ÇEVRESEL-SOSYAL PERFORMANS İLE KİŞİ BAŞINA GSYİH ARASINDA BİR İLİŞKİ VAR MIDIR? G-20 ÜLKELERİ ÜZERİNE BİR UYGULAMA

Yıl 2020, Cilt: 15 Sayı: 54, 463 - 479, 30.07.2020

Güler Aras , Filiz Mutlu Yıldırım

https://doi.org/10.14783/maruoneri.771661

Cited By: 2

Öz

Küreselleşmeyle birlikte gittikçe artan ve daha karmaşık bir yapıya bürünen birçok çevresel ve sosyal riskin ekonomik risklerden daha önemli hale gelmesi, söz konusu riskleri barındıran performanslar arasındaki ilişkinin araştırılmasını gerekli kılmaktadır. Çalışmada bu amaçla, ilk olarak çevresel ve sosyal performans göstergeleri Entropi yöntemiyle G-20 ülkeleri temel alınarak ağırlıklandırmıştır. Ardından, Gri İlişkisel Analiz yöntemi ile performans ölçümü gerçekleştirilmiştir. Son aşama ise elde edilen bu performans puanları ile ekonomik performans göstergelerinden biri olan kişi başına düşen Gayri Safi Yurtiçi Hasıla (GSYİH) arasındaki ilişki Spearman sıra korelasyon katsayısı hesaplanarak araştırılmıştır. Analiz bulguları, çevresel-sosyal performans ile kişi başına düşen GSYİH arasında pozitif yönde güçlü bir ilişki olduğunu ortaya koymaktadır.

Anahtar Kelimeler

Sürdürülebilirlik,, Çevresel-Sosyal Performans,, Kişi Başına Düşen GSYİH,, G-20, Entropi,, Gri İlişkisel Analiz,, Spearman Sıra Korelasyon Katsayısı.

IS THERE A RELATIONSHIP BETWEEN ENVIRONMENTAL SOCIAL PERFORMANCE AND GDP PER CAPITA? EVIDENCE FROM THE G-20 COUNTRIES

Öz

The fact that several environmental and social risks are on increase and have become a more complex structure with globalization, they impose greater jeopardy to countries than economic risks. Hence, it is necessary to investigate the relationship between the performances related to these risks. For this purpose, environmental and social performance indicators based on the G-20 countries’ data have been weighted firstly with the Entropy method. Then, performance measurement has been done with the Gray Relational Analysis method. In the final stage, the relationship between these performance scores and the Gross Domestic Product (GDP) per capita, which is one of the economic performance indicators, has been investigated by calculating the Spearman rank correlation coefficient. Findings reveal that there is a strong positive relationship between environmental-social performance and GDP per capita.

Anahtar Kelimeler

Sustainability,, Environmental-Social Performance,, GDP per Capita,, G-20, Entropy,, Gray Relational Analysis,, Spearman Rank Correlation Coefficient.

Kaynakça

• Adedoyin, F. F., Alola, A. A. & Bekun, F. V. (2020). An assessment of environmental sustainability corridor: The role of economic expansion and research and development in EU countries. Science of The Total Environment. 713. 136726. https://doi.org/10.1016/j.scitotenv.2020.136726.
• Antanasijević, D., Pocajt, V., Ristić, M. & Perić-Grujić, A. (2017). A differential multi-criteria analysis for the assessment of sustainability performance of European countries: Beyond country ranking. Journal of Cleaner Production. 165 (November 2017). 213-220.
• Aras, G. (2015). The future perspectives: What do we need for market and business sustainability?. In Sustainable Markets for Sustainable Business. London: Routledge.
• Aras, G. & Crowther, D. (2009). Corporate sustainability reporting: A study in disingenuity?. Journal of Business Ethics. 87 (1). 279-288.
• Baskaran, V., Nachiappan, S. & Rahman, S. (2012). Indian textile suppliers’ sustainability evaluation using the grey approach. International Journal of Production Economics. 135 (2). 647-658.
• Chen, Z., Kourtzidis, S., Tzeremes, P. & Tzeremes, N. (2020). A robust network DEA model for sustainability assessment: An application to Chinese Provinces. Operational Research. https://doi.org/10.1007/s12351.020.00553-x
• Cracolici, M. F., Cuffaro, M. & Nijkamp, P. (2010). The measurement of economic, social and environmental performance of countries: A novel approach. Social Indicators Research. 95 (2). 339-356.
• Deng, Ju-L. (1982). Control problems of grey systems. Systems & Control Letters. 1 (5). 288-294.
• Distaso, A. (2007). Well-being and/or quality of life in EU countries through a multidimensional index of sustainability. Ecological Economics. 64 (1). 163-180.
• Dos Santos, B. M., Godoy, L. P. & Campos, L. M. (2019). Performance evaluation of green suppliers using Entropy-TOPSIS-F. Journal of Cleaner Production. 207 (1). 498-509.
• Elkington, J. (1997). Cannibals with Forks: Triple Bottom Line of 21st Century Business. Chichester: Capstone Publishing Limited.
• Floridi, M., Pagni, S., Falorni, S. & Luzzati, T. (2011). An exercise in composite indicators construction: Assessing the sustainability of Italian regions. Ecological Economics. 70 (8). 1440-1447.
• Gauthier, C. (2005). Measuring corporate social and environmental performance: The extended life-cycle assessment. Journal of Business Ethics. 59 (1-2). 199-206.
• Giannakis, M., Dubey, R., Vlachos, I. & Ju, Y. (2020). Supplier sustainability performance evaluation using the Analytic Network Process. Journal of Cleaner Production. 247.119439. https://doi.org/10.1016/j.jclepro.2019.119439.
• Govindan, K., Khodaverdi, R. & Jafarian, A. (2013). A Fuzzy Multi Criteria approach for measuring sustainability performance of a supplier based on Triple Bottom Line approach. Journal of Cleaner Production. 47 (May 2013). 45-354.
• Gray, R. & Milne, M. (2002). Sustainability reporting: Who’s kidding whom?. Chartered Accountants Journal of New Zealand. 81 (6). 66-70.
• Hauke, J. & Kossowski, T. (2011). Comparison of values of Pearson’s and Spearman’s correlation coefficients on the same sets of data. Quaestiones Geographicae. 30 (2). 87-93.
• Hosseini, H. M. & Kaneko, S. (2011). Dynamic sustainability assessment of countries at the macro level: A principal component analysis. Ecological indicators. 11 (3). 811-823.
• Keeble, J. J., Topiol, S. & Berkeley, S. (2003). Using indicators to measure sustainability performance at a corporate and project level. Journal of Business Ethics. 44 (2-3). 149-158.
• Küpeli, M. & Alp, İ. (2018). G-20 Ülkelerinin yenilenebilir enerji etkinliğinin Dengeli Performans Ağırlıkları ve Veri Zarflama Analizi ile değerlendirilmesi. Uluslararası İktisadi ve İdari İncelemeler Dergisi. 18 (EİY Özel Sayı). 207-218.
• Liu, G., Baniyounes, A. M., Rasul, M. G., Amanullah, M. T. O. & Khan, M. M. K. (2013). General sustainability indicator of renewable energy system based on Grey Relational Analysis. International Journal of Energy Research. 37 (14). 1928-1936.
• Liu, K., Yang, D. G., Yang, G. & Zhou, Z. T. (2020). Assessing the regional sustainability performance in China using the global Malmquist-Luenberger productivity index. International Journal of Energy Sector Management. https://doi.org/10.1108/IJESM-03-2019-0023.
• Liu, S. & Lin, Y. (2006). Grey Information: Theory and Practical Applications. London: Springer.
• Liu, W. & Cui, J. (2008). Entropy Coefficient method to evaluate the level of sustainable development of China’s sports. International Journal of Sports Science and Engineering. 2 (2). 72-78.
• Nilashi, M., Cavallaro, F., Mardani, A., Zavadskas, E. K., Samad, S. & Ibrahim, O. (2018). Measuring country sustainability performance using ensembles of neuro-fuzzy technique. Sustainability. 10 (8). 1-20.
• Orlitzky, M. (2005). Payoffs to social and environmental performance. The Journal of Investing. 14 (3). 48-52.
• Ranganathan, J. (1998). Sustainability rulers: Measuring corporate environmental and social performance: Sustainable Enterprises Perspectives Series. Washington: World Resources Institute.
• Rosales, N. (2011). Towards the modeling of sustainability into urban planning: Using indicators to build sustainable cities. Procedia Engineering. 21 (2011). 641-647.
• Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal. 27 (3). 379-423.
• Shmelev, S. E. (2011). Dynamic sustainability assessment: The case of Russia in the period of transition (1985- 2008). Ecological Economics. 70 (11). 2039-2049.
• Shmelev, S. E. & Rodríguez-Labajos, B. (2009). Dynamic multidimensional assessment of sustainability at the macro level: The case of Austria. Ecological Economics. 68 (10). 2560-2573.
• Spearman, C. E. (1904a). The proof and measurement of association between two things. American Journal of Psychology. 15 (1904). 72-101.
• Spearman C. E. (1904b). General intelligence, objectively determined and measured. American Journal of Psychology. 15 (1904). 201-293.
• Štreimikienė, D. & Baležentis, A. (2013). Integrated sustainability index: The case study of Lithuania. Intellectual Economics. 7 (3). 289-303.
• Szekely, F. & Knirsch, M. (2005). Responsible leadership and corporate social responsibility: Metrics for sustainable performance. European Management Journal. 23 (6). 628-647.
• Sueyoshi, T. & Wang, D. D. (2020). Rank dynamics and club convergence of sustainable development for countries around the world. Journal of Cleaner Production. 250. 119480. https://doi.org/10.1016/j. jclepro.2019.119480.
• Sun, H., Mohsin, M., Alharthi, M. & Abbas, Q. (2020). Measuring environmental sustainability performance of South Asia. Journal of Cleaner Production. 251. 119519. https://doi.org/10.1016/j.jclepro.2019.119519.
• Tajbakhsh, A. & Shamsi, A. (2019). Sustainability performance of countries matters: A non-parametric index. Journal of Cleaner Production. 224 (July 2019). 506-522.
• Tan, Y., Shuai, C., Jiao, L. & Shen, L. (2017). An adaptive neuro-fuzzy inference system (ANFIS) approach for measuring country sustainability performance. Environmental Impact Assessment Review. 65 (July 2017). 9-40.
• Tang, J., Zhu, H. L., Liu, Z., Jia, F. & Zheng, X. X. (2019). Urban sustainability evaluation under the Modified TOPSIS based on Grey Relational Analysis. International Journal of Environmental Research and Public Health. 16 (2). 1-21.
• Tanguay, G. A., Rajaonson, J., Lefebvre, J. F. & Lanoie, P. (2010). Measuring the sustainability of cities: An analysis of the use of local indicators. Ecological Indicators. 10 (2). 407-418.
• Türe, H. (2019). OECD ülkeleri için refah ölçümü: Gri İlişkisel Analiz uygulaması. Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 21 (2). 310-327.
• United Nations. (06.04.2020). Sustainable development goals knowledge platform. https://sustainabledevelopment.un.org/?menu=1300 (Accessed 6 April 2020).
• United Nations (UN). (1992). Environment and development rio declaration. Principle 1. United Nations Environment and Development Conference, 3-14 June 1992. Rio de Janeiro. http://arsiv.uclg-mewa.org/doc/rio-20_z2oua.pdf (Accessed 21 March 2020).
• Wang, Q., Wu, C. & Sun, Y. (2015). Evaluating corporate social responsibility of airlines using Entropy weight and Grey Relation Analysis. Journal of Air Transport Management. 42 (January 2015). 55-62.
• Wang, Y.M. & Luo, Y. (2010). Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making. Mathematical and Computer Modelling. 51 (1-2). 1-12.
• Wang, J., Yu, J. & Zhong, R. (2020). Country sustainable development and economic growth: The international evidence. https://ssrn.com/abstract=3350232 (Accessed 28 May 2020).
• World Bank. (01.03.2020). Data Bank. https://databank.worldbank.org/home (Accessed 1 March 2020).
• World Commission on Environment and Development (WCED). (1987). Our common future. https://sustainabledevelopment.un.org/content/documents/5987our-common-future.pdf (Accessed 2 March 2020).
• World Economic Forum (WEF). (2019). The global risks report 2019. http://www3.weforum.org/docs/WEF_Global_Risks_Report_2019.pdf (Accessed 1 March 2020).
• Wu, H. H. (2002). A Comparative study of using Grey Relational Analysis in multiple attribute decision making problems. Quality Engineering. 15 (2). 209-217.
• Zhang, H., Gu, C. L., 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. 32(2). 443-451.
• Zhang, L., Xu, Y., Yeh, C. H., Liu, Y. & Zhou, D. (2016). City sustainability evaluation using multi-criteria decision making with objective weights of interdependent criteria. Journal of Cleaner Production. 131 (September 2016). 491-499.