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    Evaluation of Industry 4.0 strategies for digital transformation in the automotive manufacturing industry using an integrated fuzzy decision-making model
    (Elsevier Ltd, 2024) Görçün, Ömer Faruk; Mishra, Arunodaya Raj; Aytekin, Ahmet; Simic, Vladimir; Korucuk, Selcuk
    The current paper proposes a methodological frame to identify the best Industry 4.0 (I4) strategy for the automotive manufacturing industry as a roadmap for companies to make a more straightforward digital transformation. We noticed a critical research gap when we performed an extensive literature review. Although there are many studies available that assess the readiness of companies for I4, only a few deal with decision -making in terms of sustainable development, and none have applied that to the automotive industry. Practitioners can apply the proposed model to determine the strategy based on technological developments in I4. The current paper proposes an extended version of the combined compromise solution approach with the help of the picture fuzzy sets. According to the paper 's results, by using the proposed model, developing a new business model based on technological improvements is the best strategy for the digital transformation of the automotive industry. Also, the lack of research and development implementations on I4 implementation is the most influential factor. Hence, practitioners in the automotive industry know the significance of research and development in reaching successful results for digital transformation. The acquired outcomes of the paper show that developing technology -based new business models is the best strategy for the automotive manufacturing industry concerning digital transformation instead of accommodating traditional business models and high technology utilization.
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    A novel interval-valued-q-rung orthopair fuzzy-additive ratio assessment model for evaluating logistics service quality
    (Institute of Electrical and Electronics Engineers Inc., 2024) Korucuk, Selcuk; Aytekin, Ahmet; Moslem, Sarbast
    Logistics service quality is crucial for companies to satisfy customers, gain an advantage over competitors, minimize costs, make effective business processes, and maintain corporate reputation. Companies work with 3PL service providers to ensure the quality of their logistics services. Now, companies adopt technology adoption models closely related to 3PL service and logistics service quality. In this context, this research aims to determine the ideal technology adoption model for ensuring logistics service quality in companies that employ 3PL services. It also seeks to determine the criteria and their significance levels that must be considered to attain the specified aim. A decision-making methodology, including IV-q-ROF-ARAS, has been used to attain these goals. The research revealed that the essential criteria for the quality of logistics services are 'reliability, regularity, flexibility, and service usability,' 'delivery time and request,' and 'availability of ordering information.' According to the study, logistics companies must be reliable and flexible. The 'technology acceptance model' has been identified as the ideal adoption model for Turkish companies receiving 3PL services. The study, which focuses on logistics service quality, 3PL service providers, and technology adoption structures, presents significant implications for the literature and companies.