Evaluation of Environmental Performance of OECD Countries Using SD-Based ARAS and WASPAS Methods

Abstract

Today, industrialization and technological developments have increased rapidly. Therefore, when evaluated in terms of countries, various problems such as population growth rate, global warming, pollution, environmental destruction, waste and air pollution have become more and more important issues. Countries need to take the necessary precautions and make some improvements in order to eliminate these problems and strengthen their environmental performance. Therefore, it is important to determine the environmental performance of countries. In this context, the aim of this study is to determine the environmental performance levels of the Organization for Economic Co-operation and Development (OECD) countries using ARAS (Additive Ratio Assessment) and WASPAS (Weighted Aggregates Sum Product Assessment) methods, which are among the Multi-Criteria Decision Making (MCDM) methods. The data used within the framework of this aim was obtained from the Environmental Performance Index (2022) Report. In order to determine the environmental performance levels of countries, 10 criteria have been determined: climate change mitigation, air quality, water quality, heavy metals, waste management, biodiversity, ecosystem services, acid rain, agriculture and water resources. These criteria have been weighted with the SD (Standard Deviation) method, and rankings have been made with ARAS and WASPAS methods. The ranking results obtained from both methods have been compared. According to the SD weighting method, the criterion with the highest weight is water quality, followed by air quality and acid rain criteria. In addition, according to the results of the analysis made with ARAS and WASPAS methods, the three countries with the highest level of environmental performance in the context of 38 countries included in the analysis are Sweden, Denmark and Finland, respectively.

Keywords

• Environmental Performance
• Multi-Criteria Decision Making
• SD Method
• ARAS method
• WASPAS method

References

1. [1] De Leo, F., Miglietta, P. P., “The contribution of some environmental indicators to sustainable performance of countries”, International Journal of Sustainability Policy & Practice, 11(4): 11-26, (2015). DOI: https://doi.org/10.18848/2325-1166/CGP/v11i04/55359
2. [2] Yu, Y., Zhang, M., Huo, B., “The impact of supply chain quality integration on green supply chain management and environmental performance”, Total Quality Management & Business Excellence, 30(9-10): 1110-1125, (2017). DOI: https://doi.org/10.1080/14783363.2017.1356684
3. [3] Gallego-Álvarez, I., Vicente-Galindo, M. P., Galindo-Villardón, M. P., Rodríguez-Rosa, M., “Environmental performance in countries worldwide: Determinant factors and multivariate analysis”, Sustainability, 6(11): 7807-7832, (2014). DOI: https://doi.org/10.3390/su6117807
4. [4] Pujiati, A., Feronica, S. M. F., Ridzuan, A. R., “Measurement of the role of innovation in increasing environmental performance index: empirical study in developed and non-developed countries”, International Business and Accounting Research Journal, 7(1): 18-36, (2023). DOI: http://dx.doi.org/10.35474/ibarj.v7i1.144
5. [5] Asfahani, A. M., “Green HRM and servant leadership: driving competitive advantage and environmental performance in higher education”, Sustainability, 15(10): 7921, (2023). DOI: https://doi.org/10.3390/su15107921
6. [6] Muma, B. O., Nyaoga, R. B., Matwere, R. B., Nyambega, E., “Green supply chain management and environmental performance among tea processing firms in Kericho County-Kenya”, International Journal of Economics, Finance and Management Sciences, 2(5): 270-276, (2014). DOI: https://doi.org/10.11648/j.ijefm.20140205.11
7. [7] Wendling, Z. A., Jacob, M., Esty, D. C., Emerson, J. W., “Explaining environmental performance: Insights for progress on sustainability”, Environmental Development, 44: 100741, (2022). DOI: https://doi.org/10.1016/j.envdev.2022.100741
8. [8] Bădîrcea, R. M., Doran, N. M., Manta, A. G., Puiu, S., Meghisan-Toma, G. M., Doran, M. D., “Linking financial development to environmental performance index-the case of Romania”, Economic Research-Ekonomska Istraživanja, 36(2): 2142635, (2023). DOI: https://doi.org/10.1080/1331677X.2022.2142635

9. [9] Peiró-Signes, Á., Cervelló-Royo, R., Segarra-Oña, M., “Can a country's environmental sustainability exert influence on its economic and financial situation? The relationship between environmental performance indicators and country risk”, Journal of Cleaner Production, 375: 134121, (2022). DOI: https://doi.org/10.1016/j.jclepro.2022.134121
10. [10] Pimonenko, T. V., Liulov, O. V., Chygryn, O. Y., “Environmental Performance Index: Relation between social and economic welfare of the countries”, Environmental Economics, 9(3): 7-16, (2018). DOI: http://dx.doi.org/10.21511/ee.09(3).2018.01
11. [11] Chandrasekharan, I., Kumar, R. S., Raghunathan, S., Chandrasekaran, S., “Construction of environmental performance index and ranking of states”, Current Science, 104(4): 435-439, (2013).
12. [12] Mohaghar, A., Amiri, K., Ghasemi, R., Azani, M., “Prioritizing the OECD Countries based on Environmental Performance Index Indicators”. In International Conference on Law, Management, Business, Economics and CSR Dubai_2018, (2018).
13. [13] Digkoglou, P., Papathanasiou, J., “Ranking the EU countries according to the environmental performance index using PROMETHEE”, International Journal of Sustainable Agricultural Management and Informatics, 4(3-4): 290-305, (2018). DOI: https://doi.org/10.1504/IJSAMI.2018.099240
14. [14] Jahn, D., “Environmental performance and policy regimes: Explaining variations in 18 OECD-countries”, Policy Sciences, 31(2): 107-131, (1998).
15. [15] Üner, S. İ., Demir, A., Dinler, S., Alakaş, H. M., “Prioritizing Individuals who will have Covid-19 vaccine with multi-criteria decision making methods”, Gazi University Journal of Science, 36(3): 1277-1290, (2023). DOI: https://doi.org/10.35378/gujs.1053782
16. [16] Liu, P., Zhu, B., Wang, P., “A weighting model based on best–worst method and its application for environmental performance evaluation”, Applied Soft Computing, 103: 107168, (2021). DOI: https://doi.org/10.1016/j.asoc.2021.107168
17. [17] Kumar, A., Sah, B., Singh, A. R., Deng, Y., He, X., Kumar, P., Bansal, R. C., “A review of multi criteria decision making (MCDM) towards sustainable renewable energy development”, Renewable and Sustainable Energy Reviews, 69: 596-609, (2017). DOI: https://doi.org/10.1016/j.rser.2016.11.191
18. [18] Hu, S. K., Tzeng, G. H., “Strategizing for better life development using OECD well-being indicators in a hybrid fuzzy MCDM model”, International Journal of Fuzzy Systems, 19: 1683-1702, (2017). DOI: https://doi.org/10.1007/s40815-017-0328-8
19. [19] Shariati, S., Yazdani-Chamzini, A., Salsani, A., Tamošaitienė, J., “Proposing a new model for waste dump site selection: Case study of Ayerma Phosphate Mine”, Engineering Economics, 25(4): 410-419, (2014). DOI: https://doi.org/10.5755/j01.ee.25.4.6262
20. [20] Chakraborty, S., Zavadskas, E. K., “Applications of WASPAS method in manufacturing decision making”, Informatica, 25(1): 1-20, (2014). DOI: https://doi.org/10.15388/Informatica.2014.01
21. [21] Diakoulaki, D., Mavrotas, G., Papayannakis, L., “Determining objective weights in multiple criteria problems: The CRITIC Method”, Computers & Operations Research, 22(7): 763-770, (1995). DOI: https://doi.org/10.1016/0305-0548(94)00059-H
22. [22] https://www.oecd.org/about/document/ratification-oecd-convention.htm, Access date: 21.07.2023.
23. [23] Ismail, W. K. W., Abdullah, L., “A new Environmental Performance Index using analytic hierarchy process: A case of ASEAN countries”, Environmental Skeptics and Critics, 1(3): 39-47, (2012).
24. [24] Chithambaranathan, P., Subramanian, N., Gunasekaran, A., Palaniappan, P. K., “Service supply chain environmental performance evaluation using Grey based hybrid MCDM approach”, International Journal of Production Economics, 166: 163-176, (2015). DOI: https://doi.org/10.1016/j.ijpe.2015.01.002
25. [25] Cucchiella, F., D’Adamo, I., Gastaldi, M., Koh, S. L., Rosa, P., “A comparison of environmental and energetic performance of European countries: A sustainability index”, Renewable and Sustainable Energy Reviews, 78: 401-413, (2017). DOI: https://doi.org/10.1016/j.rser.2017.04.077
26. [26] Doğan, H., “Seçilmiş ülkelerin çevresel performanslarının bütünleşik CRITIC-MABAC yöntemleriyle ölçülmesi”, Journal of Emerging Economies & Policy, 7(2): 433-448, (2022).
27. [27] Senir, G., “Evaluation of the environmental sustainability performance of Eastern European countries with integrated MCDM methods”, International Journal of Agriculture Environment and Food Sciences, 8(2): 378-391, (2024). DOI: https://doi.org/10.31015/jaefs.2024.2.13
28. [28] Kırda, K., Aytekin, A., “Assessing industrialized countries’ environmental sustainability performances using an integrated multi-criteria model and software”, Environment, Development and Sustainability, 26(7): 17505-17550, (2024). DOI: https://doi.org/10.1007/s10668-023-03349-z
29. [29] Karahan, M., Yıldırım, Z., Yıldırım, T., “Comparative analysis of Turkey’s environmental performance with Eastern European countries according to international EPI 2022 data”, Green Technologies and Sustainability, 3(1): 100116, (2025). DOI: https://doi.org/10.1016/j.grets.2024.100116
30. [30] Karabašević, D., Stanujkić, D., Urošević, S., “The MCDM model for personnel selection based on SWARA and ARAS methods”, Management (1820-0222), 20(77): 43-52, (2015).
31. [31] Urosevic, S., Karabasevic, D., Stanujkic, D., Maksimovic, M., “An Approach to personnel selection in the tourism industry based on the SWARA and the WASPAS methods”, Economic Computation & Economic Cybernetics Studies & Research, 51(1): 75-88, (2017).
32. [32] Singh, R. K., Modgil, S., “Supplier selection using SWARA and WASPAS–a case study of Indian cement industry”, Measuring Business Excellence, 24(2): 243-265, (2020). DOI: https://doi.org/10.1108/MBE-07-2018-0041
33. [33] Sihombing, V., Nasution, Z., Al Ihsan, M. A., Siregar, M., Munthe, I. R., Siregar, V. M. M., Asfar, D. A. “Additive Ratio Assessment (ARAS) Method for Selecting English Course Branch Locations”, In Journal of Physics: Conference Series, IOP Publishing, (2021). DOI: https://doi.org/10.1088/1742-6596/1933/1/012070
34. [34] Lukić, R., Hadrović Zekić, B., “Efficiency analysis of trade companies in Serbia using the ARAS method”, In 22 nd International Scientific Conference Business Logistics in Modern Management, Osijek, Croatia, 105-119, (2022).
35. [35] Ozceylan, E., Ozkan, B., Cetinkaya, C., “A hybrid model based on FAHP and WASPAS for evaluation of explosive and narcotics trace detection devices”, In Intelligent and Fuzzy Techniques in Aviation 4.0: Theory and Applications, Cham: Springer International Publishing, 335-360, (2022).
36. [36] Hashim, A., Faisal, S. M., Khan, A. K., “Analysis of Green Supplier Using ARAS Model Integration in the Decision-Making Process”, Journal of Environmental Impact and Management Policy (JEIMP) ISSN: 2799-113X, 3(03): 1-14, (2023). DOI: https://doi.org/10.55529/jeimp.33.1.14
37. [37] Szymczyk, K., Bağcı, H., Kaygın, C., Şahin, D., “A comparison of the entrepreneurial performance of Asian-Oceanian countries via the multi-criteria decision-making techniques of Critic, Aras, Waspas, Mairca and Borda Count methods”, Acta Polytechnica Hungarica, 20(3): 65-81, (2023).
38. [38] Kökyıldırım, A., Antmen, Z. F., “Determination of financial performance in electric power enterprises with Entropy weighted WASPAS analysis method”, Çukurova Üniversitesi Mühendislik Fakültesi Dergisi, 39(3): 849-860, (2024). DOI: https://doi.org/10.21605/cukurovaumfd.1560478
39. [39] Yavuz, S., Manga, M., “Comparative analysis of OECD countries in terms of basic science and technology indicators using Entropy and WASPAS methods”, Politická Ekonomie, 5: 812-840, (2024). DOI: https://doi.org/10.18267/j.polek.1447
40. [40] Nugroho, B. I., Dewi, E. M., Kurniawan, R. D., Gunawan, G., “Application of WASPAS method in determining the best flour for nastar making”, Jurnal Mandiri IT, 13(1): 63-71, (2024).
41. [41] Hendrawan, J., Kom, S., Kom, M., “Determining the best location for a new retail branch with the Weighted Aggregated Sum Product Assessment method”, Instal: Jurnal Komputer, 16(03): 400-407, (2024).
42. [42] Hsu, A., Lloyd, A., Emerson, J. W., “What progress have we made since Rio? Results from the 2012 Environmental Performance Index (EPI) and Pilot Trend EPI”, Environmental Science & Policy, 33: 171-185, (2013). DOI: https://doi.org/10.1016/j.envsci.2013.05.011
43. [43] Ünal, H., Polat, S., “Çevresel kalite ve ekonomik büyüme ilişkisi: OECD ülkeleri için statik panel veri analizi”, Maliye Dergisi, 177: 87-103, (2019).
44. [44] EPI (2022). “Environmental Performance Index 2022”. https://epi.yale.edu/, Access date: 20.07.2023.
45. [45] Zavadskas, E. K., Turskis, Z., “A new additive ratio assessment (ARAS) method in multicriteria decision‐making”, Technological and Economic Development of Economy, 16(2): 159-172, (2010). DOI: https://doi.org/10.3846/tede.2010.10
46. [46] Madic, M., Gecevska, V., Radovanovic, M., Petkovic D., “Multi-criteria economic analysis of machining processes using the WASPAS method”, Journal of Production Engineering, 17(2): 79-82, (2014).
47. [47] Zavadskas, E. K., Chakraborty, S., Bhattacharyya, O., Antucheviciene, J., “Application of WASPAS method as an optimization tool in non-traditional machining processes”, Information Technology and Control, 44(1), 77-88, (2015). DOI: https://doi.org/10.5755/j01.itc.44.1.7124
48. [48] Pruss-Ustun, A., Bos, R., Gore, F., Bartram, J., “Safer water, better health: Costs, benefits and sustainability of interventions to protect and promote health” (1st ed.). Geneva: World Health Organization, (2008).