Yazar "Kutty, Adeeb A." seçeneğine göre listele

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    Integrated modelling for sustainability assessment and decision making of alternative fuel buses
    (Elsevier, 2023) Elagouz, Noura; Onat, Nuri C.; Kucukvar, Murat; Ayvaz, Berk; Kutty, Adeeb A.; Osman Kusakci, Ali
    In this paper, a hybrid life cycle sustainability assessment (LCSA) model integrating multi region input–output analysis with novel multi-criteria decision-making techniques is proposed to assess three different fuel alternatives: compressed natural gas (CNG), electric buses (EBs), and diesel buses (DBs). A global hybrid LCSA model first quantified the environmental, economic, and social impacts of alternative fuel buses. The results were investigated in terms of multiple combinations of manufacturing and end-of-life scenarios by encompassing impacts embedded in the global supply chains taking Qatar as a case applied to the proposed model. The Interval-Valued Neutrosophic Fuzzy (IVNF)-Analytic Hierarchy Process with the Combined Compromise Solution (CoCoSo) approach is used to rank the alternative fuel buses based on their corresponding sustainability performance. The proposed model will help in quantitatively capturing the macro-level life cycle socioeconomic and environmental impacts along with optimally selecting alternatives to support sustainable urban transport policy towards a net-zero transportation system globally.
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    Measuring sustainability, resilience and livability performance of European smart cities: A novel fuzzy expert-based multi-criteria decision support model
    (Elsevier Ltd, 2023) Kutty, Adeeb A.; Küçükvar, Murat; Onat, Nuri C.; Ayvaz, Berk; Abdella, Galal M.
    Cities of the 21st century are buffeted with challenges, leaving potentially serious consequences on the future of urban living. Smartening development in cities has reinvented hopes of melting down predicaments in the early 2000s'. However, perplexed by the intensifying complexities of smart cities, urban living in smart cities needs to be evaluated with multiple conflicting criteria. Multi-criteria-based evaluations have been an answer to this case when attempting to gauge the composite performance of multiple decision-making entities. Several multi-criteria assessment techniques exist when dealing with selection problems. Nonetheless, the vagueness associated with the methodologies accompanied by uncertainties and complexities is inevitable in multi-attribute assessments. Fuzzy-based multi-criteria models are often an answer to such uncertainties when modelling real-world problems. The study thus presents a novel fuzzy expert-based multi-criteria decision support model, where the Analytical Hierarchy Process (AHP) is combined with the Evaluation based on Distance from Average Solution (EDAS) approach under a spherical fuzzy environment to create a composite index for comprehensive performance monitoring. The case of 35 high-tech European cities was used to empirically validate the proposed novel approach and thus construct a composite index. The composite index considers the intricate facet of integrating the concept of smart cities with sustainability, urban resilience, and livability under a unified framework. The fuzzy c-means partitioning technique was then used to segment smart cities into high, medium, and low-performing classes. A comparative analysis considering several distance-based approaches under a fuzzy environment with the SF-AHP and EDAS methodology is conducted to validate the robustness and stability of the proposed novel decision support model. The results revealed London as the top-ranked smart city that promotes sustainability, resilience, and livability in its current urban development model. Dusseldorf, Zurich, Munich, Oslo, Dublin, Amsterdam, Hamburg, Rome, Moscow, and Stockholm were no exemption from addressing the tritactic goals of sustainability, urban resilience, and livability well into their urban development plan and were placed in the high-performance cluster. The proposed model is efficient to express decision makers' preferences in a larger space and modelling functional parameters including hesitancy independently in the 3-dimensional domain. The model supports decision-makers and relocation analysts to assess the performance of smart cities and set targets to improve performance to remodel urban development to a more sustainable, resilient, and livable pattern.