Scenario-based dynamic evaluation of lifecycle environmental efficiency in renewable energy infrastructure using a novel hybrid multi-facet fuzzy decision-making approach
DOI: https://doi.org/10.3846/tede.2026.28597Abstract
The efficiency of life cycle environmental impacts of renewable energy infrastructures is extremely important for ensuring sustainability and combating climate change effectively. Although prior studies have addressed various aspects of lifecycle environmental impacts in renewable energy systems, a limited number of studies have systematically identified and prioritized the most critical factors influencing lifecycle environmental efficiency. This limitation may lead to suboptimal allocation of improvement efforts and reduce the effectiveness of sustainability-oriented strategies. The main objective of this study is to determine the most effective strategies to increase environmental efficiency of economic life cycle of renewable energy infrastructures and to identify the most critical environmental impact factors in this process. For this purpose, an original decision-making model integrating dynamic multi-facet fuzzy sets, Bayesian networks and multi-objective optimization on the basis of ratio analysis (MOORA) techniques is developed. This study makes a significant contribution to the literature by presenting an innovative decision support model that systematically identifies the most critical factors for increasing life cycle environmental efficiency in renewable energy infrastructures. Considering multi-facet fuzzy sets allows dynamic redefinition of membership degrees for different scenarios (negative, positive, unstable, natural). This provides better modelling of uncertainty and variability of the decision environment.
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lifecycle environmental efficiency, renewable energy, energy infrastructure, circular economy, multi-facet fuzzy sets, uncertainty, MOORAHow to Cite
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Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.
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References
Al Mubarak, F., Rezaee, R., & Wood, D. A. (2024). Economic, societal, and environmental impacts of available energy sources: A review. Eng, 5(3), 1232–1265. https://doi.org/10.3390/eng5030067
Amiri, M., Hashemi-Tabatabaei, M., Keshavarz-Ghorabaee, M., Kaklauskas, A., Zavadskas, E. K., & Antucheviciene, J. (2022). A fuzzy extension of simplified best-worst method (F-SBWM) and its applications to decision-making problems. Symmetry, 15(1), Article 81. https://doi.org/10.3390/sym15010081
Antohi, V. M., Fortea, C., Zlati, M. L., & Balsalobre-Lorente, D. (2026). Impact of energy transition, digital integration, and financial inclusion on European Union sustainable growth. Technological and Economic Development of Economy. https://doi.org/10.3846/tede.2026.26379
Arshed, N., Anwar, A., Abbas, M., & Mughal, W. (2024). Natural habitat vs human in competition for breathing space: need for restructuring clean energy infrastructure. Ecological Economics, 220, Article 108177. https://doi.org/10.1016/j.ecolecon.2024.108177
Brauers, W. K., & Zavadskas, E. K. (2006). The MOORA Method and its application to privatization in a transition economy, Control and Cybernetics, 35(2), 443–468.
Chakraborty, S., Datta, H. N., Kalita, K., & Chakraborty, S. (2023). A narrative review of multi-objective optimization on the basis of ratio analysis (MOORA) method in decision making. Opsearch, 60(4), 1844–1887. https://doi.org/10.1007/s12597-023-00676-7
Cozzolino, A., & Geiger, S. (2024). Ecosystem disruption and regulatory positioning: Entry strategies of digital health startup orchestrators and complementors. Research Policy, 53(2), Article 104913. https://doi.org/10.1016/j.respol.2023.104913
Crîstiu, D., d’Amore, F., & Bezzo, F. (2025). Optimal design of sustainable supply chains for critical raw materials recycling in renewable energy technologies. Resources, Conservation and Recycling, 218, Article 108250. https://doi.org/10.1016/j.resconrec.2025.108250
Dembińska, I., Kauf, S., Tłuczak, A., Szopik-Depczyńska, K., Marzantowicz, Ł., & Ioppolo, G. (2022). The impact of space development structure on the level of ecological footprint-Shift share analysis for European Union countries. Science of The Total Environment, 851, Article 157936. https://doi.org/10.1016/j.scitotenv.2022.157936
Fardnia, K., Yousefi, H., & Abdoos, M. (2025). A bibliometric analysis of carbon and water footprints in renewable energy: The post-COVID-19 landscape. Green Technologies and Sustainability, 3(3), Article 100162. https://doi.org/10.1016/j.grets.2024.100162
Farfan, J., & Lohrmann, A. (2023). Gone with the clouds: Estimating the electricity and water footprint of digital data services in Europe. Energy Conversion and Management, 290, Article 117225. https://doi.org/10.1016/j.enconman.2023.117225
Firoiu, D., Ionescu, G. H., Băndoi, A., Tănasie, A. V., & Tudor, S. (2026). Determinants of sustainable economic development in the EU: the role of innovation and infrastructure resilience. Technological and Economic Development of Economy, 32(2), 597–630. https://doi.org/10.3846/tede.2026.25897
Ganda, F. (2024). Investigating the relationship and impact of environmental governance, green goods, non-green goods and eco-innovation on material footprint and renewable energy in the BRICS group. Sustainability, 16(4), Article 1602. https://doi.org/10.3390/su16041602
Gilad, D., Borgelt, J., May, R., Dorber, M., & Verones, F. (2024). Biodiversity impacts of Norway’s renewable electricity grid. Journal of Cleaner Production, 469, Article 143096. https://doi.org/10.1016/j.jclepro.2024.143096
Hu, F., Peng, J., Wang, W., Shen, L., & Jia, M. (2025). Comparing the impact of various exercise modalities on old adults with Alzheimer’s disease: a Bayesian network meta-analysis. Complementary Therapies in Clinical Practice, 59, Article 101968. https://doi.org/10.1016/j.ctcp.2025.101968
Idroes, G. M., Hardi, I., Rahman, M. H., Afjal, M., Noviandy, T. R., & Idroes, R. (2024). The dynamic impact of non-renewable and renewable energy on carbon dioxide emissions and ecological footprint in Indonesia. Carbon Research, 3(1), Article 35. https://doi.org/10.1007/s44246-024-00117-0
Jovanovic, S., Zavadskas, E. K., Stevic, Z., Marinkovic, M., Alrasheedi, A. F., & Badi, I. (2023). An intelligent fuzzy MCDM model based on D and Z numbers for paver selection: IMF D-SWARA-Fuzzy ARAS-Z model. Axioms, 12(6), Article 573. https://doi.org/10.3390/axioms12060573
Karmakar, R., Tripathi, V., Kumar, P., Singh, N., & Kumar, R. (2024). The interplay of fossil fuels and natural disasters. In N. Singh & S. A. Babu (Eds.), Climate crisis and sustainable solutions: Strategies for adaptation, mitigation and sustainable development (pp. 91–106). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-7110-3_6
Khan, S. U., Zhao, Q., Wisal, M., Shah, K. A., & Shah, S. S. (2025). A data-driven Bayesian belief network influence diagram approach for socio-environmental risk assessment and mitigation in major ecosystem-and landscape-modifier projects. Sustainability, 17(8), Article 3537. https://doi.org/10.3390/su17083537
Kou, G., Zavadskas, E. K., Ayata, A., Yüksel, S., Dinçer, H., & Eti, S. (2025). Addressing hidden challenges in urban renewable energy integration via a hybrid-decision model. Technological and Economic Development of Economy, 31(6), 2023–2044. https://doi.org/10.3846/tede.2025.23903
Liao, H., Yang, S., Zavadskas, E. K., & Škare, M. (2023). An overview of fuzzy multi-criteria decisionmaking methods in hospitality and tourism industries: bibliometrics, methodologies, applications and future directions. Economic Research-Ekonomska Istraživanja, 36(3), Article 2150871. https://doi.org/10.1080/1331677X.2022.2150871
Lin, Y., Mahmood, M. A., Meng, W., & Ali, Q. (2024). Green economy transition in Asia Pacific: A holistic assessment of renewable energy production. Journal of Cleaner Production, 437, Article 140648. https://doi.org/10.1016/j.jclepro.2024.140648
Liu, Z., Zhu, S., Senapati, T., Deveci, M., Pamucar, D., & Yager, R. R. (2025). New distance measures of complex Fermatean fuzzy sets with applications in decision making and clustering problems. Information Sciences, 686, Article 121310. https://doi.org/10.1016/j.ins.2024.121310
Lu, C., Hua, X., Peng, Y., Tian, J., & Tian, G. (2024). Achieving ecological sustainability in OECD countries: The role of fiscal decentralization and green energy. Journal of Cleaner Production, 466, Article 142814. https://doi.org/10.1016/j.jclepro.2024.142814
Miller, T., Durlik, I., Kostecka, E., Kozlovska, P., Staude, M., & Sokołowska, S. (2025). The role of lightweight AI models in supporting a sustainable transition to renewable energy: A systematic review. Energies, 18(5), Article 1192. https://doi.org/10.3390/en18051192
Mukhtarov, S. (2024). Oil prices and the renewable energy transition: Empirical evidence from China. Utilities Policy, 91, Article 101840. https://doi.org/10.1016/j.jup.2024.101840
Olaitan, D., Bertagni, M., & Porporato, A. (2024). The water footprint of hydrogen production. Science of the Total Environment, 927, Article 172384. https://doi.org/10.1016/j.scitotenv.2024.172384
Rahadian, D., Anggadwita, G., Firli, A., & Adibroto, A. (2025). Environmental impact of renewable energy projects: Life cycle assessment and ecological footprint. In H. Dinçer & S. Yüksel (Eds.), Renewable energy projects and investments (pp. 95–116). Elsevier. https://doi.org/10.1016/B978-0-443-29869-1.00006-4
Ramesh, S. (2025). Renewable energy technologies. In The political economy of contemporary human civilisation, volume II: From quantum computing and nuclear fusion to war and conflict (pp. 183–218). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-84185-9_6
Rehman, A., Ma, H., Ahmad, M. I., Batool, Z., Tillaguango, B., & Oláh, J. (2025). The technology innovation paradox in Asia’s leading innovative economies: The importance of renewable energy and green financing. Technological and Economic Development of Economy, 31(6), 1953–1978. https://doi.org/10.3846/tede.2025.23722
Shafik, W. (2024). Energy policies and infrastructure requirements for efficient green buildings. In C. S. Meena, A. Kumar, V. P. Singh, & A. Ghosh (Eds.), Sustainable technologies for energy efficient buildings (pp. 212–240). CRC Press. https://doi.org/10.1201/9781003496656-10
Sohag, K., Husain, S., & Soytas, U. (2024). Environmental policy stringency and ecological footprint linkage: Mitigation measures of renewable energy and innovation. Energy Economics, 136, Article 107721. https://doi.org/10.1016/j.eneco.2024.107721
Tiwari, S., Mentel, G., Mohammed, K. S., Rehman, M. Z., & Lewandowska, A. (2024). Unveiling the role of natural resources, energy transition and environmental policy stringency for sustainable environmental development: Evidence from BRIC + 1. Resources Policy, 96, Article 105204. https://doi.org/10.1016/j.resourpol.2024.105204
Tverijonaite, E., & Sæþórsdóttir, A. D. (2024). Hydro, wind, and geothermal: navigating the compatibility of renewable energy infrastructure with tourism. Tourism and Hospitality, 5(1), 16–31. https://doi.org/10.3390/tourhosp5010002
Velykorusova, A., Zavadskas, E. K., Tupenaite, L., Kanapeckiene, L., Migilinskas, D., Kutut, V., Ubarte, I., Abaravicius, Z., & Kaklauskas, A. (2023). Intelligent multi-criteria decision support for renovation solutions for a building based on emotion recognition by applying the COPRAS method and BIM integration. Applied Sciences, 13, Article 5453. https://doi.org/10.3390/app13095453
Virah-Sawmy, D., & Sturmberg, B. (2025). Socio-economic and environmental impacts of renewable energy deployments: A review. Renewable and Sustainable Energy Reviews, 207, Article 114956. https://doi.org/10.1016/j.rser.2024.114956
Wang, F., Ge, Z., Yan, X., Zhang, W., Jiang, K., & Cai, B. (2024). The impact of low-carbon transition of energy sectors on regional water use in China. Sustainable Production and Consumption, 49, 560–570. https://doi.org/10.1016/j.spc.2024.07.009
Wang, S., Ding, X., Chen, J., Zhong, H., Liu, J., & Su, W. (2025). Virtual water-embodied carbon nexus in the new energy system: A case study of solar photovoltaic in China. Energy, 323, Article 135815. https://doi.org/10.1016/j.energy.2025.135815
Wang, Y., & Li, J. (2025). Multi-criteria decision-making for green maritime transportation: A hybrid Fuzzy AHP-MOORA approach to reduce marine pollution. Marine Pollution Bulletin, 216, Article 118023. https://doi.org/10.1016/j.marpolbul.2025.118023
Wehbi, H. (2024). Powering the future: An integrated framework for clean renewable energy transition. Sustainability, 16(13), Article 5594. https://doi.org/10.3390/su16135594
Yang, X., & Long, L. (2024). Renewable energy transition and its implication on natural resource management for green and sustainable economic recovery. Resources Policy, 89, Article 104624. https://doi.org/10.1016/j.resourpol.2023.104624
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