Green Production and Ecological Footprint: Evaluation of Sustainability Performance with Multi-Criteria Decision-Making Methods

Öz

Sustainable development has become a critical issue in global economic and environmental policies. Industrialization and economic growth have increased the ecological footprint while disrupting the balance between biocapacity and resource consumption. In production management, green production strategies are essential for ensuring environmental sustainability. However, the existing literature lacks comprehensive assessments that use multi-criteria decision-making methods. This study addresses this gap by evaluating sustainability performance through key indicators such as ecological footprint, biocapacity, and ecological deficit. The research employs TOPSIS, time-series analysis, regional and income-based comparisons, and K-Means clustering analysis to evaluate nations comprehensively. The findings indicate that high-income countries generally have the most significant ecological footprints and ecological deficits, whereas lower-income countries face biocapacity constraints despite having smaller footprints. Meanwhile, recent findings show a strong relationship between GDP growth and increases in ecological deficits. It highlights that industrialized countries tend to put more and more stress on the environment. However, effective policies to fight climate change and sustainability have allowed some countries to do well at reducing how everything messes up the environment, and that’s been a significant achievement. From a production management perspective, the feasibility and effectiveness of green production strategies play a crucial role in reducing ecological disparities among nations. This study underscores the necessity of developing effective environmental policies and green production models to balance economic growth and ecological sustainability.

Anahtar Kelimeler

• Production Management
• Green Production
• Sustainability
• Ecological Footprint
• Biocapacity
• Multi-Criteria Decision Making
• Global Sustainability

Yeşil Üretim ve Ekolojik Ayak İzi: Çok Kriterli Karar Verme Yöntemleriyle Sürdürülebilirlik Performansının Değerlendirilmesi

Öz

Sürdürülebilir kalkınma, küresel ekonomi ve çevresel politikalar açısından giderek daha kritik bir konu haline gelmiştir. Sanayileşme ve ekonomik büyüme, ekolojik ayak izini artırırken, biyokapasite ve doğal kaynak tüketimi arasındaki dengeyi bozmuştur. Özellikle üretim yönetimi bağlamında, yeşil üretim stratejileri çevresel sürdürülebilirliği sağlamak için önemli bir araç olarak görülmektedir. Ancak, mevcut literatürde ülkelerin sürdürülebilirlik performanslarını çok kriterli karar verme yöntemleri ile değerlendiren çalışmaların sınırlı olduğu görülmektedir. Bu çalışma, bu eksikliği gidermek amacıyla ekolojik ayak izi, biyokapasite ve ekolojik açık gibi temel göstergeleri kullanarak sürdürülebilirlik performanslarını değerlendirmektedir. Araştırmada TOPSIS, zaman serisi analizi, bölgesel ve gelir bazlı karşılaştırmalar ile K-Means kümeleme analizi yöntemleri uygulanarak ülkeler arasında sürdürülebilirlik performansına yönelik kapsamlı bir değerlendirme sunulmaktadır. Araştırmanın bulguları, yüksek gelirli ülkelerin genellikle en büyük ekolojik ayak izine ve ekolojik açığa sahip olduğunu, düşük gelirli ülkelerin ise daha küçük ayak izlerine sahip olmalarına rağmen biyokapasite kısıtları ile karşı karşıya kaldığını göstermektedir. Ayrıca, GSYİH büyümesi ile ekolojik açık arasındaki korelasyon, sanayileşmiş ülkelerin çevresel baskıyı artırma eğiliminde olduğunu ortaya koymaktadır. Bununla birlikte, bazı ülkeler etkin sürdürülebilirlik politikaları uygulayarak bu olumsuz etkileri hafifletmeyi başarmıştır. Üretim yönetimi perspektifinden bakıldığında, yeşil üretim stratejilerinin uygulanabilirliği ve etkinliği, ülkeler arasındaki ekolojik farklılıkları azaltmada önemli bir rol oynamaktadır. Bu çalışma, ekonomik kalkınma ile ekolojik sürdürülebilirlik arasındaki dengeyi sağlamak için etkili çevresel politikaların ve yeşil üretim modellerinin gerekliliğini vurgulamaktadır.

Anahtar Kelimeler

• Üretim Yönetimi
• Yeşil Üretim
• Küresel Sürdürülebilirlik
• Çok Kriterli Karar Verme
• Sürdürülebilirlik
• Ekolojik Ayak İzi
• Biyokapasite

Kaynakça

1. Al Qahtani, H., & Sankar, J. P. (2024). The cluster analysis in the aluminum industry with K-means method: An application for Bahrain. Cogent Business & Management, 11(1). https://doi.org/10.1080/23311975.2024.2361475
2. Arsu, T., & Ayçin, E. (2021). Evaluation of OECD countries with multi-criteria decision-making methods in terms of economic, social and environmental aspects. Operational Research in Engineering Sciences: Theory and Applications, 4(2), 55. https://doi.org/10.31181/oresta20402055a
3. Chatfield, C. (2016). The analysis of time series: An introduction (6th ed.). Routledge. https://doi.org/10.4324/9780203491683
4. Çelekli, A., & Zariç, S. (2023). From emissions to environmental impact: Understanding the carbon footprint. International Journal of Environment and Geoinformatics (IJEGEO), 10(4), 146-156. https://doi.org/10.30897/ijegeo.1383311.
5. Demirbay, S. G., & Karakaş, E. (2024). Exploring the ecological footprint in Turkey: Analyzing the interplay of economic and environmental factors. Nicel Bilimler Dergisi, 6(2), 128-157. https://doi.org/10.51541/nicel.1373907.
6. Denny, R., & Marquart-Pyatt, S. (2018). Environmental sustainability in Africa: What drives the ecological footprint over time? Sociology of Development, 4, 119-144. https://doi.org/10.1525/sod.2018.4.1.119.
7. Dinda, S., Coondoo, D., & Pal, M. (2000). Air quality and economic growth: An empirical study. Ecological Economics, 34, 409-423. https://doi.org/10.1016/S0921-8009(00)00179-8.
8. Djordjevic, B., & Krmac, E. (2019). Evaluation of energy-environment efficiency of European transport sectors: Non-radial DEA and TOPSIS approach. Energies, 12(15), 2907. https://doi.org/10.3390/en12152907

9. Espinosa, R. M., & Koh, L. S. C. (2024). Forecasting the ecological footprint of G20 countries in the next 30 years. Scientific Reports, 14, 8298. https://doi.org/10.1038/s41598-024-57994-z
10. Feng, S., Shafiei, M. W. M., Ng, T. F., Ren, J., & Jiang, Y. (2024). The intersection of economic growth and environmental sustainability in China: Pathways to achieving SDG. Energy Strategy Reviews, 55, 101530. https://doi.org/10.1016/j.esr.2024.101530
11. Ferreira, J., Marques, J., Moreno Pires, S., Iha, K., & Galli, A. (2022). Supporting national-level policies for sustainable consumption in Portugal: A socio-economic ecological footprint analysis. Ecological Economics, 205, 107687. https://doi.org/10.1016/j.ecolecon.2022.107687.
12. Gallego-Álvarez, I., Segura, L., & Martínez-Ferrero, J. (2015). Carbon emission reduction: The impact on international companies' financial and operation. Journal of Cleaner Production, 103, 149-159. https://doi.org/10.1016/j.jclepro.2014.08.047
13. Galli, A., Iha, K., Pires, S. M., Mancini, M. S., Alves, A., Zokai, G., Lin, D., Murthy, A., & Wackernagel, M. (2020). Assessing Portuguese cities' ecological footprint and bioc: Critical results for environmental awareness and local management. Cities, 96, 102442. https://doi.org/10.1016/j.cities.2019.102442
14. Galli, A., Kitzes, J., Wackernagel, M., Wada, Y., & Marchettini, N. (2012). Assessing the global environmental consequences of economic growth through the Ecological Footprint: A focus on China and India. Ecological Indicators, 17, 99-107. https://doi.org/10.1016/j.ecolind.2011.04.022
15. Georgescu, I., Nica, I., & Kinnunen, J. (2024). Towards sustainability: Understanding Norway’s ecological footprint through the framework of the Environmental Kuznets Curve. Energies, 17(23), 6074. https://doi.org/10.3390/en17236074.
16. Ghita, S. I., Saseanu, A. S., Gogonea, R.-M., & Huidumac-Petrescu, C.-E. (2018). Perspectives of ecological footprint in European context under the impact of information society and sustainable development. Sustainability, 10(9), 3224. https://doi.org/10.3390/su10093224
17. Gholizadeh, H., Goh, M., Fazlollahtabar, H., & Mamashli, Z. (2022). Modelling uncertainty in sustainable-green integrated reverse logistics network using metaheuristics optimization. Computers & Industrial Engineering, 163, 107828. https://doi.org/10.1016/j.cie.2021.107828
18. Gogonea, R.-M., Ghita, S. I., & Saseanu, A. S. (2020). Biocapacity—Premise of sustainable development in the European space. Sustainability, 12(3), 1037. https://doi.org/10.3390/su12031037
19. Govindan, K., Sivakumar, R., Sarkis, J., & Murugesan, P. (2013). Multi-criteria decision making approaches for green supplier evaluation and selection: A literature review. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2013.06.046
20. Hariram, N. P., Mekha, K. B., Suganthan, V., & Sudhakar, K. (2023). Sustainalism: An integrated socio-economic-environmental model to address sustainable development and sustainability. Sustainability, 15(13), 10682. https://doi.org/10.3390/su151310682
21. Hassanein, A., & Elmassah, S. (2023). Economic development and environmental sustainability in the GCC countries: New insights based on the economic complexity. Sustainability, 15(10), 7987. https://doi.org/10.3390/su15107987
22. Hertwich, E., & Peters, G. (2009). Carbon footprint of nations: A global, trade-linked analysis. Environmental Science & Technology, 43, 6414-6420. https://doi.org/10.1021/es803496a.
23. Li, T., Wang, H., & Lin, Y. (2024). Selection of renewable energy development path for sustainable development using a fuzzy MCDM based on cumulative prospect theory: The case of Malaysia. Scientific Reports, 14(1), 15082. https://doi.org/10.1038/s41598-024-65982-6
24. Lin, D., Hanscom, L., Murthy, A., Galli, A., Evans, M., Neill, E., Mancini, M., Martindill, J., Medouar, F.-Z., Huang, S., & Wackernagel, M. (2018). Ecological footprint accounting for countries: Updates and results of the national footprint accounts, 2012-2018. Resources, 7(3), 1-22. https://doi.org/10.3390/resources7030058.
25. Menton, M., Larrea, C., Latorre, S., et al. (2020). Environmental justice and the SDGs: From synergies to gaps and contradictions. Sustainability Science, 15, 1621–1636. https://doi.org/10.1007/s11625-020-00789-8. Moros Ochoa, M., Castro Nieto, G., Quintero, A., & Llorente Portillo, C. (2022). Forecasting biocapacity and ecological footprint at a worldwide level to 2030 using neural networks. Sustainability, 14(17), 10691. https://doi.org/10.3390/su141710691 Ozcan, B., Tzeremes, P. G., & Tzeremes, N. G. (2020). Energy consumption, economic growth and environmental degradation in OECD countries. Economic Modelling, 84, 203-213. https://doi.org/10.1016/j.econmod.2019.04.010 Öcal, O., Altınöz, B., & Aslan, A. (2020). The effects of economic growth and energy consumption on ecological footprint and carbon emissions: Evidence from Turkey. Ekonomi Politika ve Finans Araştırmaları Dergisi, 5(3), 667-681. https://doi.org/10.30784/epfad.773461.
26. Qamruzzaman, M., & Karim, S. (2024). Green energy, green innovation, and political stability led to green growth in OECD nations. Energy Strategy Reviews, 55, 101519. https://doi.org/10.1016/j.esr.2024.101519
27. Radácsi, L., & Szigeti, C. (2024). The illusion of the Holy Grail of decoupling: Are there countries with relatively high SDGI and moderately low ecological footprint? Environmental and Sustainability Indicators, 22, 100379. https://doi.org/10.1016/j.indic.2024.100379 Saaida, M. (2023). Collaborating for change: The power of multilateral cooperation in SDGs. Zenodo, 1, 1-26. https://doi.org/10.5281/zenodo.10884330. Saqib, N., & Shahzad, U. (2024). Pathways to sustainability: Evaluating the impact of green energy, natural resources, FinTech, and environmental policies in resource-abundant countries. Resources Policy, 97, 105264.
28. Saraç, Ş., & Yağlıkara, A. (2017). Environmental Kuznets Curve: The evidence from BSEC countries. Ege Academic Review, 17(2), 255-264.
29. Shen, Y., & Yue, S. (2023). Does ecological footprint affect biocapacity? Evidence from the experiences of G20 countries. Sustainability, 36(3), e12369.
30. Syrovátka, M. (2020). On sustainability interpretations of the Ecological Footprint. Ecological Economics, 169, 106543. https://doi.org/10.1016/j.ecolecon.2019.106543 Tomadon, L., Do Couto, E., De Vries, W., & Moretto, Y. (2024). Smart city and sustainability indicators: A bibliometric literature review. Discover Sustainability, 5, Article 328. https://doi.org/10.1007/s43621-024-00328-w Toprak, A. (2023). Relationship between biocapacity efficiency and economic growth: SUR model analysis for Europe. Yönetim Bilimleri Dergisi, 21(Cumhuriyetin 100. Yılı Özel Sayısı), 789-806. https://doi.org/10.35408/comuybd.1345098.
31. UNDP, & SDSN. (2020). Youth solutions report 2020: 50 game-changing projects for the SDGs developed by young people. United Nations Development Programme and Sustainable Development Solutions Network. https://www.undp.org/sites/g/files/zskgke326/files/publications/UNDP-RBAP-SDSN-joint-report-Youth-Solutions-Report-2020.pdf
32. Wackernagel, M., Monfreda, C., Erb, K.-H., Haberl, H., & Schulz, N. (2004). Ecological footprint time series of Austria, the Philippines, and South Korea for 1961-1999: Comparing the conventional approach to an 'actual land area' approach. Land Use Policy, 21(3), 261-269. https://doi.org/10.1016/j.landusepol.2003.10.007
33. Wackernagel, M., Monfreda, C., Schulz, N. B., Erb, K.-H., Haberl, H., & Krausmann, F. (2004). Calculating national and global ecological footprint time series: Resolving conceptual challenges. Land Use Policy, 21(3), 271-278. https://doi.org/10.1016/j.landusepol.2003.10.006
34. Wang, H., Pan, C., Wang, Q., & Zhou, P. (2020). Assessing sustainability performance of global supply chains: An input-output modeling approach. European Journal of Operational Research, 285(1), 393-404. https://doi.org/10.1016/j.ejor.2020.01.057
35. York, R., Rosa, E., & Dietz, T. (2004). The ecological footprint intensity of national economies. Journal of Industrial Ecology, 8(4), 139-154. https://doi.org/10.1162/1088198043630487
36. Zavadskas, E., Mardani, A., Turskis, Z., Jusoh, A., & Nor, K. (2016). Development of TOPSIS method to solve complicated decision-making problems: An overview on developments from 2000 to 2015. International Journal of Information Technology & Decision Making, 15(4), 645-682. https://doi.org/10.1142/S0219622016300019