Climate changes and the number of people in the world are increasingly affecting the environment. In order to reduce this impact, there are more and more alternatives to cars with internal combustion. Currently, the most used alternative is electric cars. This research aimed to rank electric cars according to their characteristics. It was selected 13 criteria according to which 20 alternatives were ranked. For this purpose, it was used two methods, DNMEREC (Double normalization Method based on the Removal Effects of Criteria) used to determine criterion weights objectively and DNCRADIS (Double normalization Compromise Ranking of Alternatives from Distance to Ideal Solution) method used to rank alternatives. Here, classical methods for multi-criteria decision-making (MCDM) are extended to contribute to a more stable ranking of alternatives. Unlike similar approaches, the same normalization has been used here, but in two ways, which represents an innovative approach in MCDM. The results of this approach have shown that the best-ranked alternative is A6 (Sono Sion), while the worst-ranked alternative is A2 (Smart EQ forfour). These results were confirmed with a comparative analysis of the results obtained using other MCDM methods and sensitivity analysis. The validation of the results and the application of the Spearman correlation coefficient have shown that the ranking of the alternatives is uniform and more stable when double normalization is applied than when classical methods with their normalization are used. In addition, this decision-making provides support to potential buyers for choosing electric cars.

The present age is moving through Industry 4.0 with massive technological developments. Supply chains have become digital, keeping sync with consumer demands and preferences. The recent pandemic has reinforced the need of embracing digital technologies in managing supply chains effectively. Therefore, it is necessary that supply chains adopt 5G mobile technologies. In this regard, the present study aims to discern the critical issues for the successful adaptation of 5G technologies for supply chain management (SCM) in developing countries such as India. The success factors for the adaptation of 5G in Indian supply chains are derived from the discussions made in the related past work regarding the challenges of implementing 5G technology. Then, the listed factors are finalised through initial rounds of face-to-face discussions with a focus group of five experts. Then, a q-rung-orthopair-fuzzy (qROFS)-based rating scale is used to rate the success factors. A new qROF-weighted-neutrality-average (q-ROFWNA)-based full-consistency method (FUCOM) approach for multicriteria decision-making (MCDM) problems involving group decision making is utilised to find out the critical success factors. Based on the comparative analysis of 17 success factors (grouped into four main factors), the spectrum availability, awareness of technology and usage, the development of supporting technologies and smart cities, and skill development are found to be the top five critical factors for the successful adaptation and implementation of 5G technologies in SCM. We further carry out a sensitivity analysis and validation test and observe that our model provides a reliable and stable solution.

This study deals with the selection of a sustainable supplier on the example of the agribusiness company Mamex from Bosnia and Herzegovina. The main problem of this research is the selection of a sustainable supplier as a part of the sustainable strategy of the Mamex company. One of the prerequisites is that suppliers must present sustainability principles in business by having an appropriate certificate. The results of the selection of sustainable suppliers are completed using a new hybrid fuzzy approach with the methods IMF SWARA (Improved Fuzzy Stepwise Weight Assessment Ratio Analysis) and fuzzy TRUST (multi-normalization multi-distance assessment) CRADIS (compromise ranking of alternatives from distance to ideal solution) methods. The innovative approach is reflected in the use of a combination of these methods, especially by combining the TRUST and CRADIS methods into one method. The IMF SWARA method shows that the most important main criterion is the economic criterion, while the least important is the social criterion. By applying the fuzzy TRUST CRADIS method, it is found that out of the observed six suppliers, the second supplier has the best indicators. These results are confirmed by other fuzzy methods: MABAC (multi-attributive border approximation area comparison), WASPAS (weighted aggregated sum product assessment), fuzzy SAW (simple additive weighting), MARCOS (measurement of alternatives and ranking according to compromise solution), ARAS (a new additive ratio assessment), and TOPSIS (technique for order preference by similarity to an ideal solution). This research shows that applying more normalization when ranking alternatives reduces the influence of individual normalizations, and this approach should be used in future research.

Understanding the level of economic freedom is an important indicator for investors and policymakers. The index of economic freedom, which the Heritage Foundation releases annually, is the most significant of the methods used to measure this indicator in practice, as this index evaluates the degree of market openness over the degree of fiscal and regulatory restraint. The research presented in this paper was conducted in order to establish the level of economic freedom in the Balkan countries. For this purpose, a multi-criteria ranking of Balkan countries based on economic freedom criteria was used. The weight of the criteria was determined using the Entropy method, and the countries were ranked using the CRADIS (Compromise Ranking of Alternatives from Distance to ideal Solution) method. These methods employed a double normalisation approach, and according to the results of this application, Bulgaria has the best indicators of economic freedom, while Montenegro has the worst, with sensitivity analysis and validation of the results confirming these findings. The approach of using double normalisation contributes to decision-making stability since the results of different methods are uniform when compared to the use of the classical approach in the case of multi-criteria analysis methods.

This research is focused to identifying the most suitable plum variety for establishing a new orchard, aiming to achieve optimal outcomes. To accomplish this goal, multi-criteria decision-making model has been developed striving to support decision-making process. The gained results are based on experience of experts engaged in assessment of certain plum varieties. The analysis of collected expert ratings has involved mutual use of 3 methods, where the FUll COnsistency Method (FUCOM) and CRiteria Importance Through Intercriteria Correlation (CRITIC) methods were applied to determine the weights of selected criteria. The results of applying these methods demonstrated that the Maretability criterion is of highest importance. Besides, the fuzzy MARCOS method (Measurement Alternatives and Ranking according to Compromise Solution) has been applied to rank the plum varieties according to expert ratings. Derived results revealed that the ?Cacanska rodna? and ?Stanley? varieties were ranked as the most favorable, while the ?Prezident? variety was assessed as the most unfavorable. Further, gained research outcomes were corroborated by the sensitivity analysis and results validation. This research contributes to improvement of fruit growing in BiH by previous adequate selection of available plum varieties towards the establishing of new orchards and yielding optimal outcomes.

According to applied TOPSIS multi-criteria decision-making method (Technique for Order of Preference by Similarity to Ideal Solution), in paper was selected adequate sales distribution channel in one enterprise active within the agro-food sector at the territory of Semberija (BiH). Decision makers, in this case represented by employed management in enterprise, have been evaluated five sales distribution channels in enterprise in line to previously defined criteria, i.e. products' characteristics, company's financial situation, consumer habits, production costs, geographic concentration, and products' assortment. The main goal of research was to create a model for optimal selection of sales channels, while derived results have been showed that the model "producer - seller (retailer) - consumer" is the most adequate towards the predefined selection criteria. In addition to the justified role of used method in selection of offered alternatives, article also represents a base that will serve in further research, whose focus would be on modernizing of existing and searching for new distribution channels in agricultural enterprises.

The hotel industry is undergoing significant change as a result of technological advancements and shifting guest preferences. Artificial intelligence (AI) is playing an increasingly important role in this transformation, allowing hotels to provide personalized, efficient, and sustainable experiences that meet the needs of modern travelers. This paper provides an overview of the role and application of AI in the hotel industry, highlighting its benefits and challenges as well as presenting case studies that show how hotels are currently utilizing AI technology. According to the review of literature, AI technology can be used to optimize hotel operations, improve the guest experience, and boost sustainability efforts. However, the use of AI technology in the hotel industry raises concerns about data privacy and security, job displacement, and the need for human supervision to ensure ethical and responsible deployment. Finally, the paper discusses the future directions of AI in the hotel industry, highlighting the emergence of voice technology and augmented reality as potential areas for future innovation. This paper adds to the growing body of literature on the use of AI in the hotel industry and provides useful insights for hotel managers, technology providers, and researchers.

The primary objective of this research paper is to investigate the potential impact of emergency remote teaching on the academic performance of undergraduate students, while also assessing the consistency of academic outcomes across various courses during the emergency transition to distance learning. The research methodology involves the collection of students' accomplishments and course passing rates spanning four consecutive academic years, from 2018/2019 to 2021/2022. The study identifies three distinct teaching environments: traditional, distance learning, and hybrid. The academic year 2018/2019 is designated as a pre-pandemic reference point. The subsequent years mark a transition from distance learning to a hybrid teaching model and a return to the traditional in-class environment. The analytical framework includes descriptive and correlation analyses, supplemented by an analysis of variance to derive meaningful insights. It is essential to highlight that the results obtained are further validated by the passing rates for the academic year 2022/2023, reinforcing the contemporary relevance and credibility of the research findings.

Znanost i razvoj inženjerske industrije osnova su razvoja svake zemlje. Sve zemlje su suočene s nedostatkom osoblja u području znanosti, tehnologije, inženjerstva i matematike. Stoga mlade ljude treba poticati na nastavak školovanja u tim područjima. Jedan od načina je integracija STEM nastave u osnovnim i srednjim školama. Bosna i Hercegovina (BiH) uključila se u svjetske tokove i zajedno sa stranim vladinim i nevladinim organizacijama uvela projekt ENABLE – BiH kojem je cilj jačanje STEM područja u nastavi i obrazovanju. Istraživanje za potrebe ovoga rada je provedeno u 9. osnovnoj školi u Brčko distriktu BiH, koja je sudionica u ovom projektu. Istraženo je postojanje razlike u stavovima učenika o STEM nastavi u odnosu na način pohađanja nastave, je li riječ o razrednoj ili predmetnoj nastavi. Korištene su 4 varijable koje su grupirane faktorskom analizom. Analizom je obuhvaćeno 117 učenika koji su ispunili anketni upitnik preko 80 %. Rezultati su pokazali da jedino u varijabli vrijednost STEM nastave postoji značajna statistička razlika između ocjena učenika razredne i predmetne nastave. Rezultati provedenog istraživanja pomoći će u daljnjem razvoju STEM nastave u BiH jer istraživanje pruža temelj za razumijevanje učeničke prihvaćenosti STEM nastave.

Many fuzzy concepts have been researched and described with uncertain information. Collecting data under uncertain information is a difficult task, especially when there is a difference between the opinions of experts. To deal with such situations, different types of operators have been introduced. This paper aims to develop the Maclaurin symmetric mean (MSM) operator for the information in the shape of the interval-valued spherical fuzzy set (IVSFS). In this article, a family of aggregation operators (AOs) is proposed which consists of interval valued spherical fuzzy Maclaurin symmetric mean operator (IVSFMSM), interval valued spherical fuzzy weighted Maclaurin symmetric mean (IVSFWMSM), interval valued spherical fuzzy dual Maclaurin symmetric mean (IVSFDMSM), and interval valued spherical fuzzy dual weighted Maclaurin symmetric mean (IVSFDWMSM) operators. In this paper, we studied an elucidative example to discuss the evaluation of multi-national companies for the application of the proposed operator. Then the obtained results from the proposed operators are compared. The results obtained are graphed and tabulated for a better understanding.

The research objectives presented in this paper are to assess the current state of Bosnia and Herzegovina’s rural tourism offer and to recommend a course of action for its development based on the model’s data that was gathered from subject-matter experts. In this paper, the multicriteria analysis method DEX (Decision EXpert) was utilized to assess the capacity of rural tourism in Bosnia and Herzegovina (BIH) and to obtain the results. All establishments were rated “very good”, seeing that they made use of the natural beauty that BIH has to offer. The outcomes of using this model were used to generate suggestions for the long-term development of rural tourism in BIH. The contribution of the employed model is in the developed starting points for the advancements of rural tourism in BIH, and the proposed model presents a novel method for evaluating a nation’s tourism potential that could be used in future studies in other tourism-related fields as well. The limitations of this paper stem from the fact that not all tourist establishments were considered due to the lack of unified records for all of these establishments. The model used in this research, on the other hand, is applicable to all tourist capacities, which is an advantage.

Abstract Innovation is crucial for the competitiveness of countries in the global market. Countries oriented to progress must invest in innovative activities. Using the example of the Western Balkan countries, this study investigated their innovative competitiveness. The indicators of the Global Innovation Index (GII) were used for the years 2019, 2020, and 2021. A multi-criteria approach was based on the innovative SMART approach. The weights of the criteria were determined using the CRITIC (criteria importance through intercriteria correlation) method, while the CRADIS (compromise ranking of alternatives from distance to ideal solution) method ranked the Western Balkan countries according to their innovative characteristics. The results showed that Montenegro had the best innovation indicators, followed by Serbia, while Albania had the worst indicators. This research showed an innovative approach of using four normalizations, and the advantages of these normalizations were used to contribute to stabilization in multi-criteria decision-making.