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An Analysis of the Current Cost of Living of EU Countries with a COPRAS-ARAS Hybrid MCDM Model

Yıl 2023, Cilt: 25 Sayı: 1, 198 - 214, 28.03.2023
https://doi.org/10.32709/akusosbil.1058594

Öz

This study aimed to measure the current cost of living analysis of European Union (EU) countries by using Multi-Criteria Decision Making (MCDM) methods. The data of the research was obtained from a site called Numbeo and the data covers mid-2021. 27 alternatives and five criteria (rent index, cost of living + rent index, grocery index, restaurant price index, local purchasing power index) were included in the scope of the study. While the Entropy method was used to weight the criteria, the COPRAS-ARAS integrated model was used to evaluate the alternatives. The robustness and reliability of the results were determined by applying sensitivity analysis. In this context, first, the criteria were equally weighted and the effect of criteria weights on the results was examined. In the second stage, the results obtained with the Entropy-based COPRAS-ARAS integrated model were compared with the Entropy-based SAW, PIV, ROV, CoCoSo and MARCOS methods. In the last step, the results obtained by various MCDM methods were turned into a rational final ranking using the Copeland method. It was concluded that, Romania was the cheapest country in terms of current cost of living, while Luxembourg was the most expensive country. This is the first study to focus the current cost of living analysis with MCDM methods and it is thought that this study will fill the gap in the literature.

Kaynakça

  • Aldalou, E. ve Perçin, S. (2020). Application of integrated fuzzy MCDM approach for financial performance evaluation of Turkish technology sector. International Journal of Procurement Management, 13(1), 1-23.
  • Ayyıldız E. ve Demirci, E. (2018). Türkiye'de yer alan şehirlerin yaşam kalitelerinin SWARA entegreli TOPSIS yöntemi ile belirlenmesi. Pamukkale University Journal of Social Sciences Institute, 30, 67-87.
  • Balali, A., Valipour, A., Edwards, R. ve Moehler, R. (2021). Ranking effective risks on human resources threats in natural gas supply projects using ANP-COPRAS method: Case study of Shiraz. Reliability Engineering & System Safety, 208(2021), 1-9.
  • Balki, M. K., Erdoğan, S., Aydın, S. ve Sayin, C. (2020). The optimization of engine operating parameters via SWARA and ARAS hybrid method in a small SI engine using alternative fuels. Journal of Cleaner Production, 258(2020), 1-12.
  • Büyüközkan, G. ve Güler, M. (2020). Smart watch evaluation with integrated hesitant fuzzy linguistic SAW-ARAS technique. Measurement, 153(2020), 1-14.
  • Clausius, R. (1865). Ueber Verschiedene für die Anwendung Bequeme Formen der Hauptgleichungen der Mechanischen Wärmetheorie: Vorgetragen in der Naturforsch. Gesellschaft den 24.
  • Çağlar, A. (2020). İllerin yaşam kalitesi: Türkiye istatistik kurumu verileriyle veri zarflama analizi’ne dayalı bir endeks. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 15(3), 875-902.
  • Çınaroglu, E. (2021). CRITIC Temelli CODAS ve ROV Yöntemleri ile AB Ülkeleri Yasam Kalitesi analizi. Bingol University Journal of Economics and Administrative Sciences, 5(1), 337-364.
  • Diewert, W.E. (1990). The theory of the cost-of-living index and the measurement of welfare change, Contributions to Economic Analysis, 196(1990), 79–147.
  • Dissanayake, D. M. S. L. B., Morimoto, T., Murayama, Y., Ranagalage, M. ve Perera, E. N. C. (2020). Analysis of life quality in a tropical mountain city using a multi-criteria geospatial technique: A case study of Kandy City, Sri Lanka. Sustainability, 12(7), 2918.
  • Ecer, F. (2020). Çok Kriterli Karar Verme, Geçmişten Günümüze Kapsamlı Bir Yaklaşım. Ankara: Seçkin Yayınevi.
  • Ecer, F. (2021). A consolidated MCDM framework for performance assessment of battery electric vehicles based on ranking strategies. Renewable and Sustainable Energy Reviews, 143(2021), 1-19.
  • Eş, A. (2013). Çok Kriterli Karar Verme Yöntemleriyle Türkiye Ekonomisinde Yer Alan Sektörlerin Finansal Performanslarının Karşılaştırılması (Yayınlanmış Doktora Tezi). Abant İzzet Baysal Üniversitesi, Bolu.
  • George, J., Badoniya, P. ve Xavier, J. F. (2021). Hybrid Optimisation for Supply Chain Management: A Case of Supplier Selection by CRITIC, ARAS and TOPSIS Techniques. P. Agarwal, L. Bajpai, C. P. Singh, K. Gupta, J. P. Davim (Eds). Manufacturing and Industrial Engineering içinde (ss. 161-174). CRC Press.
  • Ghenai, C., Albawab, M. ve Bettayeb, M. (2020). Sustainability indicators for renewable energy systems using multi-criteria decision-making model and extended SWARA/ARAS hybrid method. Renewable Energy, 146, 580-597.
  • Goswami, S. S. ve Behera, D. K. (2021). Implementation of ENTROPY-ARAS decision making methodology in the selection of best engineering materials. Materials Today: Proceedings, 38, 2256-2262.
  • Goswami, S. S., Behera, D. K. ve Mitra, S. (2020). Supplier Selection Problem by Applying Additive Ratio Assessment (ARAS) Methodology. International Conference on Thermal Engineering and Management Advances, Singapore.
  • Goswami, S. S., Behera, D. K., Afzal, A., Razak Kaladgi, A., Khan, S. A., Rajendran, P., ... & Asif, M. (2021). Analysis of a robot selection problem using two newly developed hybrid MCDM models of TOPSIS-ARAS and COPRAS-ARAS. Symmetry, 13(8), 1331.
  • Goswami, S. ve Mitra, S. (2020). Selecting the best mobile model by applying AHP-COPRAS and AHP-ARAS decision making methodology. International Journal of Data and Network Science, 4(1), 27-42.
  • Hezer, S., Gelmez, E. ve Özceylan, E. (2021). Comparative analysis of TOPSIS, VIKOR and COPRAS methods for the COVID-19 Regional Safety Assessment. Journal of infection and public health, 14(6), 775-786.
  • Hoan, P. ve Ha, Y. (2021). ARAS-FUCOM approach for VPAF fighter aircraft selection. Decision Science Letters, 10(1), 53-62.
  • https://www.numbeo.com/cost-of-living/rankings_current.jsp, (Erişim tarihi: 15.11.2021)
  • Kamali Saraji, M., Streimikiene, D. ve Kyriakopoulos, G. L. (2021). Fermatean fuzzy CRITIC-COPRAS method for evaluating the challenges to industry 4.0 adoption for a sustainable digital transformation. Sustainability, 13(17), 1-20.
  • Kandpal, V. (2021). Determining interlinkages between the measures of financial literacy: An MCDM approach. Journal of Public Affairs, 1-8.
  • Khalilzadeh, M., Ghasemi, P., Afrasiabi, A. ve Shakeri, H. (2021). Hybrid fuzzy MCDM and FMEA integrating with linear programming approach for the health and safety executive risks: a case study. Journal of Modelling in Management, 16(4), 1025-1053.
  • Küçükal, N. T., Ayaş, P., Köse, D. ve Kaya, G. K. (2021). Çok kriterli karar verme yöntemlerinin karşılaştırmalı kullanımı ile Türkiye’deki illerin yaşam kalitelerinin değerlendirilmesi. Gazi İktisat ve İşletme Dergisi, 7(2), 150-168.
  • Liu, G., Fan, S., Tu, Y. ve Wang, G. (2021). Innovative Supplier Selection from Collaboration Perspective with a Hybrid MCDM Model: A Case Study Based on NEVs Manufacturer. Symmetry, 13(1), 1-28.
  • Mostafaeipour, A., Dehshiri, S. S. H., Dehshiri, S. J. H., Almutairi, K., Taher, R., Issakhov, A. ve Techato, K. (2021). A thorough analysis of renewable hydrogen projects development in Uzbekistan using MCDM methods. International Journal of Hydrogen Energy, 46(61), 31174-31190.
  • Naderi, H., Shahosseini, H. ve Jafari, A. (2013). Evaluation MCDM multi-disjoint paths selection algorithms using fuzzyCopeland ranking method, International Journal of Communication Networks and Information Security, 5(1), 59– 67.
  • Narayanamoorthy, S., Ramya, L., Kalaiselvan, S., Kureethara, J. V. ve Kang, D. (2021). Use of DEMATEL and COPRAS method to select best alternative fuel for control of impact of greenhouse gas emissions. Socio-Economic Planning Sciences, 76, 1-20.
  • Nweze, S. ve Achebo, J. (2021). Comparative Enhancement of Mild Steel Weld Mechanical Properties for Better Performance Using COPRAS–ARAS Method. European Journal of Engineering and Technology Research, 6(2), 70-74.
  • Orakçı, E. ve Özdemir, A. (2017). Telafi edici çok kriterli karar verme yöntemleri ile Türkiye ve AB ülkelerinin insani gelişmişlik düzeylerinin belirlenmesi. Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 19(1), 61-74.
  • Ozkaya, G., Timor, M. ve Erdin, C. (2021). Science, Technology and Innovation Policy Indicators and Comparisons of Countries through a Hybrid Model of Data Mining and MCDM Methods. Sustainability, 13(2), 1-49.
  • Özbek, A. (2019). Türkiye’deki İllerin Edas ve WASPAS Yöntemleri ile Yaşanabilirlik Kriterlerine Göre Siralanmasi. Kırıkkale Üniversitesi Sosyal Bilimler Dergisi, 9(1), 177-200.
  • Pérez-Gladish, B., Ferreira, F. A. ve Zopounidis, C. (2021). MCDM/A studies for economic development, social cohesion and environmental sustainability: introduction. International Journal of Sustainable Development & World Ecology, 28(1), 1-3.
  • Sahin, M. (2021). Location selection by multi-criteria decision-making methods based on objective and subjective weightings. Knowledge and Information Systems, 63(8), 1991-2021.
  • Seyhan, A. G. D. N. ve Seyhan, A. G. B. (2021). COVID-19 Salgın Sürecinde AB Ülkelerindeki Yaşam Kalitesinin Çok Kriterli Karar Verme ile Değerlendirilmesi. Journal of Social Research and Behavioral Sciences, 7(13), 158-180.
  • Shannon, C.E. (1948). A Mathematical Theory Of Communication.Bell System Technical Journal, 27, 379-423.
  • Štirbanović, Z., Stanujkić, D., Miljanović, I. ve Milanović, D. (2019). Application of MCDM Methods for Flotation Machine Selection. Minerals Engineering, 137, 140-146.
  • Torkayesh, A. E. ve Torkayesh, S. E. (2021). Evaluation of information and communication technology development in G7 countries: An integrated MCDM approach. Technology in Society, 66, 1-9.
  • Triantaphyllou, E. ve Sánchez, A. (1997). A Sensitivity Analysis Approach for Some Deterministic Multi-Criteria Decision-Making Methods. Decision Sciences, 28(1), 151–194.
  • Triplett, J. E. (2001). Should the Cost-of-living Index Provide the Conceptual Framework for a Consumer Price Index?. The Economic Journal, 111(472), 311–334.
  • Ulutaş, A. ve Karaköy, C. (2019). An analysis of the logistics performance index of EU countries with an integrated MCDM model. Economics and Business Review, 5(4), 49-69.
  • Ünvan, Y. A. ve Ergenç, C. (2021). Financial Performance Analysis with the Fuzzy COPRAS and Entropy-COPRAS Approaches. Computational Economics, 1-29.
  • Valipour, A., Sarvari, H. ve Tamošaitiene, J. (2018). Risk assessment in PPP projects by applying different MCDM methods and comparative results analysis. Administrative Sciences, 8(4), 1-17.
  • Wang, T. C. ve Lee, H. D. (2009). Developing a Fuzzy TOPSIS Approach Based on Subjective Weights and Objective Weights. Expert systems with applications, 36(5), 8980-8985.
  • Wang, Y. M. ve Luo, Y. (2010). Integration of Correlations with Standard Deviations for Determining Attribute Weights in Multiple Attribute Decision Making. Mathematical and Computer ModellingVolume, 51(1–2), 1–12.
  • Wen, Z.; Liao, H. ve Zavadskas, E.K. (2020). MACONT: Mixed aggregation by comprehensive normalization technique for multi-criteria analysis. Informatica, 31, 857–880
  • Wu, Z., Sun, J., Liang, L. ve Zha, Y. (2011). Determination of Weights for Ultimate Cross Efficiency Using Shannon Entropy.Expert Systems With Applications, 38(5),5162–5165.
  • Yıldız, A., Ayyıldız, E., Gümüş, A. T. ve Özkan, C. (2019). Ülkelerin yaşam kalitelerine göre değerlendirilmesi için hibrit pisagor bulanık AHP-TOPSIS metodolojisi: Avrupa Birliği örneği. Avrupa Bilim ve Teknoloji Dergisi, 17, 1383-1391.
  • Yuan, Y., Xu, Z. ve Zhang, Y. (2021). The DEMATEL–COPRAS hybrid method under probabilistic linguistic environment and its application in Third Party Logistics provider selection. Fuzzy Optimization and Decision Making, 1-20.
  • Zavadskas, E. K. ve Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision-making. Technol Econ Dev Econ, 16(2):159–72.
  • Zavadskas, E. K., Kaklauskas, A. ve Sarka, V. (1994). The new method of multicriteria complex proportional assessment of projects. Technol Econ Dev Econ, 1(3):131–9.
  • Zavadskas, E. K., ve Podvezko, V. (2016). Integrated determination of objective criteria weights in MCDM. International Journal of Information Technology Decision Making, 15(02), 267-283.
  • Zhang,H., Gu, C., Gu, L. ve Zhang, Y. (2011). The Evaluation of Tourism Destination Competitiveness by TOPSIS & Information Entropy - A Case in the Yangtze River Delta of China. Tourism Management, 32(2), 443-451.

COPRAS-ARAS Hibrit ÇKKV Modeli İle AB Ülkelerinin Mevcut Yaşam Maliyetinin Bir Analizi

Yıl 2023, Cilt: 25 Sayı: 1, 198 - 214, 28.03.2023
https://doi.org/10.32709/akusosbil.1058594

Öz

Bu çalışmada, Avrupa Birliği (AB) ülkelerinin mevcut yaşam maliyeti analizinin Çok Kriterli Karar Verme (ÇKKV) yöntemleri kullanılarak ölçülmesi amaçlanmıştır. Araştırma için gerekli veriler Numbeo adlı siteden elde edilmiştir ve 2021 yıl ortasını kapsamaktadır. Çalışma kapsamına 27 alternatif ve beş kriter (kira endeksi, yaşam maliyeti+kira endeksi, bakkaliye endeksi, restaurant fiyat endeksi, yerel satın alma gücü endeksi) dâhil edilmiştir. Entropy yöntemi kriterlerin ağırlıklandırılması için kullanılırken, COPRAS-ARAS entegre modeli alternatifleri değerlendirmek için kullanılmıştır. Sonuçların sağlamlığı ve güvenilirliği duyarlılık analizi uygulanarak test edilmiştir. Bu kapsamda, ilk olarak kriterlere eşit ağırlık verilmiş ve kriter ağırlıklarının sonuçlar üzerindeki etkisi incelenmiştir. İkinci aşamada ise Entropy temelli COPRAS-ARAS entergre modeli ile elde edilen sonuçlar Entropy temelli SAW, PIV, ROV, CoCoSo ve MARCOS yöntemleri ile elde edilen sonuçlar ile karşılaştırılmıştır. Son adımda ise çeşitli ÇKKV yöntemleri ile elde edilen sonuçlar Copeland yöntemi kullanılarak rasyonel nihai bir sıralama haline getirilmiştir. Çalışma sonunda, mevcut yaşam maliyeti açısından en ucuz ülke Romanya olarak tespit edilirken, Lüksemburg en pahalı ülke olarak tespit edilmiştir. Bu çalışma, mevcut yaşam maliyeti analizini ÇKKV yöntemleri ile ele alan ilk çalışma olması bakımından önemlidir ve çalışmanın literatürdeki boşluğu dolduracağı düşünülmektedir.

Kaynakça

  • Aldalou, E. ve Perçin, S. (2020). Application of integrated fuzzy MCDM approach for financial performance evaluation of Turkish technology sector. International Journal of Procurement Management, 13(1), 1-23.
  • Ayyıldız E. ve Demirci, E. (2018). Türkiye'de yer alan şehirlerin yaşam kalitelerinin SWARA entegreli TOPSIS yöntemi ile belirlenmesi. Pamukkale University Journal of Social Sciences Institute, 30, 67-87.
  • Balali, A., Valipour, A., Edwards, R. ve Moehler, R. (2021). Ranking effective risks on human resources threats in natural gas supply projects using ANP-COPRAS method: Case study of Shiraz. Reliability Engineering & System Safety, 208(2021), 1-9.
  • Balki, M. K., Erdoğan, S., Aydın, S. ve Sayin, C. (2020). The optimization of engine operating parameters via SWARA and ARAS hybrid method in a small SI engine using alternative fuels. Journal of Cleaner Production, 258(2020), 1-12.
  • Büyüközkan, G. ve Güler, M. (2020). Smart watch evaluation with integrated hesitant fuzzy linguistic SAW-ARAS technique. Measurement, 153(2020), 1-14.
  • Clausius, R. (1865). Ueber Verschiedene für die Anwendung Bequeme Formen der Hauptgleichungen der Mechanischen Wärmetheorie: Vorgetragen in der Naturforsch. Gesellschaft den 24.
  • Çağlar, A. (2020). İllerin yaşam kalitesi: Türkiye istatistik kurumu verileriyle veri zarflama analizi’ne dayalı bir endeks. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 15(3), 875-902.
  • Çınaroglu, E. (2021). CRITIC Temelli CODAS ve ROV Yöntemleri ile AB Ülkeleri Yasam Kalitesi analizi. Bingol University Journal of Economics and Administrative Sciences, 5(1), 337-364.
  • Diewert, W.E. (1990). The theory of the cost-of-living index and the measurement of welfare change, Contributions to Economic Analysis, 196(1990), 79–147.
  • Dissanayake, D. M. S. L. B., Morimoto, T., Murayama, Y., Ranagalage, M. ve Perera, E. N. C. (2020). Analysis of life quality in a tropical mountain city using a multi-criteria geospatial technique: A case study of Kandy City, Sri Lanka. Sustainability, 12(7), 2918.
  • Ecer, F. (2020). Çok Kriterli Karar Verme, Geçmişten Günümüze Kapsamlı Bir Yaklaşım. Ankara: Seçkin Yayınevi.
  • Ecer, F. (2021). A consolidated MCDM framework for performance assessment of battery electric vehicles based on ranking strategies. Renewable and Sustainable Energy Reviews, 143(2021), 1-19.
  • Eş, A. (2013). Çok Kriterli Karar Verme Yöntemleriyle Türkiye Ekonomisinde Yer Alan Sektörlerin Finansal Performanslarının Karşılaştırılması (Yayınlanmış Doktora Tezi). Abant İzzet Baysal Üniversitesi, Bolu.
  • George, J., Badoniya, P. ve Xavier, J. F. (2021). Hybrid Optimisation for Supply Chain Management: A Case of Supplier Selection by CRITIC, ARAS and TOPSIS Techniques. P. Agarwal, L. Bajpai, C. P. Singh, K. Gupta, J. P. Davim (Eds). Manufacturing and Industrial Engineering içinde (ss. 161-174). CRC Press.
  • Ghenai, C., Albawab, M. ve Bettayeb, M. (2020). Sustainability indicators for renewable energy systems using multi-criteria decision-making model and extended SWARA/ARAS hybrid method. Renewable Energy, 146, 580-597.
  • Goswami, S. S. ve Behera, D. K. (2021). Implementation of ENTROPY-ARAS decision making methodology in the selection of best engineering materials. Materials Today: Proceedings, 38, 2256-2262.
  • Goswami, S. S., Behera, D. K. ve Mitra, S. (2020). Supplier Selection Problem by Applying Additive Ratio Assessment (ARAS) Methodology. International Conference on Thermal Engineering and Management Advances, Singapore.
  • Goswami, S. S., Behera, D. K., Afzal, A., Razak Kaladgi, A., Khan, S. A., Rajendran, P., ... & Asif, M. (2021). Analysis of a robot selection problem using two newly developed hybrid MCDM models of TOPSIS-ARAS and COPRAS-ARAS. Symmetry, 13(8), 1331.
  • Goswami, S. ve Mitra, S. (2020). Selecting the best mobile model by applying AHP-COPRAS and AHP-ARAS decision making methodology. International Journal of Data and Network Science, 4(1), 27-42.
  • Hezer, S., Gelmez, E. ve Özceylan, E. (2021). Comparative analysis of TOPSIS, VIKOR and COPRAS methods for the COVID-19 Regional Safety Assessment. Journal of infection and public health, 14(6), 775-786.
  • Hoan, P. ve Ha, Y. (2021). ARAS-FUCOM approach for VPAF fighter aircraft selection. Decision Science Letters, 10(1), 53-62.
  • https://www.numbeo.com/cost-of-living/rankings_current.jsp, (Erişim tarihi: 15.11.2021)
  • Kamali Saraji, M., Streimikiene, D. ve Kyriakopoulos, G. L. (2021). Fermatean fuzzy CRITIC-COPRAS method for evaluating the challenges to industry 4.0 adoption for a sustainable digital transformation. Sustainability, 13(17), 1-20.
  • Kandpal, V. (2021). Determining interlinkages between the measures of financial literacy: An MCDM approach. Journal of Public Affairs, 1-8.
  • Khalilzadeh, M., Ghasemi, P., Afrasiabi, A. ve Shakeri, H. (2021). Hybrid fuzzy MCDM and FMEA integrating with linear programming approach for the health and safety executive risks: a case study. Journal of Modelling in Management, 16(4), 1025-1053.
  • Küçükal, N. T., Ayaş, P., Köse, D. ve Kaya, G. K. (2021). Çok kriterli karar verme yöntemlerinin karşılaştırmalı kullanımı ile Türkiye’deki illerin yaşam kalitelerinin değerlendirilmesi. Gazi İktisat ve İşletme Dergisi, 7(2), 150-168.
  • Liu, G., Fan, S., Tu, Y. ve Wang, G. (2021). Innovative Supplier Selection from Collaboration Perspective with a Hybrid MCDM Model: A Case Study Based on NEVs Manufacturer. Symmetry, 13(1), 1-28.
  • Mostafaeipour, A., Dehshiri, S. S. H., Dehshiri, S. J. H., Almutairi, K., Taher, R., Issakhov, A. ve Techato, K. (2021). A thorough analysis of renewable hydrogen projects development in Uzbekistan using MCDM methods. International Journal of Hydrogen Energy, 46(61), 31174-31190.
  • Naderi, H., Shahosseini, H. ve Jafari, A. (2013). Evaluation MCDM multi-disjoint paths selection algorithms using fuzzyCopeland ranking method, International Journal of Communication Networks and Information Security, 5(1), 59– 67.
  • Narayanamoorthy, S., Ramya, L., Kalaiselvan, S., Kureethara, J. V. ve Kang, D. (2021). Use of DEMATEL and COPRAS method to select best alternative fuel for control of impact of greenhouse gas emissions. Socio-Economic Planning Sciences, 76, 1-20.
  • Nweze, S. ve Achebo, J. (2021). Comparative Enhancement of Mild Steel Weld Mechanical Properties for Better Performance Using COPRAS–ARAS Method. European Journal of Engineering and Technology Research, 6(2), 70-74.
  • Orakçı, E. ve Özdemir, A. (2017). Telafi edici çok kriterli karar verme yöntemleri ile Türkiye ve AB ülkelerinin insani gelişmişlik düzeylerinin belirlenmesi. Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 19(1), 61-74.
  • Ozkaya, G., Timor, M. ve Erdin, C. (2021). Science, Technology and Innovation Policy Indicators and Comparisons of Countries through a Hybrid Model of Data Mining and MCDM Methods. Sustainability, 13(2), 1-49.
  • Özbek, A. (2019). Türkiye’deki İllerin Edas ve WASPAS Yöntemleri ile Yaşanabilirlik Kriterlerine Göre Siralanmasi. Kırıkkale Üniversitesi Sosyal Bilimler Dergisi, 9(1), 177-200.
  • Pérez-Gladish, B., Ferreira, F. A. ve Zopounidis, C. (2021). MCDM/A studies for economic development, social cohesion and environmental sustainability: introduction. International Journal of Sustainable Development & World Ecology, 28(1), 1-3.
  • Sahin, M. (2021). Location selection by multi-criteria decision-making methods based on objective and subjective weightings. Knowledge and Information Systems, 63(8), 1991-2021.
  • Seyhan, A. G. D. N. ve Seyhan, A. G. B. (2021). COVID-19 Salgın Sürecinde AB Ülkelerindeki Yaşam Kalitesinin Çok Kriterli Karar Verme ile Değerlendirilmesi. Journal of Social Research and Behavioral Sciences, 7(13), 158-180.
  • Shannon, C.E. (1948). A Mathematical Theory Of Communication.Bell System Technical Journal, 27, 379-423.
  • Štirbanović, Z., Stanujkić, D., Miljanović, I. ve Milanović, D. (2019). Application of MCDM Methods for Flotation Machine Selection. Minerals Engineering, 137, 140-146.
  • Torkayesh, A. E. ve Torkayesh, S. E. (2021). Evaluation of information and communication technology development in G7 countries: An integrated MCDM approach. Technology in Society, 66, 1-9.
  • Triantaphyllou, E. ve Sánchez, A. (1997). A Sensitivity Analysis Approach for Some Deterministic Multi-Criteria Decision-Making Methods. Decision Sciences, 28(1), 151–194.
  • Triplett, J. E. (2001). Should the Cost-of-living Index Provide the Conceptual Framework for a Consumer Price Index?. The Economic Journal, 111(472), 311–334.
  • Ulutaş, A. ve Karaköy, C. (2019). An analysis of the logistics performance index of EU countries with an integrated MCDM model. Economics and Business Review, 5(4), 49-69.
  • Ünvan, Y. A. ve Ergenç, C. (2021). Financial Performance Analysis with the Fuzzy COPRAS and Entropy-COPRAS Approaches. Computational Economics, 1-29.
  • Valipour, A., Sarvari, H. ve Tamošaitiene, J. (2018). Risk assessment in PPP projects by applying different MCDM methods and comparative results analysis. Administrative Sciences, 8(4), 1-17.
  • Wang, T. C. ve Lee, H. D. (2009). Developing a Fuzzy TOPSIS Approach Based on Subjective Weights and Objective Weights. Expert systems with applications, 36(5), 8980-8985.
  • Wang, Y. M. ve Luo, Y. (2010). Integration of Correlations with Standard Deviations for Determining Attribute Weights in Multiple Attribute Decision Making. Mathematical and Computer ModellingVolume, 51(1–2), 1–12.
  • Wen, Z.; Liao, H. ve Zavadskas, E.K. (2020). MACONT: Mixed aggregation by comprehensive normalization technique for multi-criteria analysis. Informatica, 31, 857–880
  • Wu, Z., Sun, J., Liang, L. ve Zha, Y. (2011). Determination of Weights for Ultimate Cross Efficiency Using Shannon Entropy.Expert Systems With Applications, 38(5),5162–5165.
  • Yıldız, A., Ayyıldız, E., Gümüş, A. T. ve Özkan, C. (2019). Ülkelerin yaşam kalitelerine göre değerlendirilmesi için hibrit pisagor bulanık AHP-TOPSIS metodolojisi: Avrupa Birliği örneği. Avrupa Bilim ve Teknoloji Dergisi, 17, 1383-1391.
  • Yuan, Y., Xu, Z. ve Zhang, Y. (2021). The DEMATEL–COPRAS hybrid method under probabilistic linguistic environment and its application in Third Party Logistics provider selection. Fuzzy Optimization and Decision Making, 1-20.
  • Zavadskas, E. K. ve Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision-making. Technol Econ Dev Econ, 16(2):159–72.
  • Zavadskas, E. K., Kaklauskas, A. ve Sarka, V. (1994). The new method of multicriteria complex proportional assessment of projects. Technol Econ Dev Econ, 1(3):131–9.
  • Zavadskas, E. K., ve Podvezko, V. (2016). Integrated determination of objective criteria weights in MCDM. International Journal of Information Technology Decision Making, 15(02), 267-283.
  • Zhang,H., Gu, C., Gu, L. ve Zhang, Y. (2011). The Evaluation of Tourism Destination Competitiveness by TOPSIS & Information Entropy - A Case in the Yangtze River Delta of China. Tourism Management, 32(2), 443-451.
Toplam 55 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm İktisadi ve İdari Bilimler
Yazarlar

Nazlı Ersoy 0000-0003-0011-2216

Yayımlanma Tarihi 28 Mart 2023
Gönderilme Tarihi 16 Ocak 2022
Yayımlandığı Sayı Yıl 2023 Cilt: 25 Sayı: 1

Kaynak Göster

APA Ersoy, N. (2023). COPRAS-ARAS Hibrit ÇKKV Modeli İle AB Ülkelerinin Mevcut Yaşam Maliyetinin Bir Analizi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 25(1), 198-214. https://doi.org/10.32709/akusosbil.1058594