Celal Alpay Havle

The increasing complexity of supply chains in today's globalizing world has increased the importance of effective supply chain management. Consequently, businesses increasingly rely on new technologies to maintain flexibility, efficiency, and competitiveness. In this context, artificial intelligence (AI) technologies have the potential to offer significant opportunities at many critical junctures in supply chain management. The valuable contributions AI algorithms make to effective supply chains in areas such as supplier relationships, logistics planning, inventory management, demand forecasting, and fast and accurate decision-making demonstrate the strategic importance of this technology. However, harnessing the potential of AI technology in supply chain management requires overcoming several challenges, including technical infrastructure, human resource adequacy, data integrity, and security. In this perspective, this study is motivated by the need to identify the critical factors that will enable businesses to overcome these challenges and maximize the effectiveness of AI technologies. Therefore, this study aims to identify, model, and systematically and strategically analyze the key factors affecting the success of integrating AI into the supply chain for an effective supply chain. To this end, a model consisting of four main dimensions and 16 criteria is proposed based on a literature review and expert opinions based on Delphi method. To test the applicability and validity of the proposed model, an application was conducted using a case study in Turkey. The Analytic Hierarchy Process (AHP), one of the multi-criteria decision-making (MCDM) techniques, was used in this application. To overcome the uncertainty, intuition, and hesitancy due to human perception inherent in real- life decision-making processes, the AHP method was extended to interval-valued intuitionistic fuzzy (IVIF) sets. The analysis conducted reveals that elements such as “Strategic Vision”, “Quality of Algorithms” and “Data Security and Compatibility” are of critical importance for effective supply chain management.

There have been major changes in air transport. A new era called Aviation 4.0 has begun with the rise of contemporary digital technologies such as artificial intelligence and the internet of things. This has resulted in efficiency, security, lower costs, digitization, operational efficiency and customer experience. Aviation 4.0, dominated by digitization and digital transformation, has become a time of radical change. One of these changes can be seen in customers, who are the backbone of the industry. Digital technologies have completely changed customer expectations, behavior and perceptions of service quality. Classic service quality has given way to digital service quality (DSQ). Therefore, the purpose of this research is to strategically analyze DSQ from the perspective of Aviation 4.0. Fuzzy Analytic Hierarchy Process (FAHP) is used to prioritize DSQ criteria. A case study has been conducted in Turkish aviation industry to validate the study.

In recent years, sudden developments have occurred in technology. The widespread use of digital technologies and digital transformation have created an environment that allows advanced technologies to be developed and accepted by both the public and the business world. One of today's shocking developments is the rise of artificial intelligence (AI) technology. AI brings with it many opportunities both socially and economically and it has an impact on almost many sectors. One of these sectors is the aviation industry. It is extremely important for the world economy and countries. Furthermore, it has a complex structure where large data sets and changing customer demands are abundant. The use of AI technologies in the aviation industry can provide many competitive advantages. For this reason, focusing on AI requirements (AIR) is extremely critical. For this reason, this study aims to determine and analyze AIRs. The identified requirements are analyzed in a case study in Turkey aviation industry. For this purpose, cognitive map (CM) approach is adopted in the study to analyze the requirements. Modeling and solving real-life problems are complex and involve human perception that creates uncertainty. To overcome this complexity and uncertainty, the classical CM method is applied in fuzzy environment.

Today, international trade is extremely important for countries' economies. It is possible to show the ship's transport as one of the most important execution channels of this trade. International commercial maritime transport subject to many rules and regulations carries many risks in processes such as loading, handling and unloading. Commercial ports are the places where these risks are seen intensely. From this point, many risk components in terms of the process in the port, one of the international commercial port in Turkey, based on a risk analysis is tried to be evaluated in this study. Especially, loading and unloading processes are focused with the directions of industrial experts. The main dimensions of the risks in the port are determined via expert opinions, and the sub-criteria of these dimensions are revealed. In this way, a generic model is proposed based on failure mode and effect analysis and the model is digitized using intuitionistic fuzzy TOPSIS. Interpretations are made in the direction of the obtained analysis results.