ELECTRE III VE TOPSIS YÖNTEMLERİ İLE ÜLKELERİN İŞ YAPMA KOLAYLIĞINA GÖRE SIRALANMASI

Year 2021, Issue: 50, 382 - 408, 22.06.2021

Sibel Şener Hüdaverdi Bircan

https://doi.org/10.17498/kdeniz.926625

Cited By: 1

Abstract

Karar verme sürecinde, Çok Kriterli Karar Verme yöntemleri, Karar Verici’nin birden fazla kriter kullanmasına izin vererek en iyi alternatiflerin belirlenmesinde kolaylık sağlamaktadır. Çok kriterli bir yapıya sahip olan İş Yapma Kolaylığı Endeksi, ekonomilerin rekabet gücünü artırmak için küçük ve orta büyüklükteki işletmelerin kuruluşlarını ve faaliyetlerini kolaylaştıracak bir iş ortamını sağlayan düzenleyici ve yasal sistemleri incelemek amacıyla oluşturulmuş bir endekstir. Bu çalışmada, ELECTRE III ve TOPSIS yöntemleri kullanılarak iş yapma kolaylığına göre ülke ekonomilerinin en iyiden en kötüye doğru sıralanması amaçlanmıştır. Her iki yöntemin elde ettiği sonuçlar İş Yapma Kolaylığı Endeksi’nin sıralaması ile karşılaştırıldığında, ELECTRE III yönteminin TOPSIS yöntemine göre daha iyi bir performans gösterdiği belirlenmiştir. ELECTRE III yöntemin değişik parametrelerine (farksızlık, tercih ve veto eşikleri) yapılan duyarlılık analizi sonucunda, sıralamanın özellikle farksızlık ve tercih eşiğine duyarlı olduğu, veto eşiğine fazla duyarlı olmadığı gözlemlenmiştir. Her iki yöntem ile elde edilen sıralamalarda en iyi ve en kötü ülke sıralaması doğru tahmin edilmiştir. Bu sonuçlara göre, Yeni Zelanda en iyi iş düzenleme ortamına sahip ülke, Güney Sudan, Kongo, Libya ve Eritre ise en kötü iş düzenleme ortamına sahip son dört ülke olarak bulunmuştur. Ayrıca TOPSIS, ELECTRE III yönteminin başlangıç parametreleri ile elde edilen sıralamasıyla karşılaştırıldığında, her iki yöntemin 17 ülkeyi aynı sırada sıraladığı tespit edilmiştir.

Keywords

Çok Kriterli Karar Verme, ELECTRE III, TOPSIS, İş Yapma Kolaylığı Endeksi, Eşik Değer

SEQUENCE OF COUNTRIES ACCORDING TO EASE OF DOING BUSINESS WITH ELECTRE III AND TOPSIS METHODS

Abstract

In the decision-making process, Multi-Criteria Decision Making methods allow the Decision Maker to use more than one criterion, making it easier to identify the best alternatives. The Ease of Doing Business Index, which has a multi-criteria structure, is an index designed to examine the regulatory and legal systems that provide a business environment that will facilitate the creation and operation of small and medium-sized enterprises in order to increase the competitiveness of economies. In this study, it is aimed to rank the economies of the countries from the best to the worst according to the ease of doing business using ELECTRE III and TOPSIS methods. When the results obtained by both methods were compared with the ranking of the Ease of Doing Business Index, it was determined that the ELECTRE III method performed better than the TOPSIS method. As a result of the sensitivity analysis performed on various parameters of the ELECTRE III method (thresholds of indifference, preference and veto), it was noticed that the rating is especially sensitive to the thresholds of indifference and preference, but not too sensitive to the threshold of veto. In the rankings obtained by both methods, the best and worst country rankings were estimated correctly. According to these results, New Zealand was found to be the country with the best business regulatory environment, while South Sudan, Congo, Libya and Eritrea were the last four countries with the worst business regulatory environment. In addition, when the TOPSIS, ELECTRE III methods were compared with the rankings obtained using the initial parameters, it was determined that both methods ranked 17 countries in the same order.

Keywords

Multi-Criteria Decision Making, ELECTRE III, TOPSIS, Ease of Doing Business Index, Threshold

РАНЖИРОВАНИЕ ГОСУДАРСТВ С УПРОЩЁННЫМЫ РЕГУДЯЦИЯМИ ПО ВЕДЕНИЮ БИЗНЕСА С ПОМОЩЬЮ ЭЛЕКТРЕ III И ТОПСИСНЫХ МЕТОДОВ

Abstract

Упрощённые и разнообразные критерии позволяют выбрать более одного метода в процессе принятия решении. Индекс упрощения для ведения бизнеса, имеющий многокритериальную структуру, вводится с целю изучения нормативных и правовых систем, которые обеспечивают бизнес-среду, способствующее созданию и деятельности малых и средних предприятий для повышения конкурентоспособности экономики. Целью данного исследования является ранжирование экономики стран от лучшей к худшему в соответствии с легкостью ведения бизнеса с использованием методов ELECTRE III и TOPSIS. По результатам исследования из обоих методов и сравнения их с рейтингом индекса легкости ведения бизнеса, было установлено, что метод ELECTRE III работает лучше, чем метод TOPSIS. В результате анализа чувствительности, выполненного по различным параметрам метода ELECTRE III (пороги безразличия, зоны предпочтения и вето), было замечено, что ранжирование особенно чувствительно к порогам безразличия и зоне предпочтения, но не слишком чувствительно к зоне вето. В рейтингах, полученных обоими методами, точно оценивались лучшие и худшие страны. Согласно этим результатам, Новая Зеландия была признана страной с наилучшей нормативно-правовой средой для ведения бизнеса, в то время как Южный Судан, Конго, Ливия и Эритрея были последними четырьмя странами с наихудшей нормативно-правовой средой для ведения бизнеса. При сравнении методов TOPSIS, ELECTRE III с рейтингом из исходных параметров, стало очевидно, с обеими методами в одинаковом порядке было одинаково ранжировано все 17 государств.

Keywords

принятие решений по нескольким критериям, ELECTRE III, TOPSIS, индекс упрощения по ведению бизнеса, порог

References

• Akgün, İ. ve Erdal, H. (2019). Solving an ammunition distribution network design problem using multi-objective mathematical modeling, combined AHP-TOPSIS, and GIS. Computers & Industrial Engineering, 129, 512-528.
• Albahria, A.S., Hamid, R. A., Albahri, O. S. ve Zaidan, A. A. (2021). Detection-based prioritisation: Framework of multi-laboratory characteristics for asymptomatic COVID-19 carriers based on integrated Entropy–TOPSIS methods. Artificial Intelligence in Medicine 111, 101983.
• Alp, S. ve Engin, T. (2011). Trafik kazalarının nedenleri ve sonuçları arasındaki ilişkinin TOPSIS ve AHP yöntemleri kullanılarak analizi ve değerlendirilmesi. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, 10 (19), 65-87.
• Barros, C. P. ve Wanke, P. (2015). An analysis of African airlines efficiency with two-stage TOPSIS and neural networks. Journal of Air Transport Management, 44–45, 90-102.
• Bayyurt, N. (2013). Ownership Effect on Bank's Performance: Multi Criteria Decision Making Approaches on Foreign and Domestic Turkish Banks, Procedia - Social and Behavioral Sciences, 99, 919 – 928.
• Bilbao-Terol, A., Arenas-Parra, M., Cañal-Fernández, V. ve Antomil-Ibias, J. (2014). Using TOPSIS for assessing the sustainability of government bond funds. Omega, 49, 1-17.
• Boer, L. B., Wegen, L. ve Telgen, J. (1998). Outranking methods in support of supplier selection. European Journal of Purchasing & Supply Management, 4(2-3), 109-118.
• Borajee, M. ve Haji, Y. S. (2011). Using the AHP-ELECTREIII integrated method in a competitive profile matrix. 2011 International Conference on Financial Management and Economics IPEDR, 11, Singapore.
• Buchanan, J., Sheppard, P. ve Lamsade, D. V. (1999). Project ranking using ELECTRE III. Department of Management Systems, 24 January 1999.
• Cavallaro, F. (2010). A comparative assessment of thin-film photovoltaic production processes using the ELECTRE III method. Energy Policy, 38, 463–474.
• Chavira, D.A.G., Lopez, J.C.L., Noriega, J.J.S., Valenzuela, O.A. ve Carrillo, P.A.A. (2017). A credit ranking model for a parafinancial company based on the ELECTRE-III method and a multiobjective evolutionary algorithm. Applied Soft Computing, 60, 190–201.
• Chen, Z.-S., Zhang, X., Rodríguez, R. M., Pedryczc, W. ve Martínez, L. (2021). Expertise-based bid evaluation for construction-contractor selection with generalized comparative linguistic ELECTRE III. Automation in Construction, 125, 103578.
• Demireli, E. (2010). TOPSIS çok kriterli karar verme sistemi: Türkiye’deki kamu bankaları üzerine bir uygulama. Girişimcilik ve Kalkınma Dergisi, 5(1), 101-112.
• Díaz, H. ve Soares, C. G. (2021). A Multi-Criteria Approach to Evaluate Floating Offshore Wind Farms Siting in the Canary Islands (Spain). Energies, 14(4), 865, 1-18.
• Doing Business (2017). A World Bank Group Flagship Report. Equal Opportunity for All, 14. edition.
• Doing Business (2015). A World Bank Group Flagship Report. Going Beyond Efficiency, 12.edition.
• Dortaj, A., Maghsoudy, S., Ardejani, F. D. ve Eskandari, Z. (2020). Locating suitable sites for construction of subsurface dams in semiarid region of Iran: using modified ELECTRE III. Sustainable Water Resources Management, 6:7, https://doi.org/10.1007/s40899-020-00362-2.
• Ebrahimi, J., Moradi, H. R. ve Chezgi, J. (2021). Prioritizing suitable locations for underground dam construction in south east of Bushehr Province. Research Square, 1, 1-26. Eraslan, S. (2015). A decision making method via TOPSIS on soft sets. ISSN: 1304-7981, Journal of New Results in Science, 4(8), 57-71.
• Eray, E. (2015). İnşaat Sektöründe Tedarikçi Seçiminde Kullanılan Çok Amaçlı Karar Destek Yöntemlerinin Karşılaştırılması. Yüksek Lisans Tezi, İstanbul Teknik Üniversitesi Fen Bilimleri Enstitüsü, İstanbul.
• Figueira, J. R., Mousseau, V. ve Roy, B. (2003). ELECTRE Methods. Chapter 1. Erişim adresi https://pdfs.semanticscholar.org/b4ac/6cfbd4878f652079900ed2b6dea4565cda5c.pdf,
• García-Cascales, M.S. ve Lamata, M.T. (2012). On rank reversal and TOPSIS method. Mathematical and Computer Modelling, 56, 123–132.
• Giannoulis, C. ve Ishizaka, A. (2010). A Web-based decision support system with ELECTRE III for a personalised ranking of British universities. Decision Support Systems, 48(3), 488–497.
• Gül, Ş. ve Fırat, M. (2021). TOPSIS ve MAUT Yöntemleri ile İçmesuyu Dağıtım Sistemlerinde Rehabilitasyon Önceliğinin Belirlenmesi. Fırat Üniversitesi Müh. Bil. Dergisi, 33(1), 27-38, 2021.
• Hobbs, B.F. ve Horn, G.T.F. (1997). Building public confidence in energy planning: a multimethod MCDM approach to demand-side planning at BC gas. Energy Policy, 25, 3, 357–375.
• Hokkanen, J. ve Salminen, P. (1997). Choosing a solid waste management system using multicriteria decision analysis. European Journal of Operational Research, 98(1), 19-36.
• Hwang, C.L. ve Yoon, K. (1981). Multiple attribute decision making: Methods and applications. A State-of-the-Art Survey. Springer-Verlag, Berlin. Erişim adresi https://books.google.com.tr/books.
• Kabadayı,N. ve Çakır Esen, T. E. (2021). Gri Temelli TOPSIS Yöntemi ile Depo Yeri Seçimi. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, 9(1), 169–184.
• Keleş, M. K. ve Tunca, M. Z. (2019a). ELECTRE Yöntemi İle Ankara Bölgesinde İnovatif ve Girişimci İşletmeler İçin Teknokent Seçimi. Finans Politik & Ekonomik Yorumlar, 648, 143-180.
• Keleş, M. K. (2019b). Entropi Temelli ELECTRE III Yöntemi İle B Segmenti Otomobil Markalarının Sıralanması. Süleyman Demirel Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 33, 29-50.
• Kokaraki, N., Hopfe, C. J., Robinson, E. ve Nikolaidou, E. (2019). Testing the reliability of deterministic multi-criteria decision-making methods using building performance simulation. Renewable and Sustainable Energy Reviews, 112, 991–1007.
• Konstantinos, I., Georgios, T. ve Garyfalos, A. (2019). A Decision Support System methodology for selecting wind farm installation locations using AHP and TOPSIS: Case study in Eastern Macedonia and Thrace region, Greece. Energy Policy, 132, 232-246.
• Kou, G., Lu, Y., Peng, Y. ve Shi, Y. (2012). Evaluation of Classification Algorithms Using MCDM and Rank Correlatıon. International Journal of Information Technology & Decision Making, 11(1), 197-225.
• Kumar, R. Padhi, S. S. ve Sarkar, A. (2019). Supplier selection of an Indian heavy locomotive manufacturer: An integrated approach using Taguchi loss function, TOPSIS, and AHP. IIMB Management Review, 31(1), 78-90.
• Liu, M., Shao, Y., Yu, C. ve Yu, J. (2020). A Heterogeneous QoS-Based Cloud Service Selection Approach Using Entropy Weight and GRA-ELECTRE III. Mathematical Problems in Engineering, Volume 2020, 1-17, https://doi.org/10.1155/2020/1536872.
• Mahmoudi, M., Aydi, A. ve Ibrahim, H. (2021). Site selection for artificial recharge with treated wastewater with the integration of multi-criteria evaluation and ELECTRE III. Environ Sci Pollut Res, 11356-021-12354-6.
• Marzouk, M. M. (2011). ELECTRE III model for value engineering applications. Automation in Construction, 20(5), 596–600.
• Mela, K., Tiainen, T. ve Heinisuo, M. (2012). Comparative study of multiple criteria decision making methods for building design. Advanced Engineering Informatics, 26, 716–726.
• Montazer, G. A., Saremi, H. Q. ve Ramezani, M. (2009). Design a new mixed expert decision aiding system using fuzzy ELECTRE III method for vendor selection. Expert Systems with Applications, 36(8), 10837–10847.
• Oktem, R. ve Ergül, N. (2012). Testing ELECTRE-III Method in Stock Selection. Journal of Money, Investment and Banking ISSN, 1450-288X, 24.
• Özbek, A. (2016). BİM Mağazalar Zincirinin 2008-2015 Dönemi Finansal Performansinin Electre III Yöntemi İle Ölçümü. Kırıkkale Üniversitesi Sosyal Bilimler Dergisi, 6(2), 273-290.
• Özbey, Ö. (2012). Interactıve Multi Kriteria Decision Making using a tchebycheff or Hybrid Utility Function and Predicted Strength of preferences. Doctor of Phılosophy, The State Unıversıty of New York at Buffalo, Industrial and Systems Engineering, 5-6.
• Papadopoulos, A. ve Karagiannidis, A. (2008). Application of the multi-criteria analysis method ELECTRE III for the optimisation of decentralised energy systems. Omega, 36(5), 766 – 776.
• Peng, H., Shen, K., He, S., Zhang, H. ve Wang, J. (2019). Investment risk evaluation for new energy resources: An integrated decision support model based on regret theory and ELECTRE III. Energy Conversion and Management, 183, 332–348.
• Ranjbar, H. R. ve Nekooie, M. A. (2018). An improved hierarchical fuzzy TOPSIS approach to identify endangered earthquake-induced buildings. Engineering Applications of Artificial Intelligence, 76, 21-39.
• Raju, K. S. ve Duckstein, L. (2004). Integrated application of cluster and multicriterion analysis for ranking water resources planning strategies: a case study in Spain. Journal of Hydroinformatics, 6(4), 295-307.
• Rogers, M. ve Bruen, M. (1998a). Choosing realistic values of indifference, preference and veto thresholds for use with environmental criteria within ELECTRE. European Journal of Operational Research, 107(3), 542-551.
• Rogers, M. ve Bruen, M. (1998b). A new system for weighting environmental criteria for use within ELECTRE III. European Journal of Operational Research, 107(3), 552-563.
• Roszkowska, E. (2011). Multi-criteria decision making models by applying the TOPSIS method to crisp and intervaldata. Mult. Criteria Decis. Mak. Univ. Econ. Katow., 6, 200–230.
• Roy, B. (1991). The outranking approach and the foundations of ELECTRE methods. Theory and Decision, 31, 49-73.
• Roy, B. (1968). Classement et choix en presence de points de vue multiples (la methode ELECTRE). Revue Francaise d’Automatique Information et Research Operationelle, 57-75.
• Roy, B. ve Bouyssou, D. (1986). Comparison of two decision-aid models applied to a nuclear power plant siting example. European Journal of Operational Research, 25(2), 200-215.
• Salminen, P., Hokkanen, J. ve Lahdelma, R. (1998). Comparing multicriteria methods in the context of environmental problems. European Journal of Operational Research, 104, 485-496.
• Saracoglu, B. O. (2015). An experimental research study on the solution of a private small hydropower plant investments selection problem by ELECTRE III/IV, Shannon’s Entropy, and Saaty’s Subjective Criteria Weighting. Hindawi Publishing Corporation Advances in Decision Sciences, ArticleID 548460, 20.
• Selmi, M., Kormi, T. ve Bel Hadj Ali, N. (2016). Comparison of multi-criteria decision methods through a ranking stability index. Int. J. Operational Research, 27, 1/2.
• Supçiller, A. A. ve Çapraz, O. (2011). AHP-TOPSIS yöntemine dayalı tedarikçi seçimi uygulaması. Ekonometri ve İstatistik (12. Uluslararası Ekonometri, Yöneylem Araştırması, İstatistik Sempozyumu Özel Sayısı), 13, 1–22.
• Şimşek, A., Çatır, O., ve Ömürbek, N. (2015). TOPSIS ve Moora yöntemleri ile tedarikçi seçimi: turizm sektöründe bir uygulama. Balıkesir University The Journal of Social Sciences Institute. 18(33), 133-161.
• Tam, C. M., Tong, T. K. L. ve Lau, C. T. (2003). ELECTRE III in evaluating performance of construction plants: case study on concrete vibrators. Construction Innovation; 3(1), 45-61.
• Tavana, M. ve Hatami-Marbini, A. (2011). A group AHP-TOPSIS framework for human spaceflight mission planning at NASA. Expert Systems with Applications, 38(11), 13588-13603.
• Tervonen, T., Figueira, J., Lahdelma, R. ve Salminen P. (2005). An inverse approach for ELECTRE III. Instituto de Engenharia de Sistemas e Computadores de Coimbra INESC - Coimbra, Revised(2nd), 20, 1645-2631.
• Tomasz, M. M. (2010). Multicriteria aided design of integrated heating-cooling energy systems in buildings. ISSN:1047-3289 Journal of the Air & Waste Management Association. 60(8), 949–958.
• Tscheikner-Gratl F., Egger P., Rauch W. ve Kleidorfer M. (2017). Comparison of multi-criteria decision support methods for integrated rehabilitation prioritization. Water, 9(2), 68.
• Ulubeyli, S. ve Manisalı, E. (2015). İnşaat Makineleri Alımında Çok Ölçütlü Karar Verme Modeli. 3. Yapı İşletmesi Kongresi, Bildiriler Kitabı, 172-182.
• Vasegaard, A. E., Picard, M., Hennart, F., Nielsen, P. ve Saha, S. (2020). Multi Criteria Decision Making for the Multi-Satellite Image Acquisition Scheduling Problem. Sensors, 20(5), 1242.
• Vasto-Terrientes, L. D., Kumar, V., Chao, T. C. ve Valls, A. (2016). A decision support system to find the best water allocation strategies in a Mediterranean river basin in future scenarios of global change. Journal of Experimental & Theoretical Artificial Intelligence, 28(1–2), 331–350.
• Yürekli, H. (2008). Taarruz Helikopterleri Seçiminde ELECTRE Yönteminin Kullanılması. Doktora Tezi, İstanbul Üniversitesi Sosyal Bilimler Enstitüsü, İstanbul.
• Zhang, K.ve Shi, Q. (2010). Safety Evaluation in Power Supply Enterprises Using the ELECTRE III and TOPSIS Methods. 2. International Workshop on Intelligent Systems and Applications.
• Xu, B. ve Ouenniche, J. (2012). Performance evaluation of competing forecasting models: A multidimensional framework based on MCDA. Expert Systems with Applications, 39(9), 8312–8324.