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Öğe Digital Transformation in Automotive Sector(Springer Science and Business Media Deutschland GmbH, 2023) Haktanır, E.; Kahraman, C.; Çebi, S.; Otay, İ.; Boltürk, E.The automotive industry is one of the industries that adapts the fastest to digital transformation (DT) in the world because of its standard production process and mass production. It is the sector that needs digitalization the most in order to gain a competitive advantage and increase its production quality. This chapter focuses on the DT in automotive production processes in both academic literature and industrial applications. It presents the development of automobile technology throughout the years, the type of robots used in automobile production, and an assessment of alternative robot technologies for digital production processes with a sensitivity analysis. The chapter is concluded by future research directions and suggestions. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Öğe Evaluation of sustainable energy systems in smart cities using a Multi-Expert Pythagorean fuzzy BWM & TOPSIS methodology(Elsevier Ltd, 2024) Otay, İ.; Çevik Onar, S.; Öztayşi, B.; Kahraman, C.Smart cities are technological settlements using the collected data to utilize resources and services effectively by combining information and communication technologies with various tools connected to the internet of things network. Sustainable energy systems in smart cities are systems can be evaluated by using multiple criteria decision making methods or methodologies based on several vague/imprecise evaluation criteria. In this paper, sustainable energy systems in smart cities are evaluated by interval-valued Pythagorean fuzzy (IVPF) sets with an integrated optimization based multi-expert fuzzy Best Worst Method (BWM) and TOPSIS methodology that can better handle uncertainty and vagueness in experts’ linguistic assessments than existing methodologies. The considered criteria are weighted by multi-expert IVPF Best Worst Method, which has become a popular weighting method in recent years. Later, the energy alternatives for a real case study are prioritized by multi-expert IVPF TOPSIS method. In the analysis, the most important criterion is found as Environmental sustainability (C1) with the defuzzified weight of 0.218 while the other weights are as initial investment (C2) with 0.196, operating expenses (C3) with 0.163, technical feasibility (C4) with 0.154, social acceptability (C5) with 0.140, and scalability (C6) with 0.129. The obtained results indicate that “Investing in advanced technologies” in a smart city with relative degree of closeness (RDC) value of 0.798, has been determined as the best alternative among the considered five alternatives. It is closely followed by “Developing a transportation system” with the RDC value of 0.681. Sensitivity analysis shows that the ranking results are quite robust and reliable. The comparative analysis with crisp BWM and TOPSIS methodology is applied to check the validity of the proposed methodology. © 2024 Elsevier LtdÖğe Interval-Valued Pythagorean Fuzzy AHP: Evaluation of Freight Transportation Strategies(Springer Science and Business Media Deutschland GmbH, 2023) Otay, İ.Freight transportation with the highest reliance on fossil fuels, has one of the vital roles on generating CO2 emission compared to other sectors. For that reason, choosing the best appropriate freight transportation strategy becomes an important problem that decision makers deal with. In this chapter, we focus on freight transportation strategy selection problem by tackling imprecision and vagueness in real life problems. The problem is modeled and solved using Analytic Hierarchy Process (AHP) based on one of the extensions of ordinary fuzzy sets named as Pythagorean fuzzy sets. In the application part, interval-valued membership and non-membership degrees are used to represent uncertainty in a better way. In the chapter, sensitivity analysis is performed and the results are compared with interval-valued intuitionistic fuzzy AHP method. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.