The Evaluation of the Environmental Performance of the Countries with Multiple Criteria Decision Making Methods and a Fuzzy Logic Based Approach

Öz

In recent years, due to industrialization, population growth, the continuous increase in the needs of the society and technological developments, the environmental problems of the countries are increasing and the countries take the necessary measures to eliminate this problem. In this study, six different multi-criteria decision-making (MCDM) models that measure the environmental performance of countries using Entropy, Gray Relational Analysis (GRA) and Multi Objective Optimization on the basis of Ratio Analysis (MOORA) methods are introduced. Criteria weights are calculated by Entropy method and environmental performance levels of countries were analyzed by GRA and MOORA methods. In addition, the results obtained from six different MCDM models are combined with a fuzzy logic-based approach and a single result is achieved. According to the results of the analysis, it is concluded that the most important criteria are forests, agriculture, and water resources; the best performing countries are Austria, Denmark and France. 

Anahtar Kelimeler

• Entropy,Grey Relation Analysis,MOORA,Fuzzy Logic,Measuring Environmental Performance

Ülkelerin Çevresel Performanslarının Çok Kriterli Karar Verme Yöntemleri ve Bulanık Mantık Tabanlı Bir Yaklaşım İle Bütünleşik Olarak Değerlendirilmesi

Öz

Son yıllarda endüstrileşme, nüfus artışı, toplumun ihtiyaçlarının sürekli artması ve teknolojik gelişmeler nedeniyle ülkelerin çevresel sorunları gittikçe artmakta ve bu sorunu ortadan kaldırmak için ülkeler gerekli önlem ve tedbirleri almaktadır. Bu çalışmada çok kriterli karar verme (ÇKKV) yöntemlerinden Entropi, Gri İlişkisel Analiz (GİA) ve Oransal Analize Dayalı Çok Amaçlı Optimizasyon (MOORA) yöntemleri bütünleşik olarak kullanılarak ülkelerin çevresel performanslarını ölçen altı farklı çok kriterli karar verme modeli tanıtılmıştır. Entropi yöntemi ile kriter ağırlıkları hesaplanmış, GİA ve MOORA yöntemleri ile de ülkelerin çevresel performans düzeyleri analiz edilmiştir. Ayrıca altı farklı ÇKKV modelinden elde edilen sonuçlar bulanık mantık tabanlı bir yaklaşım ile birleştirilerek tek bir sonuca ulaşılmıştır. Analiz sonuçlarına göre, en önemli kriterlerin ormanlar, tarım ve su kaynakları olduğu, en iyi performans gösteren ülkelerin Avusturya, Danimarka ve Fransa olduğu sonucuna ulaşılmıştır.

Anahtar Kelimeler

• Entropi,Gri İlişkisel Analiz,MOORA,Çevresel Performans Ölçümü,Bulanık Mantık

Kaynakça

1. Ab-rahim, Rossazana (2015), “Environmental Performance of ASEAN Countries: A Data Envelopment Analysis”, Journal of Economic Policy and Research, Vol. 10, No. 1: 98-108.
2. Adalı, Esra Aytaç; Tuş Işık, Ayşegül (2017), “The Multi-Objective Decision Making Methods Based on MULTIMOORA and MOOSRA For The Laptop Selection Problem, Journal of Industrial Engineering International, Vol. 13, No. 2: 229-237.
3. Akıncı, Sevcan Kılıç; Akıncı, M. Mehmet (2010), “Sürdürülebilir Kalkınmaya Katkı Bağlamında Örgütlerin Çevresel Performansları ve Performans Değerlendirme Teknikleri”, Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, C. 24, S. 1: 193-207.
4. Aksu, Esra Özkan; Gencer, Cevriye Temel (2018), “Veri Zarflama Analizi İle OECD Ülkelerinin Çevre Performansının İncelenmesi”, International Journal of Economic and Administrative Studies, 18. EYİ Özel Sayısı, 191-206.
5. Bhowmik, Chiranjib; Baruah, Abhinandan; Bhowmik, S.; Ray, A. (2009), “Green Energy Sources Selection For Sustainable Energy Planning Using Multi-Criteria Decision-Making Approach”, International Conference on Mechanical, Materials and Renewable Energy, Vol. 377, No. 1: 1-9.
6. Bimha, Alfred; Nhamo, Goldwell (2017), “Measuring Environmental Performance of Banks: Evidence From Carbon Disclosure Project (CDP) Reporting Banks”, Journal of Economic and Financial Sciences, Vol. 10, No. 1: 26-46.
7. Brauers, Willem Karel (2013), “Multi-Objective Seaport Planning by MOORA Decision Making”, Annals of Operations Research, Vol. 206, No. 1: 39-58.
8. Brauers, Willem Karel; Ginevičius, Romualdas; Podvezko, V. (2010), “Regional Development In Lithuania Considering Multiple Objectives By The MOORA Method”, Technological and Economic Development of Economy, Vol. 16, No. 4: 613-640.

9. Brauers, Willem Karel; Ginevicius, Romualdas (2009), “Robustness in Regional Development Studies: The Case of Lithuania”, Journal of Business Economics and Management, Vol. 10, No. 2: 121-140.
10. Brauers, Willem Karel; Zavadskas, Edmundas Kazimieras (2006), “The MOORA Method and its Application to Privatization in a Transition Economy”, Control and Cybernetic, Vol. 35, No. 2: 445-469.
11. Brauers, Willem Karel; Zavadskas, Edmundas Kazimieras; Turskis, Z.; Vilutiene, T. (2008), “Multi‐objective Contractor's Ranking by Applying the Moora Method”, Journal of Business Economics and Management, Vol. 9, No. 4: 245-255.
12. Campos, Lucila M.S; Heizen, Daiane Aparecida de Melo, Verdinelli, M. A.; Miguel, P. A. C. (2015), “Environmental Performance Indicators: A Study on ISO 14001 Certified Companies”, Journal of Cleaner Production, Vol. 99: 286-296.
13. Chang, Young-Tae (2013), “Environmental Efficiency of Ports: A Data Envelopment Analysis Approach”, Maritime Policy & Management, Vol. 40, No. 5: 467-478.
14. Dashore, Kshitij; Pawar, Shashang Sing; Sohani, N.; Verma, D. S. (2013), “Product Evaluation Using Entropy and Multi Criteria Decision Making Methods”, International Journal of Engineering Trends and Technology, Vol. 4, No. 5: 2183-2187.
15. Demircioğlu, Mert; Coşkun, İbrahim Tolga (2018), “Critic-Moosra Yöntemi ve UPS Seçimi Üzerine Bir Uygulama”, Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, C. 27, S. 1: 183-195.
16. Deng, Julong (1989), “Introduction to Grey System Theory”, The Journal of Grey System, Vol. 1, No. 1: 1-24.
17. Diakoulaki, Danae; Mavrotas, George; Papayannakis, L. (1995), “Determining Objective Weights in Multiple Criteria Problems: The CRITIC Method”, Computers & Operations Research, Vol. 22, No. 7: 763-770.
18. Djoundourian, Salpie (2012), “Environmental Performance of Developing Countries: A Comparative Study”, Topics in Middle Eastern and African Economies, Vol. 14: 265-277.
19. Dwivedi, Sanjay Kumar; Dwivedi, Ashutosh (2018), “Application of MOORA And WSM Method For Supplier Selection In Manufacturing”, International Journal of Advance Research and Development, Vol. 3, No. 7: 114-117.
20. Erol, İsmail; Ferrell Jr, William (2009), “Integrated Approach for Reorganizing Purchasing: Theory and a Case Analysis on a Turkish Company”, Computers & Industrial Engineering, Vol. 56, No. 4: 1192-1204.
21. Gadakh, Vijay S. (2011), “Application of MOORA Method For Parametric Optimization of Milling Process”, International Journal Of Applied Engineering Research, Dindigul, Vol. 1, No. 4: 743-758.
22. García-Sánchez, Isabel Maria; Almeida, Thiago Alexandre das Neves; Camara, R .P. B. (2015), “A Proposal for A Composite Index of Environmental Performance (CIEP) for Countries”, Ecological Indicators, Vol. 48: 171–188.
23. Gök, Murat; Yiğit, Sema (2017), “Türkiye’deki Büyükşehirlerin Sürdürülebilirlik Kriterleri Açısından İncelenmesi”, Yönetim Bilimleri Dergisi, C. 15, S. 30: 253-273.
24. Gonçalves, Tiago Jose Menezes; Correia, Anderson Ribeiro (2016), “A Multicriteria Model to Evaluate Airport Ramp Safety: A Study At São Paulo International Airport”, Ingeniare. Revista chilena de ingeniería, Vol. 24, No. 3: 454-464.
25. Guo, Ji; Zhu, Dongdong; Wu, X.; Yan, Y. (2017), “Study on Environment Performance Evaluation and Regional Differences of Strictly-Environmental- Monitored Cities in China”, Sustainability, Vol. 9, No. 12: 1-20.
26. Hasani, Hossein; Tabatabaei, Somayeh Akhavan; Amiri, G. (2012), “Grey Relational Analysis to Determine the Optimum Process Parameters for Open-End Spinning Yarns”, Journal of Engineered Fibers and Fabrics, Vol. 7, No. 2: 81-86.
27. Hermann, Barbara; Kroeze, Carolen; Jawjit, W. (2006), “Assessing Environmental Performance by Combining Life Cycle Assessment, Multi-Criteria Analysis and Environmental Performance Indicators”, Journal of Cleaner Production, Vol. 15, No. 18: 1787-1796.
28. Hourneaux Jr., Flavio; Hrdlicka, Hermann Atila; Gomes, C. M.; Kruglianskas, I. (2014), “The Use of Environmental Performance Indicators and Size Effect: A Study of Industrial Companies”, Ecological Indicators, Vol. 36: 205-212.
29. Hsiao, Shih Wen; Lin, Hsing Hung; Ko, Y. C. (2017), “Application of Grey Relational Analysis to Decision-Making during Product Development”, EURASIA Journal of Mathematics Science and Technology Education, Vol. 13, No. 6: 2581-2600.
30. Hsu, Chaug-Ing; Wen, Yuh-Horng (2000), “Application of Grey Theory and Multi Objective Programming towards Airline Network Design”, European Journal of Operational Research, Vol. 127, No. 1: 44-68.
31. Hsu, Yu-Lung; Liu, Chun-Chu (2010). “Environmental Performance Evaluation and Strategy Management Using Balanced Scorecard”, Environmental Monitoring and Assessment, Vol.170, No. 1-4: 599–607.
32. Ismail, Zubaidah; Tai, Jie Chuin; Kong, K. K.; Law, K. H.; Shirazi, S. M.; Karim, R. (2013), “Using Data Envelopment Analysis In Comparing The Environmental Performance and Technical Efficiency of Selected Companies In Their Global Petroleum Operation”, Measurement, Vol. 46, No. 9: 3401–3413.
33. Jahan, Ali; Mustapha, Faizal; Sapuan, S. M.; Ismail, M. Y.; Bahraminasab, M. (2012), “A Framework for Weighting of Criteria in Ranking Stage of Material Selection Process”, The International Journal of Advanced Manufacturing Technology, Vol. 58, No. 1: 411-420.
34. Kabak, Mehmet; Dağdeviren, Metin (2017), “A Hybrid Approach Based On ANP and Grey Relational Analysis For Machine Selection”, Technical Gazette, Vol. 24, No. 1: 109-118.
35. Kundakçı, Nilsen. (2016), “Personnel Selection with Grey Relational Analysis”, Management Science Letters, Vol. 6, No. 5: 351–360.
36. Kung, Chaang-Yung; Yan, Tzung-Ming; Chuang, S. C. (2006), “GRA to Assess the Operating Performance of Non-Life Insurance Companies in Taiwan”, The Journal of Grey System, Vol. 18, No. 2: 155- 160.
37. Lee, Ming-Chang; Chang, Jui-Fang; Chen, J. F. (2011), “An Entropy Decision Model for Selection of Enterprise Resource Planning System”, International Journal of Computer Trends and Technology, March to April Issue, 1-9.
38. Lin, Jiang-Long; Lin, C. L. (2005), “The Use of Grey-Fuzzy Logic for the Optimization of the Manufacturing Process”, Journal of Materials Processing Technology, Vol. 160, No. 1: 9-14.
39. Liu, Wei; Tian, Jinping; Chen, L.; Lu, W.; Gao, Y. (2015), “Environmental Performance Analysis of Eco-Industrial Parks in China A Data Envelopment Analysis Approach”, Journal of Industrial Ecology, Vol. 19, No. 6: 1070-1081.
40. Lundberg, Kristina; Balfors, Berit Brokking; Folkeson, L. (2009), “Framework for Environmental Performance Measurement In A Swedish Public Sector Organization”, Journal of Cleaner Production, Vol. 17, No. 11: 1017–1024.
41. Metcalf, Kim R.; Woodall, W. Robert; Hobson, C. M.; Williams, P. L. (1996), “Environmental Performance Measurement: A Case Study”, Environmental Quality Management, Vol. 6, No. 1: 27-37.
42. Moghimi, Masoomeh; Yazdi, Mohammadreza Taghizadeh (2016), “Applying Multi-Criteria Decision-Making (MCDM) Methods for Economic Ranking of Tehran-22 Districts to Establish Financial and Commercial Centers (Case: City of Tehran)”, Urban Economics and Management, Vol. 5, No. 4: 43-55.
43. Myhre, Oddvar; Fjellheim, Kristin; Ringnes, H.; Reistad, T.; Longva, K. S.; Ramos, T. B. (2013), “Development of Environmental Performance Indicators Supported by An Environmental Information System: Application to the Norwegian Defence Sector”, Ecological Indicators, 29, 293–306.
44. Nakıboğlu, Gülsün; Bulğurcu, Berna (2017), “İşletmelerin Çevresel Sürdürülebilirlik Göstergelerine Yönelik Farklı Bir Değerlendirme: Modifiye Edilmiş Dijital Mantık (MDL)”, International Journal of Economic and Administrative Studies, UİK Özel Sayısı, 709-728.
45. Olafsson, Snjolfur; Cook, David; Davidsdottir, B.; Johannsdottir, L. (2014), “Measuring Countries' Environmental Sustainability Performance – A Review and Case Study of Iceland”, Renewable and Sustainable Energy Reviews, Vol. 39: 934–948.
46. Özbek, Aşır; Demirkol, İsa (2018), “Lojistik Sektöründe Faaliyet Gösteren İşletmelerin SWARA ve GİA Yöntemleri İle Analizi”, Kırıkkale Üniversitesi Sosyal Bilimler Dergisi, C. 8, S. 1: 71-86.
47. Özdağoğlu, Aşkın, Yakut, Enis, Bahar, S. (2017), “Machine Selection in a Dairy Product Company with Entropy and SAW Method Integration”, Dokuz Eylül Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, C. 32, S. 1: 341-359.
48. Peker, İskender; Baki, Birdoğan (2011), “Gri İlişkisel Analiz Yöntemiyle Türk Sigortacılık Sektöründe Performans Ölçümü”, International Journal of Economic and Administrative Studies, Vol. 4, No. 7: 1-18.
49. Sarkar, Asis; Panja, S. C., Das, D; Sarkar, B. (2015), “Developing An Efficient Decision Support System For Non-Traditional Machine Selection: An Application of MOORA and MOOSRA”, Production & Manufacturing Research, Vol. 3, No. 1: 324-342.
50. Shahmardan, Amin; Zadeh, Mohammad Hendijani (2013), “An Integrated Approach for Solving A MCDM Problem, Combination of Entropy Fuzzy and F-PROMETHEE Techniques”, Journal of Industrial Engineering and Management, Vol. 6, No. 4: 1124-1138.
51. Şimşek, Ali; Çatır, Ozan; Ömürbek, N. (2015), “TOPSIS Ve MOORA Yöntemleri İle Tedarikçi Seçimi: Turizm Sektöründe Bir Uygulama”, Balıkesir University The Journal of Social Sciences Institute, Vol. 18, No. 33: 133-161.
52. Şişman, Bilal; Eleren, Ali (2013), “En Uygun Otomobilin Gri İlişkisel Analiz ve Electre Yöntemleri ile Seçimi”, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, C. 18, S. 3: 411-429.
53. Ünlü, Ulaş; Yalçın, Neşe; Yağlı, İ. (2017), “Kurumsal Yönetim ve Firma Performansı: TOPSIS Yöntemi ile BİST 30 Firmaları Üzerine Bir Uygulama”, Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, C.19, S. 1: 63-81.
54. Tam, Vivian W.Y; Tam, C. M; Zeng, S. X.; Chan, K. K. (2006), “Environmental Performance Measurement Indicators in Construction”, Building and Environment, Vol. 41: 164-173.
55. Tanç, Ahmet; Gümrah, Abdurrahman (2015), “Sürdürülebilirlik Raporlaması ve Çevresel Performans: Borsa İstanbul’da Bir Uygulama”, İşletme Araştırmaları Dergisi, C. 7, S. 2: 258-273.
56. Tsai, Chih-Hung; Chang, Ching-Liang; Chen, L. (2003), “Applying Grey Relational Analysis to the Vendor Evaluation Model”, International Journal of The Computer, The Internet and Management, Vol. 11, No. 3: 45-53.
57. Vujičić, Momcilo D.; Papić, Milos Z., Blagojević, M. D. (2017), “Comparative Analysis of Objective Techniques for Criteria Weighing in Two MCDM Methods on Example of an Air Conditioner Selection”, Tehnika, Vol. 72, No. 3: 422-429.
58. Wang, Tien-Chin; Lee, Hsien-Da (2009), “Developing a Fuzzy TOPSIS Approach Based on Subjective Weights and Objective Weights”, Expert Systems with Applications, Vol. 6, No. 5: 8980-8985.
59. Wu, Hsing-Hung (2002), “A Comparative Study of Using Grey Relational Analysis in Multiple Attribute Decision Making Problems”, Quality Engineering, Vol. 15, No. 2: 209-217.
60. Yıldırım, Bahadır Fatih; Önder, Emrah (2015), “Çok Kriterli Karar Verme Yöntemleri”, 2. Baskı, Bursa: Dora Yayıncılık.
61. Zadeh, Nazanin Chaharmahali; Kazemi, Roohollah (2016), “The Environmental Performance Evaluation of Ahwaz Pipe Manufacturing Company within the Environmental Management System”, International Journal of Pharmaceutical Research & Allied Sciences, 2016, Vol. 5, No. 3: 413-436.
62. Zhai, Lian-Yin; Khoo, Li-Pheng; Zhong, Z. W. (2009), “Design Concept Evaluation in Product Development Using Rough Sets and Grey Relation Analysis”, Expert Systems with Applications, Vol. 36, No. 3: 7072-7079.
63. Zhang, Hong; Gu, Chao-Lin; Gu, L. W.; Zhang, Y. (2011), “The Evaluation of Tourism Destination Competitiveness by TOPSIS & Information Entropy–A Case in the Yangtze River Delta of China”, Tourism Management, Vol. 32, No. 2: 443-451.
64. Zhang, Xianqi; Wang, Chenbo; Li, E.; Xu, C. (2014), “Assessment Model of Eco Environmental Vulnerability based on Improved Entropy Weight Method”, The Scientific World Journal, 1-7.
65. Zuo, Xuan; Hua, Hui; Dong, Z.; Hao, C. (2017), “Environmental Performance Index at the Provincial Level for China 2006–2011”, Ecological Indicators, Vol. 75: 48-56.