hwang SN. “Multi-period efficiency and Malmquist productivity index in two-stage production systems”. European Journal of Operational Research, 232(3), 512-521, 2014.
  • Charnes A, Cooper WW. “Programming with linear fractional functionals”. Naval Research Logistics, 9(3-4), 181-186, 1962.
  • Sueyoshi T. “DEA non-parametric ranking test and index measurement: slack-adjusted DEA and an application to Japanese agriculture cooperatives”. Omega, 27(3), 315-326, 1999.
  • Seiford LM, Zhu J. “Modeling undesirable factors in efficiency evaluation”. European Journal of Operational Research, 142, 16-20, 2002.

Karma-tamsayılı iki aşamalı veri zarflama analizi modeli ile en etkin tedarikçi seçimi

Yıl 2020, Cilt: 26 Sayı: 4, 758 - 767, 20.08.2020

Öz

Tedarikçi seçimi tedarik zinciri yönetiminde en önemli stratejik konulardan biridir ve bir organizasyonda kilit bir rol oynar. Uygun bir tedarikçi seçmek satın alma departmanının en önemli kararlarından biridir ve bu karar genellikle çeşitli kriterlere dayanır. Bu çalışmada iki aşamalı üretim süreci olarak ifade edilen bir tedarik zinciri yapısında girdi, ara ürün ve çıktı ile birlikte en iyi (en etkin) tedarikçiyi değerlendirmek ve seçmek için karma-tamsayılı bir Veri Zarflama Analizi modeli önerilmiştir. Hem plastik ambalaj kayışı endüstrisindeki firmaların hem de reçine üreten firmaların tedarikçilerinin seçilmesi probleminde önerilen model uygulanmış ve modelin performansı diğer çalışmalarla karşılaştırılmıştır. Sonuçlar önerilen karma tamsayılı iki aşamalı modelin karar vericinin tedarikçi seçimini kolaylaştırdığı göstermektedir.

Kaynakça

  • Dağdeviren M, Eraslan E. “Promethee siralama yöntemi ile tedarikçi seçimi”. Journal of the Faculty of Engineering and Architecture of Gazi University, 23(1), 69-75, 2008.
  • Torun H, Canbulut G. “İki aşamalı tedarik zinciri koordinasyonunun bulanık talep altında analizi”. Journal of the Faculty of Engineering and Architecture of Gazi University, baskıda, 2019.
  • Saen, RF. “Developing a new data envelopment analysis methodology for supplier selection in the presence of both undesirable outputs and imprecise data”. The International Journal of Advanced Manufacturing Technology, 51, 1243-1250, 2010.
  • Kilincci O, Onal SA. “Fuzzy AHP approach for supplier selection in a washing machine company”. Expert Systems with Applications, 38(8), 9656-9664, 2011.
  • Sevkli M, Lenny Koh S, Zaim S, Demirbag M, Tatoglu E. “An application of data envelopment analytic hierarchy process for supplier selection: A case study of BEKO in Turkey”. International Journal of Production Research, 45(9), 1973-2003, 2007.
  • Lin CT, Chen CB, Ting YC. “An ERP model for supplier selection in electronics industry”. Expert Systems with Applications, 38(3), 1760-1765, 2011.
  • Güneri AF, Ertay T, Yücel A. “An approach based on ANFIS input selection and modeling for supplier selection problem”. Expert Systems with Applications, 38(12), 14907-1491, 2011.
  • Soheilirad S, Govindan K, Mardani A, Zavadskas EK, Nilashi M, Zakuan N. “Application of data envelopment analysis models in supply chain management: a systematic review and meta-analysis”. Annals of Operations Research, 271, 915-969, 2018.
  • Charnes A, Cooper WW, Rhodes E. “Measuring the efficiency of DMUs”. European Journal of Operational Research, 2, 429-444, 1978.
  • Easton L, Murphy DJ, Pearson JN. “Purchasing performance evaluation with data envelopment analysis”. European Journal of Purchasing & Supply Management, 8(3), 123-134, 2002.
  • Çelebi D, Bayraktar D. “An integrated neural network and data envelopment analysis for supplier evaluation under incomplete information”. Expert Systems with Applications, 35(4), 1698-1710, 2008.
  • Zeydan M, Çolpan C, Çobanoglu C. “A combined methodology for supplier selection and performance evaluation”. Expert Systems with Applications, 38(3), 2741-2751, 2011.
  • Ribeiro Soriano D, Ross AD, Parker H, del Mar Benavides-Espinosa M, Droge C. “Sustainability and supply chain infrastructure development”. Management Decision, 50(10), 1891-1910, 2012.
  • Karsak EE, Dursun M. “An integrated supplier selection methodology incorporating QFD and DEA with imprecise data”. Expert Systems with Applications, 41(16), 6995-7004, 2014.
  • Egilmez G, Kucukvar M, Tatari O, Bhutta MKS. “Supply chain sustainability assessment of the US. food manufacturing sectors: A life cycle-based frontier approach”. Resources, Conservation and Recycling, 82, 8-20, 2014.
  • Azadi M, Shabani A, Khodakarami M, Saen RF. “Planning in feasible region by two-stage target-setting DEA methods: An application in green supply chain management of public transportation service providers”. Transportation Research Part E: Logistics and Transportation Review, 70, 324-338, 2014.
  • Mirhedayatian SM, Azadi M, Saen RF. “A novel network data envelopment analysis model for evaluating green supply chain management”. International Journal of Production Economics, 147(Part B), 544-554, 2014.
  • Khodakarami M, Shabani A, Saen RF, Azadi M. “Developing distinctive two-stage data envelopment analysis models: An application in evaluating the sustainability of supply chain management”. Measurement, 70, 62-74, 2015.
  • Tajbakhsh A, Hassini E. “A data envelopment analysis approach to evaluate sustainability in supply chain networks”. Journal of Cleaner Production, 105, 74-85, 2015.
  • Shi P, Yan B, Shi S, Ke C. “A decision support system to select suppliers for a sustainable supply chain based on a systematic DEA approach”. Information Technology and Management, 16(1), 39-49, 2015.
  • Shabani A, Saen RF. “Developing a novel data envelopment analysis model to determine prospective benchmarks of green supply chain in the presence of dual-role factor”. Benchmarking: An International Journal, 22(4), 711-730, 2015.
  • Mahdiloo M, Saen RF, Lee KH. “Technical, environmental and eco-efficiency measurement for supplier selection: An extension and application of data envelopment analysis”. International Journal of Production Economics, 168, 279-289, 2015.
  • Ji X, Wu J, Zhu Q. “Eco-design of transportation in sustainable supply chain management: A DEA-likemethod”. Transportation Research Part D: Transport and Environment, 48, 451-459, 2016.
  • Zarbakhshnia N, Jaghdani TJ. “Sustainable supplier evaluation and selection with a novel two-stage DEA model in the presence of uncontrollable inputs and undesirable outputs: a plastic case study”. The International Journal of Advanced Manufacturing Technology, 97(5-8), 2933-2945, 2018.
  • Chen Y, Zhu J. “Measuring information technology's indirect impact on firm performance”. Information Technology and Management, 5(1), 9-22, 2004.
  • Wanke P, Barros C. “Two-stage DEA: An application to major Brazilian banks”. Expert Systems with Applications, 41(5), 2337-2344, 2014.
  • Wang K, Huang W, Wu J, Liu YN. “Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA”. Omega, 44, 5-20, 2014.
  • Premachandra IM, Zhu J, Watson J, Galagedera DU. “Best-performing US mutual fund families from 1993 to 2008: Evidence from a novel two-stage DEA model for efficiency decomposition”. Journal of Banking & Finance, 36(12), 3302-3317, 2012.
  • Kao C, Hwang SN. “Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan”. European Journal of Operational Research, 185(1), 418-429, 2008.
  • Chen Y, Cook WD, Li N, Zhu J. “Additive efficiency decomposition in two-stage DEA”. European Journal of Operational Research, 196(3), 1170-1176, 2009.
  • Moreno P, Lozano S. “A network DEA assessment of team efficiency in the NBA”. Annals of Operations Research, 214(1), 99-124, 2014.
  • Li Y, Lei X, Dai Q, Liang L. “Performance evaluation of participating nations at the 2012 London Summer Olympics by a two-stage data envelopment analysis”. European Journal of Operational Research, 243(3), 964-973, 2015.
  • Sexton TR, Silkman RH, Hogan AJ. “Data envelopment analysis: Critique and extensions”. New Directions for Evaluation, (32), 73-105, 1986.
  • Andersen P, Petersen NC. “A procedure for ranking efficient units in data envelopment analysis”. Management Science, 39(10), 1261-1264, 1993.
  • Amin GR, Toloo M. “Finding the most efficient DMUs in DEA: An improved integrated model”. Computers & Industrial Engineering, 52(1), 71-77, 2007.
  • Amin GR. “Comments on finding the most efficient DMUs in DEA: An improved integrated model”. Computers & Industrial Engineering, 56(4), 1701-1702, 2009.
  • Foroughi AA. “A new mixed integer linear model for selecting the best decision making units in data envelopment analysis”. Computers & Industrial Engineering, 60(4), 550-554, 2011.
  • Wang YM, Jiang P. “Alternative mixed integer linear programming models for identifying the most efficient decision making unit in data envelopment analysis”. Computers & Industrial Engineering, 62(2), 546-553, 2012.
  • Toloo M. “Alternative minimax model for finding the most efficient unit in data envelopment analysis”. Computers & Industrial Engineering, 81, 186-194, 2015.
  • Liu JS, Lu WM, Yang C, Chuang M. “A network-based approach for increasing discrimination in data envelopment analysis”. Journal of the Operational Research Society, 60(11), 1502-1510, 2009.
  • Liu JS, Lu WM. “DEA and ranking with the network-based approach: a case of R&D performance”. Omega, 38(6), 453-464, 2010.
  • Seiford LM, Zhu J. “Profitability and marketability of the top 55 US commercial banks”. Management Science, 45(9), 1270-1288, 1999.
  • Kao C, Hwang SN. “Multi-period efficiency and Malmquist productivity index in two-stage production systems”. European Journal of Operational Research, 232(3), 512-521, 2014.
  • Charnes A, Cooper WW. “Programming with linear fractional functionals”. Naval Research Logistics, 9(3-4), 181-186, 1962.
  • Sueyoshi T. “DEA non-parametric ranking test and index measurement: slack-adjusted DEA and an application to Japanese agriculture cooperatives”. Omega, 27(3), 315-326, 1999.
  • Seiford LM, Zhu J. “Modeling undesirable factors in efficiency evaluation”. European Journal of Operational Research, 142, 16-20, 2002.
Toplam 46 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Makale
Yazarlar

Volkan Soner Özsoy

Mediha Örkcü Bu kişi benim

Hasan Örkcü

Yayımlanma Tarihi 20 Ağustos 2020
Yayımlandığı Sayı Yıl 2020 Cilt: 26 Sayı: 4

Kaynak Göster

APA Özsoy, V. S., Örkcü, M., & Örkcü, H. (2020). Karma-tamsayılı iki aşamalı veri zarflama analizi modeli ile en etkin tedarikçi seçimi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 26(4), 758-767.
AMA Özsoy VS, Örkcü M, Örkcü H. Karma-tamsayılı iki aşamalı veri zarflama analizi modeli ile en etkin tedarikçi seçimi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. Ağustos 2020;26(4):758-767.
Chicago Özsoy, Volkan Soner, Mediha Örkcü, ve Hasan Örkcü. “Karma-tamsayılı Iki aşamalı Veri Zarflama Analizi Modeli Ile En Etkin tedarikçi seçimi”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 26, sy. 4 (Ağustos 2020): 758-67.
EndNote Özsoy VS, Örkcü M, Örkcü H (01 Ağustos 2020) Karma-tamsayılı iki aşamalı veri zarflama analizi modeli ile en etkin tedarikçi seçimi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 26 4 758–767.
IEEE V. S. Özsoy, M. Örkcü, ve H. Örkcü, “Karma-tamsayılı iki aşamalı veri zarflama analizi modeli ile en etkin tedarikçi seçimi”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, c. 26, sy. 4, ss. 758–767, 2020.
ISNAD Özsoy, Volkan Soner vd. “Karma-tamsayılı Iki aşamalı Veri Zarflama Analizi Modeli Ile En Etkin tedarikçi seçimi”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 26/4 (Ağustos 2020), 758-767.
JAMA Özsoy VS, Örkcü M, Örkcü H. Karma-tamsayılı iki aşamalı veri zarflama analizi modeli ile en etkin tedarikçi seçimi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2020;26:758–767.
MLA Özsoy, Volkan Soner vd. “Karma-tamsayılı Iki aşamalı Veri Zarflama Analizi Modeli Ile En Etkin tedarikçi seçimi”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, c. 26, sy. 4, 2020, ss. 758-67.
Vancouver Özsoy VS, Örkcü M, Örkcü H. Karma-tamsayılı iki aşamalı veri zarflama analizi modeli ile en etkin tedarikçi seçimi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2020;26(4):758-67.





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