Tedarik zincirinde etkin blokzincir ve yapay zeka uygulaması için yeni önerilen yaklaşımlar

Businesses worldwide are increasingly facing significant technological challenges in their operations. Today, organizations try to use Industry 4.0 technologies such as Internet of Things (IoT), Cloud Computing, Artificial Intelligence (AI), Blockchain, and so to increase productivity and solve business problems associated with data confidentiality, security, and information sharing. Blockchain and AI are two of these innovative technologies in the supply chain (SC) literature. Literature indicates that implementation in SCs involves both success and risk factors, and requires a comprehensive guide for practitioners. In addition, the literature shows industrial applications are inadequate and there is still gap for how to success, and therefore guidance based on customer requirements and effective system design is needed for successful implementation. Hence, the objective of this study is to propose success and risk factors for better understanding of Blockchain and AI, and analyze customer needs and design requirements for building effective SC structure based on these technologies. As all these topics involve various decision-making processes, a hybrid multiple criteria decision making (MCDM) approach is proposed where Incomplete Intuitionistic Fuzzy Preferences (IIFPs) under missing data are suggested as the backbone of the methodology. Success and risk factors are evaluated by combining IIFRs with Analytic Network Process (ANP), while customer and design requirements are evaluated by combining IIFRs with ANP and House of Quality (HoQ). Incorporation of those methods are unique and for the first time which adds value to the literature. With the experts in the field, case studies are implemented to demonstrate the feasibility of evaluation models.