Digital supply chains (DSCs) are value-driven and collaborative digital systems designed to generate business value for firms through various innovative technologies. Today, we are witnessing companies transitioning from traditional supply chain models to DSCs through digital technologies. The effective selection of digital suppliers during these digital transformation processes is a strategic research topic. Additionally, factors such as the proliferation of information and communication technologies, globalization, and the pandemic have contributed to the expansion of e-commerce platforms. In this rapid growth phase, identifying the right supplier is crucial for the success of e-commerce sites. This study aims to develop an innovative, integrated, and comprehensive decision-making methodology to assist e-commerce platforms in selecting appropriate suppliers for their DSCs. To achieve this, an extended fuzzy VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method is tested, where criteria and alternative evaluations made by decision-makers (DMs) are characterized by interval-valued intuitionistic fuzzy numbers (IVIFNs). The proposed decision mechanism is tested on the DSS problem of an e-commerce platform specializing in household products. Findings of the application, which uses three experts’ opinion to evaluate four digital suppliers based on the seven criteria, are discussed to help e-commerce sites conduct the DSS process more effectively.

Ranking several countries on a specific area may require the consideration of various factors simultaneously. To obtain a ranking of countries, the development of analytical approaches, which can aggregate opinions of a group of people on various criteria, is essential. The main aim of this study was to propose such a ranking approach for European countries in terms of healthcare services. To this end, a hybrid group decision-making model based on Hesitant Fuzzy Linguistic Terms Set (HFLTS) and Hesitant Fuzzy Technique of Order Preference by Similarity to Ideal Solution (HF-TOPSIS) is presented in this study. Importance degree of indicators were determined by the HFLTS-based group decision-making approach, and then HF-TOPSIS was used to obtain the rank of countries. According to the results obtained by the proposed model, Austria, Sweden and Finland are the best European countries in terms of healthcare services. Moreover, two comparative analyses, one for the utilization of different hesitant fuzzy distance measures in HF-TOPSIS and one for the ranking of countries obtained by utilizing TOPSIS, return some variations in country rankings. While Austria remained the best country for all distance measures in the hesitant fuzzy environment, Luxemburg was found to be the best for the deterministic case of TOPSIS.

Çok kriterli karar verme problemlerinin çözümlerinin bir kısmında, nesnelerin birden fazla kriter temelinde değerlendirilerek önceden belirlenmiş sınıflara atanması gerçekleştirilir. Bu tip problemler sınıfların sıralı olup olmamasına bağlı olarak çok kriterli sıralama veya sınıflandırma problemi olarak tanımlanırlar. Ters çok kriterli sıralama problemi ise, nesnelerin durumlarını değiştirebilecek olası eylemler arasında seçimler yapılması yoluyla nesnelerin atandığı sınıfların iyileştirilmesiyle ilgilenir. Bu çalışmada ters çok kriterli sıralama problemi için en düşük maliyetli iyileştirme ve belirli bir sınıfa atanan nesne sayısı hedefi arasında uzlaşık çözümü bulmayı amaçlayan bir hedef programlama modeli geliştirilmiştir. Geliştirilen model bina enerji sınıflarını iyileştirmeye yönelik bir uygulama çalışması üzerinde test edilerek elde edilen çözüm sonuçları değerlendirilmiştir.

Despite having child brings great responsibility, people want to have a child instinctively. In the context of childcare, parental responsibility requires that children should be born in good conditions and grow healthy and happily. Parents’ first responsibility is to ensure that children born in a healthy way. Nowadays, pregnant women visit doctor regularly and monitor the infant development. There are too many doctors and hospitals working in obstetrics area. The increasing number of alternatives and selection criteria makes it difficult to find a compromise solution in terms of conflicting selection criteria. Therefore, using analytical methods becomes necessary while making the decision of hospital choice for pregnancy follow-up. The main aim of this study is to develop a decision tool for determining the best hospital for pregnancy process. Because of the existence of linguistic evaluations in the decision process, Fuzzy Analytic Hierarchy Process is used in this study for determining the best alternative. An application of a real world problem is presented to demonstrate the applicability of the proposed methodology. Within the presented application weight of hospital selection criteria and priority values of five predetermined alternative hospitals in Ankara are calculated are determined. The obtained results of the study shows that staff quality and technical conditions are the most important criteria for hospital selection.

Classification is defined as the problem of assignment of objects to the predefined classes. In general view, classification problems divided into two groups: classification and sorting problems. Sorting problems define the case of existence of ordered classes for objects, while classes are not ordered in classification problems. Besides these two groups of classification problems, Inverse Multiple Criteria Sorting Problem (IMSCP) is also introduced into the literature in recent years. IMSCP deals with finding the possible actions that can change the assignment of objects to classes in order to obtain the desired classification of objects. The main aim in this study is to propose an extension of IMSCP with fuzzy parameters with a proper solution approach. A case study of building energy labelling improvement in an existing building site in Ankara is solved by using parametric fuzzy solution approach of Carlsson and Korhonen. Obtained results of the application presents the possible actions to improve the energy labels of the buildings within the site. Also, solution results show that the proposed model in this study can be used to improve current Building Energy Performance model in Turkey to a new one with efficiency improvement suggestions.

Having a baby brings new changes and challenges in parents’ life. There is a list of things which are required in order to provide a comfortable life for the baby. Since most of the people have limited economic resources, determination of the things to be bought becomes an important decision for parents. Moreover, the number of alternatives for the items in shopping list (bed, clothes, feeding equipment, stroller, etc.) is very much. Therefore, making a choice among alternative items is necessary. For each item, different alternatives have several advantages over another in views of different aspects. Consideration of several aspects of items would lead to good decisions, and parents must evaluate things in this way. It is aimed in this research to develop an analytic decision-making approach for stroller selection decision of parents. Hesitant fuzzy linguistic terms set (HFLTS) approach was presented in order to model the uncertain situations that the decision makers feel hesitant over various values of a linguistic variable. By using this pattern, elicitation of linguistic information is improved and thoughts of decision makers are represented better in decision models. Under the consideration of hesitant feelings of parents, HFLTS based group decision making approach is utilized to determine the optimum stroller. Apracticeof the presented model is presented to indicate its applicability and the presented decision approach seems useful for stroller selection.