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    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-Boon
    The 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.
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    Picture fuzzy compromise ranking of alternatives using distance-to-ideal-solution approach for selecting blockchain technology platforms in logistics firms
    (Elsevier ltd, 2025) Rani, Pratibha; Mishra, Arunodaya Raj; Alshamrani, Ahmad M.; Alrasheedi, Adel Fahad; Tirkolaee, Erfan Babaee
    The emergence of blockchain technology (BT) has indicated a new era for the supply chain and logistics industries wherein uncertainty significantly affects the establishment of suitable blockchain platforms for logistics firms. Moreover, uncertainty widely occurs in such realistic situations. This study develops a hybrid picture fuzzy information-based framework for assessing and ranking the blockchain platforms in the logistics firm. The experts' significance values are obtained using a distance measure and a rank sum model-based process under the picture fuzzy set (PFS) context. A novel distance measure is offered for PFSs, and its effectiveness over previously developed measures is demonstrated. To estimate the criteria weights, an integrated weighting model is utilized, which is based on the criteria importance through inter-criteria correlation (CRITIC) method for objective weights and the ranking comparison (RANCOM) approach for subjective weights. Moreover, the picture fuzzy compromise ranking of alternatives from distance to ideal solution (CRADIS) approach is utilized to rank the alternatives. To illustrate the superiority and practicality of the model, it is applied to a case study of blockchain platform selection including six alternatives and thirteen criteria to assess and rank the BTs options based on PFSs. The findings demonstrate that "Microsoft (1.0)" emerges as the best choice with the highest compromise measure among a set of six blockchain platforms in the logistics firm. Finally, sensitivity and comparative analyses are conducted to test the robustness and superiority of the developed method.