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Analysis of green energy in sustainable transportation in developing nations through a decision support model

Author

Listed:
  • Deveci, Muhammet
  • Gokasar, Ilgin
  • Chen, Yu
  • Wang, Weizhong
  • Karaismailoğlu, Ali Eren
  • Antucheviciene, Jurgita

Abstract

Countries are progressively integrating green energy sources into their long-term strategies in reaction to recent adverse geopolitical and environmental changes. Along with energy generation, lowering fossil fuel usage is crucial to solving the climate crisis. These efforts focus on the high-carbon transportation industry. Despite international transport and logistics emissions, individual transportation, public transit, and urban logistics contribute significantly to macro-scale carbon emissions. This change is necessary for sustainable global environmental solutions. Thus, a hybrid T-spherical decision-making model is presented to evaluate the role of green energy in transportation, integrating the logarithmic percentage change-driven objective weighting (LOPCOW) and simple weighted sum product (WISP) method. The proposed model is applied in a case study of evaluating the five alternatives using four aspects and fourteen subcriteria, which approves its practicality and efficacy. The T-spherical fuzzy LOPCOW method is utilized to measure the importance of criteria, which can eliminate negative values and dimensional inconsistencies. Then, the T-spherical fuzzy WISP method is developed to assess and prioritize the alternatives. The outcomes indicate that using the existing system (0.947) emerges as the best alternative for sustainability in developing countries. Further, sensitivity and comparison studies are organized to demonstrate the features of the presented model.

Suggested Citation

  • Deveci, Muhammet & Gokasar, Ilgin & Chen, Yu & Wang, Weizhong & Karaismailoğlu, Ali Eren & Antucheviciene, Jurgita, 2025. "Analysis of green energy in sustainable transportation in developing nations through a decision support model," Renewable Energy, Elsevier, vol. 244(C).
  • Handle: RePEc:eee:renene:v:244:y:2025:i:c:s0960148125003052
    DOI: 10.1016/j.renene.2025.122643
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