ELEKTRONİK SEKTÖRÜNDE BULANIK ÇOK KRİTERLİ KARAR VERME YAKLAŞIMIYLA GERİ KAZANIM ALTERNATİFİ SEÇİMİ

Year 2018, Volume: 23 Issue: 4, 141 - 158, 31.12.2018

Hande Erdoğan Aktan , İsmail Karayün

https://doi.org/10.17482/uumfd.455216

Abstract

Dünyadaki büyük elektronik
üreticilerinin pek çoğu, rekabetçi üretim maliyetleri için Türk şirketleri ile
işbirliği yapmaktadır. Elektrik, Elektronik ve Hizmetler İhracatçıları Birliği
tarafından düzenlenen istatistiklere göre hem bu tarz işbirliklerinin hem de
Türk üreticilerinin orijinal malzeme üretimlerinin sayesinde 2015 yılında
elektronik ürün ihracatı ilk sırada yer almıştır. Ekonomik açıdan bakıldığında
ihracatın özellikle elektronik sektöründe hayati bir role sahip olması, ulusal
üretim kaynaklarının bilinçsizce kullanılmasını önlemek için geri kazanım
alternatiflerinin değerlendirilmesini gerektirmektedir. Ürünlerin yaşam
döngüleri sonunda üretime geri dönmelerinin sağlanması ile malzemelerin bir
kısmının üretim sürecinde yeniden kullanılması mümkün olabilmektedir. Bu
çalışmada tersine lojistik faaliyetlerine odaklanan ve geri kazanım bilincine
sahip Antalya'da elektronik sektöründe faaliyet gösteren işletmelerin farklı
nedenlerle geri dönen ürünleri için geri kazanım alternatifleri arasından en
uygun olanın belirlenmesi bulanık ortamda DEMATEL temelli ANP (DANP) ve VIKOR
yöntemlerinin birlikte kullanılmasıyla gerçekleştirilmiştir. Bu çalışma, bu
alandaki öncü araştırmalardan biri olma niteliğine sahiptir. 

Keywords

Bulanık VIKOR, Çok Kriterli Karar Verme, DANP, Geri Kazanım, Tersine Lojistik

Recovery Alternatives Selection by Fuzzy Multi Criteria Decision Making Approach in Electronics Sector

Abstract

Many of world's largest electronic
manıfacturers are making cooperation with Turkish companies for competitive
production costs. Either these production cooperations or original equipment
manufacturing productions of Turkish companies, regarding to statistics are
issued by Electrical, Electronics and Services Exporters' Association, in 2015
the export of electronics took place as the first. The fact that exports play a
vital role in the economy, especially in the electronics sector, requires the
evaluation of recovery alternatives to prevent the unconscious use of national
production resources. It is possible 
that some of the materials can be reused during the production process
by ensuring that the products return to the production at the end of their life
cycle. In this study, determination of the most suitable recovery alternative
for the products which are operating in the electronics sector in Antalya and which
focuses on reverse logistics activities and for those who have returned these
products for different reasons was carried out by using DEMATEL based ANP
(DANP) and VIKOR methods in the fuzzy environment . This study is one of the
leading researches in this area.

Keywords

DANP, Fuzzy VIKOR, Multi-Criteria Decision-Making, Recovery, Reverse Logistics

References

• Agrawal, S., Singh, R.K. ve Murtaza, Q. (2016) Disposition Decisions in Reverse Logistics by Using AHP-Fuzzy TOPSIS Approach, Journal of Modelling in Management, 11(4), 932-948. doi: 10.1108/JM2-12-2014-0091.
• Akyüz, G. (2012) Bulanık VİKOR Yöntemi ile Tedarikçi Seçimi, Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, Cilt: 26, Sayı: 1, 197-215.
• Arıkan, E., Şimşit-Kalender, Z.T. ve Vayvay, Ö. (2017) Solid Waste Disposal Methodology Selection Using Multi-Criteria Decision Making Methods and An Application in Turkey, Journal of Cleaner Production, 142, Bölüm 1, 403-412. Doi: 10.1016/j.jclepro.2015.10.054
• Bouzon, M., Govindan, K., Rodriguez, C.M.T. ve Campos, L.M.S. (2016) Identification and Analysis of Reverse Logistics Barriers Using Fuzzy Delphi Method and AHP, Resources, Conservation and Recyling, 108, 182-197. Doi: 10.1016/j.resconrec.2015.05.021.
• Chang, B., Chang, C.W. ve Wu, C.H. (2011) Fuzzy Dematel Method for Developing Supplier Selection Criteria, Expert Systems with Applications, 38(3), 1850-1858. doi: 10.1016/j.eswa.2010.07.114.
• Chen, L.Y. ve Wang, T.C. (2009) Optimizing Partners’ Choice in IS/IT Outsourcing Projects: The Strategic Decision Of Fuzzy VIKOR, International Journal of Production Economics, 120(1), 233-242. doi: 10.1016/j.ijpe.2008.07.022.
• Chuo, Y.C., Yang, C.-H., Lu, C.-H., Dang, V.T. ve Yang, P.A. (2017) Building Criteria for Evaluating Green Project Management: An Integrated Approach of Dematel and ANP, Sustainability, 9(5), 1-17. doi: 10.3390/su9050740
• Cui, J. ve Zhang, L. (2008) Metallurgical recovery of metals from electronic waste: a review. Journal of hazardous materials, 158(2-3), 228-256. doi: 10.1016/j.jhazmat.2008.02.001
• Feito-Cespon, M., Sarache, W., Piedra-Jimenez, F. Ve Cespon-Castro, R. (2017) Redesign of A Sustainable Reverse Supply Chain under Uncertainty: A Case Study, Journal of Cleaner Production, 151, 206-217. doi: 10.1016/j.jclepro.2017.03.057
• Flylgansvaer, B., Dahlstrom, R. Ve Nygaard, A. (2018) Exploring the Pursuit of Sustainability in Reverse Supply Chains for Electronics, Journal of Cleaner Production, 189, 472-484. doi: 10.1016/j.jclepro.2018.04.014
• Hsieh, T.-Y., Lu, S.-T. ve Tzeng, G.-H. (2004) Fuzzy MCDM approach for planning and design tenders selection in public office buildings, International Journal of Project Management, 22(7), 573–584. doi: 10.1016/j.ijproman.2004.01.002
• Hung, C-H. Ve Lee, W-Y. (2016) A Proactive Technology Selection Model for New Technology: The Case of 3D IC TSV, Technological Forecasting and Social Change, 103, 191-202. doi: 10.1016/j.techfore.2015.11.009
• Jain, V. ve Khan, S.A. (2016) Reverse Logistics Service Provider Selection: A TOPSIS-QFD Approach, Industrial Engineering and Engineering Management (IEEM), 2016 IEEE International Conference , Bali, 803-806.
• Jindal, A. ve Sangwan, K.S. (2016) A Fuzzy Based Decision Support Framework for Product Recovery Process Selection in Reverse Logistics, International Journal of Services and Operations Management, 25(4), 413-439. doi: 10.1504/IJSOM.2016.080274
• Kaya, M. (2016) Recovery of metals from electronic waste by physical and chemical recycling processes. International Journal of Chemical, Molecular, Nuclear, Materials and Metallurgical Engineering, 10(2), 232-243.
• Kızılkaya-Aydogan, E. ve Ozmen, M. (2016) The Stochastic VIKOR and Its Use in Reverse Logistic Option Selection Problem, Rairo-Operations Research, 1(1), 1-10.
• Liu, K-M., Lin, S-H., Hsieh, J-C. ve Tzeng, G-H. (2018) Improving the Food Waste Composting Facilities Site Selection for Sustainable Development Using a Hybrid Modified MADM Model, Waste Management, 75, 44-59. doi: 10.1016/j.wasman.2018.02.017.
• Liu, C.H., Tzeng G.H. ve Lee M.H. (2012) Improving Tourism Policy Implementation - The Use of Hybrid MCDM Models, Tourism Management, 33(2), 413-426. doi: 10.1016/j.tourman.2011.05.002.
• Lou, K.H. ve Wang, Y. (2009) Reverse Logistics in the Electronic Industry of China: A Case Study, Supply Chain Management: An International Journal, 14(6), 447–465. doi: 10.1108/13598540910995228
• 18. Mahapatara, S.S., Sharma, S.K. ve Parappagoudar, M.B. (2013) A Novel Multi-Criteria Decision Making Appraoch for Selection of Reverse Manufacturing Alternatives, International Journal of Services and Operations Management, 15(2), 176-195. doi: 10.1504/IJSOM.2013.053644
• Nakıboğlu, G. (2007) Tersine Lojistik: Önemi ve Dünyada Uygulamaları, Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 9(2), 181-196.
• Opricovic, S. (1998) Multi-criteria optimization of civil engineering systems. Belgrade: Faculty of Civil Engineering.
• Opricovic, S. (2011) Fuzzy VIKOR With An Application To Water Resources Planning, Expert Systems with Applications, 38, 12983–12990. doi: 10.1016/j.eswa.2011.04.097
• Opricovic, S. ve Tzeng, G.H. (2004) Compromise Solution By MCDM Methods: A Comparative Analysis of VIKOR and TOPSIS, European Journal of Operational Research, 156(2), 445–455. doi: 10.1016/S0377-2217(03)00020-1
• Opricovic, S. ve Tzeng, G.-H. (2003) Defuzzification within A Multicriteria Decision Model, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11(5), 635-652. doi:10.1142/S0218488503002387.
• Özdemir, Ö. (2010), Product Recovery Systems: A Review Of The Current Literature And Research Opportunities, ODÜ Sosyal Bilimler Enstitüsü Sosyal Bilimler Araştırmaları Dergisi, 1(2), 111-134.
• Özmen, M. ve Kızılkaya-Aydogan, E. (2013) Reverse Logistics Options Selection Problem: An Application of SMAA-2, IX. International Logistics Supply Chain Congress, Nevşehir, 673-680.
• Prakash, C. ve Barua, M.K. (2016) An Analysis of Integrated Robust Hybrid Model for Third-Party Reverse Logistics Partner Selection under Fuzzy Environment, Resources, Conservation and Recyling, 108, 63-81. doi: 10.1016/j.resconrec.2015.12.011
• Ravi, V. ve Shankar, R. (2012) Evaluating Alternatives in Reverse Logistics for Automobile Organisations, International Journal of Logistics Systems and Management, 12(1), 32-51. doi: 10.1504/IJLSM.2012.047057
• 29.Ravi, V., Shankar, R. ve Tiwari, M.K. (2005) Analyzing Alternatives in Reverse Logistics for End-of-Life Computers: ANP and Balanced Scorecard Approach, Computers&Industrial Engineering, 48, 327-356. doi: 10.1016/j.cie.2005.01.017
• Ravi, V., Shankar, R. ve Tiwari, M.K. (2008) Selection of A Reverse Logistics Project For End-of-Life Computers: ANP and Goal Programming, International Journal Of Production Research, 46(17), 4849-4870.
• Sharma, S. K., Mahapatra, S.S. ve Parappagoudar, M.B. (2016) Benchmarking of Product Recovery Alternatives in Reverse Logistics, Benchmarking: An International Journal, 23(2), 406-424. doi: 10.1108/BIJ-01-2014-0002
• Samantra, C., Sahu, N.K., Datta, S. ve Mahapatara, S.S. (2013) Decision-making in selecting reverse logistics alternative using interval-valued fuzzy sets combined with VIKOR approach, International Journal of Services and Operations Management, 14(2), 175-196. doi: 10.1504/IJSOM.2013.051828
• Sun, Z., Cao, H., Xiao, Y., Sietsma, J., Jin, W., Agterhuis, H., ve Yang, Y. (2016) Toward sustainability for recovery of critical metals from electronic waste: the hydrochemistry processes. ACS Sustainable Chemistry & Engineering, 5(1), 21-40. doi: 10.1021/acssuschemeng.6b00841
• Tosun, N., (2017) Target Market Selection in Fresh Fruit-Vegetable Sector Using Fuzzy VIKOR Method. Journal of Management, Marketing and Logistics (JMML), 4(4), 465-471. doi: 10.17261/Pressacademia.2017.734
• Tuzkaya,G. ve Gulsun, B. (2008) Evaluating Centralized Return Centers in a Reverse Logistics Network: An Integrated Fuzzy Multi-Criteria Decision Approach, International Journal of Environmental Science and Technology, 5(3), 339-352. doi: 10.1007/BF03326029
• Tzeng, G.H., Chiang, C.H. ve Li, C.W. (2007) "Evaluating Intertwined Effects in E-Learning Programs: A Novel Hybrid MCDM Model Based on Factor Analysis and Dematel", Expert Systems with Applications, 32(4), 1028-1044. doi: 10.1016/j.eswa.2006.02.004
• Wang, Z., Ren, J., Goodsite, M.E. ve Xu, G. (2018) Waste-to-energy, Municipal Solid Waste Treatment, and Best Available Technology: Comprehensive Evaluation by an Interval-Valued Fuzzy Multi-Criteria Decision Making Method, Journal of Cleaner Production, 172, 887-899. doi: 10.1016/j.jclepro.2017.10.184
• Yang, Y.P.O., Shieh H.M. ve Tzeng, G.H. (2013) A VIKOR Technique Based on Dematel and ANP for Information Security Risk Control Assessment, Information Sciences, 232, 482-500. doi: 10.1016/j.ins.2011.09.012.
• Yıldız, A. ve Deveci, M. (2013) Bulanık VIKOR Yöntemine Dayalı Personel Seçim Süreci”, Ege Akademik Bakış, 13(4), 427-436.
• Yu, H. ve Solvang, W.D. (2016) A Stochastic Programming Approach with Improved Multi-Criteria Scenario-Based Solution Method for Sustainable Reverse Logistics Design of Waste Electrical and Electronic Equipment (WEEE), Sustainability, 8(12), 1-28. doi: 10.3390/su8121331
• Zhao, Y., Cao, Y., Li, H., Wang, S., Liu, Y., Li, Y. ve Zhang, Y. (2018) Bullwhip Effect Mitigation of Green Supply Chain Optimization in Electronics Industry, Journal of Cleaner Production, 180, 888-912. doi: 10.1016/j.jclepro.2018.01.134
• Ziout, A., Azab, A. ve Atwan, M. (2014) A Holistic Approach for Decision on Selection of End-of-Life Products Recovery Options, Journal of Cleaner Production, 65, 497-516. doi: 10.1016/j.jclepro.2013.10.001.