Purpose: Pharmaceutical supply chains (PSCs) need a well-operating and faultless logistics system to successfully store and distribute their medicines. Hospitals, health institutes, and pharmacies must maintain extra stock to respond requirements of the patients. Nevertheless, there is an inverse correlation between the level of medicine stock and logistics service level. The high stock level held by health institutions indicates that we have not sufficiently excellent logistics systems presently. As such, selecting appropriate logistics service providers (drug distributors) is crucial and strategic for PSCs. However, this is difficult for decision-makers, as highly complex situations and conflicting criteria influence such evaluation processes. So, a robust, applicable, and strong methodological frame is required to solve these decision-making problems.Design/methodology/approach: To achieve this challenging issue, the authors develop and apply an integrated entropy-WASPAS methodology with Fermatean fuzzy sets for the first time in the literature. The evaluation process takes place in two stages, as in traditional multi-criteria problems. In the first stage, the importance levels of the criteria are determined by the FF-entropy method. Afterwards, the FF-WASPAS approach ranks the alternatives.Findings: The feasibility of the proposed model is also supported by a case study where six companies are evaluated comprehensively regarding ten criteria. Herewith, total warehouse capacity, number of refrigerated vehicles, and personnel are the top three criteria that significantly influence the evaluation of pharmaceutical distribution and warehousing companies. Further, a comprehensive sensitivity analysis proves the robustness and effectiveness of the proposed approach.Practical implications: The proposed multi-attribute decision model quantitatively aids managers in selecting logistics service providers considering imprecisions in the multi-criteria decision-making process.Originality/value: A new model has been developed to present a sound mathematical model for selecting logistics service providers consisting of Fermatean fuzzy entropy and WASPAS methods. The paper's main contribution is presenting a comprehensive and more robust model for the ex ante evaluation and ranking of providers.

Purpose: Due to the current pandemic, the importance of logistics functions and decisions is well understood both at the level of companies and users. Logistics systems and related decisions are of vital importance in making supply chains effective, efficient and without disruption. Logistic pressure factors may emerge at different points along the logistics process, and given the role of logistics decisions as one of the important indicators of competitiveness, the determination of the logistics pressures that are likely to increase the costs of business, and their causative factors are a vital aspect of the logistics decision-making process. The study aims to provide assistance in the selection of the most ideal logistics decision by ranking the pressure factors affecting the logistics system, especially during the pandemic period for logistics enterprises operating in Ordu and Giresun provinces and which have a corporate identity.Design/methodology/approach: In this study, it is aimed to make the most ideal logistics decision selection by ranking the pressure factors affecting the logistics system, especially during the pandemic period for the logistics enterprises operating in Ordu and Giresun provinces and having a corporate identity. For that purpose interval-valued Pythagorean fuzzy (IVPF)–analytic hierarchy process (AHP) based combinative distance-based assessment (CODAS) methodology was used. Additionally sensitivity and comparison analysis were discussed.Findings: Competitive pressure was found as the most important pressure factor affecting the logistics system during the pandemic period. Change in regulatory rules was the pressure factor found to have the least effect on the logistics system. Using the weights of logistics pressure factors, “Operational Decisions” was found to be the most ideal logistics decision selection.Research limitations/implications: The findings provide support for the evaluation of logistical pressures and decision options by presenting a decision model capable of processing ambiguous information. During a pandemic or similar period, the study assists decision makers in determining a new route. The findings will also call business managers' attention to logistical pressure factors and lead them toward more realistic and feasible practices in the logistics decision-making process.Originality/value: This study provided an effective and applicable solution to a decision-making problem in the logistics sector including logistics pressure factors and the selection of logistics decisions. In this context, a methodology was presented that will allow businesses to self-evaluate their own logistics pressure factors and the selection of optimal solutions.

Today, economic development and development are extremely important. With the increasing need for energy in both the world and Turkish economy, the importance of ensuring the sustainability of the energy resources used and the security of energy supply is also increasing. Implementation of a sustainable energy system; It includes important factors such as efficient energy use together with sufficient, economical, safe and environmentally compatible energy supply. Energy is one of the main factors to consider in discussions of sustainable development. The main dimensions of sustainability in energy production are environmental protection and the economically and socially sustainable supply of energy resources in a way that is reliable, sufficient and financially accessible in the long run. For this reason, it is important for Turkey to identify sustainable energy problems and determine the right energy policy. In this study, the determination of sustainable energy problems and the problems of determining the right energy security policy in manufacturing enterprises in Samsun province in Turkey were made with multi-criteria decision making methods. As a result of this research, the most ideal energy security policy was “Resource Sharing” in the selection created by using the degrees of sustainable energy related problems in manufacturing enterprises. On the other hand, the most ideal energy security alternatives were realized as Resource Sharing (A4)>> Source Distribution (A3)>> Resource Diversification (A1)>> Price Security (A2), respectively.

Nowadays businesses transform into the faster, less costly, more flexible, and qualified structure because of developing world economy and fierce competition environment with each passing day. Outsourcing as one of the most essential concepts related to strategic management is considered to meet all the aforementioned conditions. In fact, logistics enterprises composing the main theme of this study tend to the outsourcing like other businesses and prefer it to increase the competitive power and specialized in main area of activity. Despite outsourcing in logistics enterprises provide numerous opportunity and advantage, some risks and problems emerge in case of not achieving the desired accordance and coordination. In this context risks and problems caused by the outsourcing for enterprises operated in international logistics activities in Giresun province are determined and ranked via the q-rung orthopair fuzzy subjective weighting as one of the multi-criteria decision analysis approaches. According to the results, essential risks and problems caused by the outsourcing for logistics enterprises were found as "Loss of control over the outsourcing firm", "Inaccurate sales pitches", "Layoffs" and "Unfulfilled contract provisions" respectively.

Urban earthquake risk management presents a challenging problem due to rising urban density, vulnerable infrastructure, and the unpredictability of disasters. This study introduces an innovative methodological framework that combines urban resilience assessment with a Fermatean Fuzzy Set (FFs)-based Multi-Criteria Decision-Making (MCDM) methodology to analyze and improve earthquake-resilience in Turkish cities. The study identifies and prioritizes 9 criteria affecting earthquake-resilience by integrating expert perspectives from 17 specialists in disaster risk management and urbanization in Turkey. The methodology benefits from the Fermatean Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique to avoid uncertainty and to rank criteria in expert assessments, and provides a better understanding of interdependencies between resilience criteria. The findings of the study prove that the most significant determinant is the degree to which decision-makers embrace and integrate resilience thinking, which was followed by good governance mechanisms and safe residential areas as important criteria. The suggested framework of the study creates solutions for methodological deficiencies in traditional risk assessments by including uncertainty and inadequate data, while offering practical recommendations for policymakers at the same time. Therefore, this research enhances the discourse on urban resilience, because it creates a comprehensive, flexible decision-support model to inform strategic planning and disaster management in high-risk urban areas regarding earthquakes.