Effects of Motor Vehicle Increase on Environmental Protection Expenditures and Traffic Safety: An Examination Using Grey Relational Analysis Method

Abstract

Global environmental pollution is increasingly becoming one of today's most pressing issues, and the situation is becoming increasingly alarming day by day due to greenhouse gas emissions causing climate change. Industrialization and urban growth adversely affect the quality of air, water, and soil, reduce biological diversity, and endanger human health. In this regard, increasing and efficiently using environmental protection expenditures is a crucial criterion for reducing harmful emissions as well as achieving sustainable development goals. The increase in the number of motor vehicles has a significant impact on environmental protection expenditures. Exhaust gases from vehicles are one of the main causes of air pollution, which, especially in large cities, reduces air quality. Increasing air pollution causes health problems as well as environmental damage, forcing governments and local administrations to allocate more financial resources to improve air quality and reduce emissions. In this study, using data obtained from the Turkish Statistical Institute (TÜİK) for the period 2013-2022, grey relational grades of environmental protection expenditures, greenhouse gas emissions, and the number of road accidents according to the number of motor vehicles were calculated. When examining the grey relational grades, it was observed that the number of motor vehicles is approximately 78% related to environmental protection expenditures, about 95% related to greenhouse gas emissions, and about 98% related to the number of road accidents.

Keywords

• Grey relational analysis
• Motor Vehicles
• environmental protection expenditures
• greenhouse gas.

References

1. Altıntaş, F. F. (2020). İnovasyon Performanslarının ENTROPİ Tabanlı Gri İlişkisel Analiz Yöntemi ile Değerlendirilmesi: G7 Grubu Ülkeleri Örneği. Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 7(2), 151–172. https://doi.org/10.30803/adusobed.802738
2. Aydemir, E., & Sahin, Y. (2019). Evaluation of healthcare service quality factors using grey relational analysis in a dialysis center. Grey Systems: Theory and Application, 9(4), 432–448. https://doi.org/10.1108/gs-01-2019-0001
3. Aydemir, E., & Turhan, T. (2022a). Comparison of Grey Incidence Degrees of Selected Stock Indices According to BIST100 Index in the Covid19 Pandemic Process. 1st International Conference on Engineering and Applied Natural Sciences, 1731–1735.
4. Aydemir, E., & Turhan, T. (2022b). Grey Incidence Analysis for Covid19 New Cases and Deaths in Selected European Countries According to Türkiye. 3rd International Conference on Applied Engineering and Natural Sciences, 1592–1597.
5. Dang, Y.-g., Liu, Z., & Xie, Y.-m. (2020). Characteristic Test Method of Matrix Grey Incidence Degree and Its Application. Operations Research and Management Science, 29(9), 131–138.
6. Deng, J. L. (1989). Introduction to Grey system theory. J. Grey Syst., 1(1), 1–24.
7. Değirmenci, T., & Aydın, M. (2020). Çevre Koruma Harcamaları ile Gelir Dağılımı ve Ekonomik Büyüme Arasındaki Dinamik İlişkiler: Seçili OECD Ülkeleri için Panel Nedensellik Yaklaşımı. Sosyoekonomi, 28(46), 391–406. https://doi.org/10.17233/sosyoekonomi.2020.04.18
8. Du, J., Liu, S., & Liu, Y. (2021). A novel grey multi-criteria three-way decisions model and its application. Computers & Industrial Engineering, 158, 107405. https://doi.org/10.1016/j.cie.2021.107405

9. Haftacı, V., & Soylu, K. (2007). Çevre Kirlenmesi ve Çevre Koruma Bağlamında Çevre Muhasebesinin Önemi. Muhasebe Ve Finansman Dergisi, 33, 102–120.
10. Javanmardi, E., Liu, S., & Xie, N. (2020). Exploring Grey Systems Theory-Based Methods and Applications in Sustainability Studies: A Systematic Review Approach. Sustainability, 12(11), 4437. https://doi.org/10.3390/su12114437
11. Kelen, F. (2014). Motorlu Taşıt Emisyonlarının İnsan Sağlığı ve Çevre Üzerine Etkileri. Yüzüncü Yıl Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 19(1–2), 80–87.
12. Lin, S.-L., & Wu, S.-J. (2011). Is grey relational analysis superior to the conventional techniques in predicting financial crisis?. Expert Systems with Applications, 38(5), 5119–5124. https://doi.org/10.1016/j.eswa.2010.09.139
13. Liu, S., Cai, H., Cao, Y., & Yang, Y. (2011). Advance in grey incidence analysis modelling. 2011 IEEE International Conference on Systems, Man, And Cybernetics, 1886–1890. https://doi.org/10.1109/icsmc.2011.6083947
14. Recepoğlu, M. (2021). Türkiye'de Gelir, Enerji Tüketimi, Ticari Açıklık ve Çevre Koruma Harcamaları: ÇKE Hipotezinin Bölgesel Analizi. International Journal of Public Finance, 6(2), 353–372. https://doi.org/10.30927/ijpf.1013985
15. Turhan, T., & Aydemir, E. (2021). A Financial Ratio Analysis on BIST Information and Technology Index (XUTEK) Using AHP-weighted Grey Relational Analysis. Düzce Üniversitesi Bilim Ve Teknoloji Dergisi, 9(6), 195–209. https://doi.org/10.29130/dubited.1011252
16. Zhai, L.-Y., Khoo, L.-P., & Zhong, Z.-W. (2009). Design concept evaluation in product development using rough sets and grey relation analysis. Expert Systems with Applications, 36(3), 7072–7079. https://doi.org/10.1016/j.eswa.2008.08.068
17. Özdemir, O., & Kılıçarslan, Ş. (2021). Entropi Temelli Gri İlişkisel Analiz Tekniği ile Hayat ve Emeklilik Şirketlerinin Finansal Performansları Üzerine Bir Araştırma. Süleyman Demirel Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 26(4), 413–434.
18. Şahin, Y., & Aydemir, E. (2019). Akıllı Telefon Teknik Özellik Önem Derecelerinin AHP Ağırlıklı Gri İlişkisel Analizi Yöntemi İle Belirlenmesi. Eskişehir Osmangazi Üniversitesi İktisadi Ve İdari Bilimler Dergisi, 14(1), 225–238. https://doi.org/10.17153/oguiibf.486920