Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2025Scopus SJRQ1/r/gumushane/10621
  A hybrid decision support system for transport policy selection: A case study on Russia's Northern Sea route in Artic region

  Yalçin, Galip Cihan; Limon, Elif Gurdal; Kara, Karahan; Limon, Onur; Gürol, Pinar; Deveci, Muhammet; Demirayak, Ozgur; Tomáková, Hana

  The selection of transport policies by countries is critical both for international relations and for the implementation of effective and sustainable transport practices. Countries consider numerous parameters when deciding on transport policies. This study aims to develop a Decision Support System (DSS) to assist countries in selecting transport policies and to demonstrate its applicability. The primary motivation of the research is to identify transport policies for Russia's Arctic region and to determine the best alternative policy based on expert evaluations. For this purpose, the IF-SIWEC-ARLON (Intuitionistic Fuzzy Sets - Simple Weight Calculation - Alternative Ranking Using Two-Step Logarithmic Normalization) hybrid method was developed as a DSS in this study. To implement this hybrid method, a decision model incorporating experts, criteria, and transport policies was first established. The contribution levels of experts to the decision-making process were calculated using IF sets. Next, the criteria weights were determined using the IF-SIWEC approach. Finally, the ranking of transport policies was carried out using the IF-ARLON method. An algorithm representing the application of this hybrid method was developed and applied to a case study focusing on Russia's transport policy selection process of Northern Sea Route (NSR) in the Arctic region. The results supported the successful application of the IF-SIWEC-ARLON hybrid method. Its robustness was tested through sensitivity analysis scenarios, while the consistency of the findings was verified via comparative analyses. The study concluded that the best transport policy for Russia's Arctic region is Improved regulatory control with strategic international partnerships, with the most influential criterion in the decision process identified as State interests, security, and sovereignty..

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  AtıfScopus11·WoS10·OpenAlex17

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• MakaleAçık Erişim2023Scopus SJRQ1/r/gumushane/12820
  Multi-criteria evaluation of medical waste management process under intuitionistic fuzzy environment: A case study on hospitals in Turkey

  Çelik, Sefa; Peker, İskender; Gök-Kısa, A. Cansu; Büyüközkan, Gülçin

  Waste management has come to the fore in the whole world with the increasing impact of the Covid-19 pandemic along with concerns about human health, environmental threats, and socio-economic factors, etc. Medical waste is one of the waste types that need special management processes including particularly collection, storage, separation, and disposal. Healthcare activities create a great amount of medical waste deriving from the hospitals. This study aims to determine the hospital that carries out medical waste management in the most effective way in Erzurum, Turkey. To handle intense uncertainty in the evaluation process, the case is analyzed by Intuitionistic Fuzzy Multi-Criteria Decision-Making (IFMCDM) methods. The present study contributes to the literature by focusing on a real case problem under IF environment in a Group Decision-Making (GDM) framework. Additionally, based on the literature review and expert judgments, the evaluation criteria relevant to the case are defined in this paper. To this end, a four-phased integrated methodology that involves Intuitionistic Fuzzy Weighted Averaging (IFWA), IF Analytical Hierarchy Process (IFAHP), IF Technique for Order Preference by Similarity to Ideal Solution (IFTOPSIS) and One-Dimensional Sensitivity Analysis, is conducted. Firstly, IFWA is aimed to express the significance levels of decision makers (DMs) based on their knowledge, qualifications and experiences. Secondly, IFAHP is used to calculate the importance weights of the decision criteria and IFTOPSIS is preferred to rank the available hospitals. Then, sensitivity analysis is employed to display robustness. According to the results, the most important criteria are Qualified personnel, Health institution infrastructure, and Control of waste, respectively and the most efficient hospital is determined.

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  AtıfScopus50·WoS48·OpenAlex65

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