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Sustainable technology transition in bus fleet management: Integrating life cycle sustainability assessment and multi-objective optimization

Author

Listed:
  • Elagouz, Noura
  • Onat, Nuri C.
  • Kucukvar, Murat
  • Kharbeche, Mohamed
  • Kutty, Adeeb A.

Abstract

This study presents a comprehensive alternative fuel bus fleet management model for sustainable technology transitions. Life cycle sustainability assessment and multi-objective optimization approaches are integrated. The optimal allocation of Electric, Compressed Natural Gas (CNG), and Diesel buses (DBs) is calculated by considering the relative relevance of thirteen sustainability indicators and the boundary of the assessment. When only local sustainability impacts are considered, CNG and electric buses (EBs) manufactured in China are found to be dominant alternatives in the optimal fleet composition. However, when the system boundary is enlarged with consideration of all global supply-chain-related impacts, the optimal fleet composition significantly changes, and the model mainly favors CNG buses produced in Sweden. The results highlight two crucial aspects of sustainability assessment: 1) System boundary (consideration of local or global impacts) selection in life cycle sustainability assessment and 2) decision-makers priorities about social, economic, and environmental impacts significantly affect the selection of sustainable alternatives. Thus, management of sustainable technology transition, in the case of this paper, “sustainable bus fleet management,” requires a comprehensive and integrated consideration of three pillars of sustainability, impacts embodied in the global supply chains, and decision-makers priorities with consideration of both local and global indicators.

Suggested Citation

  • Elagouz, Noura & Onat, Nuri C. & Kucukvar, Murat & Kharbeche, Mohamed & Kutty, Adeeb A., 2025. "Sustainable technology transition in bus fleet management: Integrating life cycle sustainability assessment and multi-objective optimization," Technological Forecasting and Social Change, Elsevier, vol. 212(C).
  • Handle: RePEc:eee:tefoso:v:212:y:2025:i:c:s0040162524006978
    DOI: 10.1016/j.techfore.2024.123899
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