Multi-criteria decision analysis (MCDA) applications consist of techniques that enable the decision maker to make clearer decisions in scenarios where there is more than one alternative and criterion. The general approach for sensitivity analysis in MCDA applications implies sensitivity to the weight coefficient. In this study, as an alternative approach, we reinterpret sensitivity by using the statistical relationship between the final ranking produced by an MCDA method and a constant external factor. Thus, we both verify through an anchor and reveal to what extent the change in the weight coefficient changes the external relations of MCDA. The motivation for this study is to propose an alternative sensitivity methodology. On the other hand, brand value is a parameter that contains critical information about the future of the company, which has not integrated into financial performance studies made with MCDAs before. To that end, the financial performance of 31 companies with the highest brand value in Turkey and trading on Borsa Istanbul between 2013 and 2022 was analyzed with seven different MCDA applications via integrating brand value into the criteria for the first time. The study’s findings revealed that the proposed innovative sensitivity tests produced similarly robust results as traditional tests. In addition, brand value has been proved to be an advantageous criterion to be implemented into MCDAs for financial performance problems through the sensitivity analysis made.

Priority sequencing criteria are of utmost importance in the determination of the sequence in which jobs are processed at workstations in parallel machine scheduling. The utilization of diverse priority rules can result in varied sequencing arrangements, hence requiring more experimentation to ascertain the optimal rule. Hence, it is imperative to formulate a thorough approach for the selection of the most suitable priority sequencing rule from the standpoint of management decision-making. The objective of this research is to analyze and compare six different priority sequencing rules in the context of parallel machine scheduling. Additionally, a methodology is proposed for the assessment and selection of the most suitable rule. This methodology combines the full consistency method (FUCOM) with the measurement of alternatives and ranking according to compromise solution (MARCOS) method, which are both multi-criteria decision-making techniques. When reviewing and selecting the optimal priority sequencing rule, seven parameters are taken into consideration. The weights of these criteria are computed using the FUCOM method, while the relative proximity values of all priority sequencing rules are derived by the MARCOS method. The data indicate that the priority sequencing rules are prioritized according to their level of importance. The approach outlined in this study is essential for workstation management to make well-informed decisions regarding the choice of the most advantageous priority sequencing rule for parallel machine scheduling.

Abstract The impact of logistics performance in the era of sustainable mobility on the overall economic development of a country is inevitable. It can even be said to represent an extremely important component in identifying economic conditions and provides the possibility of defining adequate strategies. In this article, the evaluation of the member countries of the European Union was carried out on the basis of the logistics performance index (LPI) according to the latest report of the World Bank (WB). A unique and original Multiple-Criteria Decision Making (MCDM) approach has been created, and it involves the application of four methods: Criteria Importance Through Intercriteria Correlation, Method based on the Removal Effects of Criteria, and Entropy and Fuzzy ROV (Range of Value). The weighting coefficients of six factors were obtained with the first three methods in crisp form, so they were converted into Triangular Fuzzy Number. The Fuzzy ROV method has been created for the first time in the literature and represents a great contribution from the methodological aspect. The results of the developed model and the applied steps show that there are certain differences in the rankings compared to the World Bank report, with a note that the best-ranked countries have maintained their positions. In addition, verification tests of the originally obtained results were created, with an emphasis on the importance of evaluation parameter values and their impact on the LPI ranking.

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Urban logistics implementation causes environmental pollution; therefore, it is necessary to consider the impact on the environment when carrying out such logistics. Electric vehicles are alternative vehicles that reduce the impact on the environment. For this reason, this study investigated which electric vehicle has the best indicators for urban logistics. An innovative approach when selecting such vehicles is the application of a fuzzy–rough method based on expert decision making, whereby the decision-making process is adapted to the decision makers. In this case, two methods of multi-criteria decision making (MCDM) were used: SWARA (stepwise weight assessment ratio analysis) and MARCOS (measurement alternatives and ranking according to compromise solution). By applying the fuzzy–rough approach, uncertainty is included when making a decision, and it is possible to use linguistic values. The results obtained by the fuzzy–rough SWARA method showed that the range and price of electric vehicles have the greatest influence on the selection of an electric delivery vehicle. The results of applying the fuzzy–rough MARCOS method indicated that the Kangoo E-Tech Electric vehicle has the best characteristics according to experts’ estimates. These results were confirmed by validation and the application of sensitivity analysis. In urban logistics, the selection of an electric delivery vehicle helps to reduce the impact on the environment. By applying the fuzzy–rough approach, the decision-making problem is adjusted to the preferences of the decision makers who play a major role in purchasing a vehicle.

: Within the evolving landscape of modern business, a proficient logistics sector stands paramount in fostering regional and global competitive edges. A country's logistics performance, gauged aptly, can influence not just the business outcomes of individual enterprises but also shape the nation's holistic logistics efficacy. This study delves into an examination of logistics standards in European Union (EU) countries, viewed through the lens of the Logistics Performance Index (LPI) as reported by the World Bank. The primary focus is on the LPI data for 2023, with a subsequent exploration of the EU’s performance trajectory from 2007 to 2018. The findings illuminate that specific EU countries consistently uphold superior logistics proficiency, while striving for advancements. Beyond these front runners, many EU countries manifest commendable logistics outcomes, positioning themselves favorably on the global stage.