Enes Emre Başar

Sensor selection in IoT-based smart healthcare systems is a complex fuzzy decision-making problem due to the presence of numerous uncertain and interdependent evaluation criteria. Traditional fuzzy multi-criteria decision-making (MCDM) approaches often assume independence among criteria and rely on aggregation operators that impose sharp transitions between preference levels. These assumptions can lead to decision outcomes with insufficient differentiation, limited discriminatory capacity, and potential issues in consistency and sensitivity. To overcome these limitations, this study proposes a novel fuzzy decision-making framework by integrating Quasi-D-Overlap functions into the fuzzy MARCOS (Measurement of Alternatives and Ranking According to Compromise Solution) method. Quasi-D-Overlap functions represent a generalized extension of classical overlap operators, capable of capturing partial overlaps and interdependencies among criteria while preserving essential mathematical properties such as associativity and boundedness. This integration enables a more intuitive, flexible, and semantically rich modeling of real-world fuzzy decision problems. In the context of real-time health monitoring, a case study is conducted using a hybrid edge–cloud architecture, involving sensor tasks such as heartrate monitoring and glucose level estimation. The results demonstrate that the proposed method provides greater stability, enhanced discrimination, and improved responsiveness to weight variations compared to traditional fuzzy MCDM techniques. Furthermore, it effectively supports decision-makers in identifying optimal sensor alternatives by balancing critical factors such as accuracy, energy consumption, latency, and error tolerance. Overall, the study fills a significant methodological gap in fuzzy MCDM literature and introduces a robust fuzzy aggregation strategy that facilitates interpretable, consistent, and reliable decision making in dynamic and uncertain healthcare environments.

This study examines the Logistics Performance Index (LPI) rankings developed by the World Bank from a methodological perspective and proposes an alternative decision support framework. LPI serves as an interactive tool that helps countries identify challenges, innovative solutions, and opportunities in their trade and logistics sectors. In this study, the efficiency of logistics operations in 118 countries was evaluated using an integrated multi-criteria decision-making (MCDM) model objectively weighted by the Entropy method. Countries were ranked using the MCRAT, SAW, TOPSIS, and FUCA methods. According to the findings, large datasets provide more robust insights for sensitivity analyses, and wider weighting coefficient combinations make the data more meaningful. In addition, it is suggested to use low-compensation methods instead of classical additive methods for LPI. Unlike other studies in literature, this research applied an innovative sensitivity analysis to test the robustness of the model and comprehensively examined the effects of weighting techniques based on over 2500 different MCDM results. The findings suggest that the FUCA method should be recommended to decision-makers for calculating LPI rankings due to its simplicity, practicality, low compensatory power, and low sensitivity. This study offers methodological improvements when evaluating logistics performance and provides significant contributions to decision-making processes. The findings are expected to provide a valuable resource for policymakers and businesses in understanding a country’s position in global competition, as well as serving as a reference for researchers evaluating the logistics performance of countries.

Bu çalışma, Türkiye'de perakende sektörü güveni, tüketici güveni, sanayi üretimi ve tüketici fiyatlarının perakende satış hacmi üzerindeki etkilerini incelemektedir. Resmi istatistik kurumlarının 2011:01 – 2023:11 dönemini kapsayan aylık verilerini kullanan çalışma, ilk olarak Fourier eşbütünleşme testini (FSHIN) kullanarak bu değişkenler arasındaki eşbütünleşme ilişkisini tespit etmektedir. Daha sonra, uzun dönem katsayılarını hesaplamak için Dinamik Sıradan En Küçük Kareler (DOLS) tahmincisi kullanılmıştır. Bulgular, sanayi üretim endeksi, tüketici güven endeksi ve tüketici fiyat endeksinin perakende satış hacmi üzerinde pozitif bir etkiye sahip olduğunu ortaya koymaktadır. Ancak analiz sonuçları, perakende sektörü güven endeksinin incelenen dönem boyunca perakende satış hacmini önemli ölçüde etkilemediğini göstermektedir.

The circular economy mostly relies on the reduction of fossil-based materials. Finding economically viable, low-cost, renewable, and biodegradable alternatives to plastic packaging is a significant challenge for this aim since it is widely used in the daily consumption of various products. Bioplastics are already considered promising substitutes for packaging materials since they are biodegradable, use renewable resources, and release fewer greenhouse gases. However, the shift from fossil-based to biobased materials also has its difficulties. This study uses qualitative data collected from three primary stakeholder groups of this transition, namely, R&D managers from the packaging industry, researchers, and policymakers. The research findings show that stakeholders are mostly in consensus regarding the advantages and challenges of the shift from fossilbased plastic to bioplastics. The knowledge and awareness of the process are highly compatible with the literature on the subject. Additionally, the findings suggest that although bioplastics have the potential to contribute significantly to sustainability goals and the circular economy greatly costs, lack of regulations, incentives and inadequate recycling infrastructure are major obstacles to change. The agreement of stakeholders on the matter of challenges also reveals the need for common ground for a solution.

The main objective of the present study is to examine whether Turkish households’ environmental knowledge effects environmentally responsible food choices through the mediating effect of households' environmental concerns. A face-to-face survey was conducted, resulting in 450 responses from households that have recently chosen environmentally responsible foods in Erzurum, Turkey. The hypotheses were tested using the partial least squares-based structural equation modelling (PLS-SEM) technique to detect how the mediating role of environmental concerns plays in the relationships between environmental knowledge and households’ environmentally responsible food choices. The findings confirm that environmental knowledge and environmental concerns positively and significantly enhance households' environmentally responsible food choices. It is also the first study to examine the mediational effect of environmental concerns on environmental knowledge and households’ environmentally responsible food choice relations. The findings of the study and its implications are expected to benefit the development of environmentally responsible foods in the Turkish food industry.

In this research, it is tried to determine whether brands can create customer engagement through virtual communities. In this direction, it is aimed to detect the effects of uses theory’s components which are functional value, hedonic value, co-creation value and social interaction value on the creation of customer engagement. Research data were collected from 400 customers who are members of the virtual community of BMW. Path analysis via LISREL 8.5 software was applied to the obtained data to test the hypotheses. As a result of the analysis, customers’ functional value, hedonic value, co-creation value perceptions have positive effects on customer engagement.

The Effect of Self-Construal on Statue and Role-Relaxed Consumption