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    Critical success factors of lean six sigma to select the most ideal critical business process using q-ROF CRITIC-ARAS technique: Case study of food business
    (Pergamon-Elsevier Science Ltd, 2023) Aytekin, Ahmet; Okoth, Basil Oluch; Korucuk, Selcuk; Mishra, Arunodaya Raj; Memis, Salih; Karamasa, Caglar; Tirkolaee, Erfan Babaee
    The current market conditions have forced Lean Six Sigma (LSS) upon businesses as one of the must-have practices. The practices have been credited with enhancing the efficiency of the operational and functional processes of enterprises from production to marketing, from personnel management to finance, all the while helping them augment their growth and profitability. LSS has the customer as its main focus and works to create added value for businesses through cost reduction and waste prevention hence can be considered as a process improvement practice. One priority area of improvement in most organizations is the assessment of Critical Business Processes (CBPs) as key processes in the success of businesses that must be tackled in line with the objectives of the businesses due to their extensive impact on customer satisfaction. For this purpose, this study evaluates and ranks the CBPs, and then select the most ideal CBP in food companies with corporate identity in Istanbul following the LSS success factors. Hence, the components attained from the literature are assessed using the suggested q-ROF CRITIC-ARAS method which is based on CRiteria Importance Through Intercriteria Correlation (CRITIC), Additive Ratio Assessment (ARAS) techniques and q-Rung Orthopair Fuzzy Sets (q-ROFSs). The findings demonstrate that the most important criterion for LSS success in food businesses is Top Management and Support, while Education and Culture is the least important. Furthermore, Enlightenment Approach is found to be the most ideal CBP based on LSS success factors.
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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.