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Öğe Accelerating the integration of the metaverse into urban transportation using fuzzy trigonometric based decision making(Pergamon-Elsevier Science Ltd, 2024) Deveci, Muhammet; Pamucar, Dragan; Gokasar, Ilgin; Martinez, Luis; Koppen, Mario; Pedrycz, WitoldMetaverse is defined as a fictional universe that could serve as a simulation environment of reality. Beginning in the past with games, it becomes increasingly integrated into human life as time passes. Metaverse usage is inevitable in every aspect of life. One of its potential application areas could be urban transportation. A novel fuzzy trigonometric based on the combination of the Full Consistency Method (FUCOM) and Combined Compromise Solution (CoCoSo) is proposed to rank three alternatives with twelve criteria under four major aspects: managerial, safety, user, and urban mobility. In the first stage, fuzzy FUCOM methods are used to calculate the weights of the criteria. In the second stage, the fuzzy trigonometric based CoCoSo method is applied to evaluate and rank the alternatives. The proposed model enables the nonlinear processing of complex and uncertain information using fuzzy trigonometric functions. The findings demonstrate focusing on a particular age group can make it easier to integrate the metaverse with urban transportation. The findings of this study have the potential to serve as a guide for decision-makers. The metaverse-based applications could be started by policymakers, which is a promising opportunity with potential boundaries beyond human comprehension making this statement weaker.Öğe Adoption of energy consumption in urban mobility considering digital carbon footprint: A two-phase interval-valued Fermatean fuzzy dominance methodology(Pergamon-Elsevier Science Ltd, 2023) Jeevaraj, S.; Gokasar, Ilgin; Deveci, Muhammet; Delen, Dursun; Zaidan, Bilal Bahaa; Wen, Xin; Shang, Wen-LongInterval-valued Fermatean fuzzy sets play a significant role in modelling decision-making problems with incomplete information more accurately than intuitionistic fuzzy sets. Various decision-making methods have been introduced for the different classes IFSs. In this study, we aim to introduce a novel two-phase interval-valued Fermatean fuzzy dominance method which suits the decision-making problems modelled under the IVFFS environment well and study its applications in the adoption of energy consumption in Urban mobility considering digital carbon footprint. The proposed method considers the importance and performance of one alternative with respect to all others, which is not the case with many available decision making algorithms introduced in the literature. Transportation is one of the most significant sources of global greenhouse gas (GHG) emissions. Numerous potential remedies are proposed to reduce the quantity of GHG generated by transportation activities, including regulatory measures and public transit digitalization initiatives. Decision-makers, however, should consider the digital carbon footprint of such projects. This study proposes three alternatives for reducing GHG emissions from transportation activities: incremental adoption of digital technologies to reduce energy consumption and greenhouse gases, disruptive digitalization technologies in urban mobility, and redesign of urban mobility using regulatory approaches and economic instruments. The proposed novel two-phase interval-valued Fermatean fuzzy dominance method will be utilized to rank these alternative projects in order of advantage. First, the problem is converted into a multi-criterion group decision making problem. Then a novel two-phase interval-valued Fermatean fuzzy dominance method is designed and developed to rank the alternatives. The importance and advantage of the proposed two-phase method over other existing methods are discussed by using sensitivity and comparative analysis. The results indicate that rethinking urban mobility through governmental policies and economic tools is the least advantageous choice, while incremental adoption of digital technologies is the most advantageous.Öğe Advantage prioritization of digital carbon footprint awareness in optimized urban mobility using fuzzy Aczel Alsina based decision making(Elsevier, 2024) Deveci, Muhammet; Gokasar, Ilgin; Pamucar, Dragan; Zaidan, Aws Alaa; Wei, Wei; Pedrycz, WitoldCity governments prioritize mobility in urban planning and policy. Greater mobility in a city leads to happier citizens. Although enhanced urban mobility is helpful, it comes with costs, notably in terms of climate change. Transportation systems that enable urban mobility often emit greenhouse gases. Cities must prioritize digital carbon footprint awareness. Cities may reduce the environmental impact of urban mobility while keeping its benefits by close monitoring and reducing the carbon footprint of digital technologies like transportation applications, ride-sharing platforms, and smart traffic control systems. The aim is to advantage prioritize three alternatives, namely doing nothing, upgrading and optimizing data centers and networks, and using renewable energy sources for data centers and networks to minimize the digital carbon footprint using the proposed decision making tool. This study consists of two stages. In the first stage, fuzzy Aczel-Alsina functions (fuzzy Aczel-Alsina weighted assessment - ALWAS method) based Ordinal Priority Approach (OPA) is proposed to find the weights of criteria. Secondly, fuzzy ALWAS Combined Compromise Solution (CoCoSo) model improved to evaluate and choose the best alternative among the three alternatives. The improved ALWAS-CoCoSo model enables flexible nonlinear processing of uncertain information and simulation of different risk levels. Besides, we proposed the improved fuzzy OPA algorithm for processing uncertain and incomplete information. The case study is provided to the decision-makers to advantage prioritize the alternatives based twelve criteria organized into four aspects, including digital carbon footprint, externalities, technical capability, and economics. The ranking results reveal that A(3) = 2.445 is the best among the three alternative, while A(1) = 1.705 is the worst alternative. The results show that the best way to reduce the digital carbon footprint is to use renewable energy sources to power data centers and networks (A(3)).Öğe Assessing alternatives of including social robots in urban transport using fuzzy trigonometric operators based decision-making model(Elsevier Science Inc, 2023) Deveci, Muhammet; Pamucar, Dragan; Gokasar, Ilgin; Zaidan, Bilal Bahaa; Martinez, Luis; Pedrycz, WitoldCurrent trends point to a not-too-distant future with qualitatively advanced interactions between humans and social robots. It is critical to consider the possibility of forming meaningful social relationships with robots when defining the future of human-robot interactions, as well as studying how these interactions will evolve to the point where humans are unable to distinguish between humans and robots in urban transportation. In this study, the advantages of using social robots in urban transportation are prioritized by using a multi-criteria decisionmaking tool, which consists of two consecutive stages, namely: i) a novel fuzzy sine trigonometry based on the logarithmic method of additive weights (fuzzy ST-LMAW) that is proposed to calculate the criteria weights; ii) a nonlinear fuzzy Aczel-Alsina function based the weighted aggregate sum product assessment (fuzzy ALWASWASPAS) that is developed to select and rank the alternatives. The proposed model enables flexible nonlinear processing of complex and uncertain information encountered in real applications. A case study is developed to rank three alternatives with twelve sub-criteria grouped into four aspects using the proposed method. The results show that the most advantageous alternative is to replace people with social robots as safety drivers in level four autonomous vehicles due to their possible impact on transportation.Öğe Evaluation of intelligent transportation system implementation alternatives in metaverse using a Fermatean fuzzy distance measure-based OCRA model(Elsevier Science Inc, 2024) Deveci, Muhammet; Mishra, Arunodaya Raj; Rani, Pratibha; Gokasar, Ilgin; Isik, Mehtap; Delen, Dursun; Ooi, Keng-BoonThe concept of the Metaverse, an immersive simulated world with parallels to reality, has gained significant prominence in recent times. Initially popularized through gaming, the Metaverse is now poised to infiltrate various aspects of human life. Intelligent transportation systems represent a promising yet challenging domain for Metaverse integration. Alternative implementations can create challenges in different dimensions. A comprehensive evaluation that takes challenges and opportunities for the different dimensions into account is required in decision making process of choosing the best implementation method. This study presents the development of a novel evaluation model, the Fermatean Fuzzy Operational Competitiveness Rating (OCRA) model, which incorporates the Fermatean Fuzzy Distance Measure (FF-DM) and Relative Closeness Coefficient (FF-RCC) techniques. The model is tested in a case to rank three alternative approaches, considering criteria of four key dimensions: managerial, safety, user, and urban mobility. In the first stage, the FF-DM and FF-RCC-based tool is employed to determine the criteria weights. In the second stage, an enhanced version of the Fermatean Fuzzy OCRA model, utilizing FF-DM and FFRCC, is employed to rank the alternatives. The findings indicate that policymakers' decisions in traffic management hold the potential to shape the trajectory of the Metaverse movement, representing an unparalleled opportunity with implications that extend beyond our current comprehension.Öğe Evaluation of metaverse integration alternatives of sharing economy in transportation using fuzzy Schweizer-Sklar based ordinal priority approach(Elsevier, 2023) Pamucar, Dragan; Deveci, Muhammet; Gokasar, Ilgin; Delen, Dursun; Koppen, Mario; Pedrycz, WitoldSharing economy transportation applications reduce car ownership and single-vehicle occupancy, contributing to the region's environmental sustainability. Metaverse is a promising new technology that combines sharing economy applications with transportation networks. By combining these two approaches, authorities can improve the sustainability of sharing economy applications. This study aims to assist decision-makers and authorities by developing a multi-criterion decision-making (MCDM) model that prioritizes three sharing economybased metaverse integration alternatives, namely integrating safety measures, payment systems, and the optimization of operations in the metaverse. A novel multi-criteria framework, including fuzzy Schweizer-Sklar norms based on the Ordinal Priority Approach (OPA) to assess the metaverse integration alternatives, is developed. To rank the alternatives, non-linear processing of information based on the fuzzy Schweizer-Sklar weight assessment method (SWAS) is proposed. A case study is developed to provide a foundation for the experts' evaluations using twelve criteria, which are organized into four aspects namely, economic, user, operational, and advancement. Finally, the results indicate that the most favorable approach is optimized operations via the integration of the sharing economy into the metaverse.Öğe Sustainable regional rail system pricing using a machine learning-based optimization approach(Springer, 2023) Gokasar, Ilgin; Karakurt, Ahmet; Kuvvetli, Yusuf; Deveci, Muhammet; Delen, Dursun; Pamucar, DraganRegional transport pricing is indeed very vital in urban settings where the transportation network is spread out across large areas and can influence travel behavior and the sustainability of cities. Therefore, in addition to existing pricing systems, such as flat fare, distance-based fare, and zonal pricing, this study proposes a sustainable approach to regional rail system pricing using rent prices and a transportation affordability index. The proposed model aims to reduce commuters' overall travel distance in order to reduce air pollution and maintenance costs for public transportation vehicles. Rent-based pricing encourages people to rent houses in regions that shorten their travel distances and fill a gap in the literature on regional rail system pricing by dealing with the decentralization of the cities. A two-step clustering and non-linear optimization modeling approach are proposed based on face-to-face surveys with regional rail system passengers. For various clusters of stations, rent per income rates and rental-based ticket prices were obtained. Furthermore, a sensitivity analysis is conducted to evaluate different conditions of the affordability index and rent prices in the studied regions. Compared to the current pricing system, ticket revenues increased by 3.88% and 1.68% in rent-based pricing.Öğe Sustainable regional rail system pricing using a machine learning-based optimization approach (25 OCT, 10.1007/s10479-023-05603-z, 2023)(Springer, 2024) Gokasar, Ilgin; Karakurt, Ahmet; Kuvvetli, Yusuf; Deveci, Muhammet; Delen, Dursun; Pamucar, Dragan[Abstract Not Available]
