Disposal of healthcare waste is a key issue of environmental sustainability in the world. The amount of healthcare waste is increasing every day, and it is necessary to adequately dispose of this kind of waste. There are various treatments for healthcare waste disposal, of which incineration of healthcare waste is one of the solutions. This paper suggests a model for selection of the type of incinerators that best solve the problem of healthcare waste in secondary healthcare institutions in Bosnia and Herzegovina. In the selection of incinerators, extended sustainability criteria were applied. Basic sustainability criteria: environmental, economic, and social criteria, were extended with the technical criterion. To assess which of the incinerators best meets the needs for healthcare waste collection, multi-criteria decision-making was used. For this purpose, a combination of two MCDA methods was applied in this paper, namely full consistency method (FUCOM) and compromise ranking of alternatives from distance to ideal solution (CRADIS). The FUCOM method was applied to determine the weights of the criteria, while the CRADIS method was applied to rank the alternatives. The best alternative of the six alternatives used is A2 (I8-M50), followed by alternative A1 (I8-M40), while the worst ranked alternative is A5 (I8-M100). These results were confirmed by applying the other six methods of multi-criteria analysis and the performed sensitivity analysis. The contribution of this paper is reflected through a new method of multi-criteria analysis that was used to solve decision-making problems. This method has shown simplicity and flexibility in operation and can be used in all problems when it is necessary to make a multi-criteria selection of alternatives.

This manuscript aims to propose a new extension of the EDAS method, adapted for usage with single-valued neutrosophic numbers. By using single-valued neutrosophic numbers, the EDAS method can be more efficient for solving complex problems whose solution requires assessment and prediction, because truth- and falsity-membership functions can be used for expressing the level of satisfaction and dissatisfaction about an attitude. In addition, the indeterminacy-membership function can be used to point out the reliability of the information given with truth- and falsity-membership functions. Thus, the proposed extension of the EDAS method allows the use of a smaller number of complex evaluation criteria. The suitability and applicability of the proposed approach are presented through three illustrative examples.

There is not a single country in the world that is so rich that it can remove all level crossings or provide their denivelation in order to absolutely avoid the possibility of accidents at the intersections of railways and road traffic. In the Republic of Serbia alone, the largest number of accidents occur at passive crossings, which make up three-quarters of the total number of crossings. Therefore, it is necessary to constantly find solutions to the problem of priorities when choosing level crossings where it is necessary to raise the level of security, primarily by analyzing the risk and reliability at all level crossings. This paper presents a model that enables this. The calculation of the maximal risk of a level crossing is achieved under the conditions of generating the maximum entropy in the virtual operating mode. The basis of the model is a heterogeneous queuing system. Maximum entropy is based on the mandatory application of an exponential distribution. The system is Markovian and is solved by a standard analytical concept. The basic input parameters for the calculation of the maximal risk are the geometric characteristics of the level crossing and the intensities and structure of the flows of road and railway vehicles. The real risk is based on statistical records of accidents and flow intensities. The exact reliability of the level crossing is calculated from the ratio of real and maximal risk, which enables their further comparison in order to raise the level of safety, and that is the basic idea of this paper.

In this study, the performance of Sub-Saharan African railways systems (SSA) is assessed by using an integrated Entropy-MARCOS (Measurement Alternatives and Ranking according to COmpromise Solution) - based methodology. In the first phase, the Entropy method is employed to determine the weights of each sub-criterion of the decision model. This process identifies six main criteria, i.e., safety, security, internal business aspect, intermodal aspect, innovation, and learning aspect, and customer satisfaction which are further supplemented by 13 sub-criteria. In the second phase, the MARCOS method is used to rank the countries based on their railway performance assessment. Based on the results from the proposed method, a sensitivity analysis was carried out through a comparative analysis with seven other multi-criteria decision-making (MCDM) methods. The results of the study indicate that the most weighted sub-criterion is the labor productivity (internal business perspective criteria) followed by the terrorist incidence (security criteria) and the number of employees going through training/exposure sessions (innovation and learning perspective criteria). Moreover, it was revealed that Kenya is the best alternative in terms of its railway performance followed by Ethiopia, Cameroon, Nigeria, and Ghana. Based on the findings from this study, decision-makers can be assisted during the operative, designing, and planning investigations of the railway system through the consideration of these parameters as insert indicators. Also, the findings can help as a benchmark for the performance analysis of other railway systems in other African countries.

Identification of key indicators that cause safety challenges and vulnerable roads is crucial for improving traffic safety. This paper, therefore, entails to the development of a novel multiphase multicriteria decision-making (MCDM) model to evaluate the vulnerability of urban roads for traffic safety. This was conducted by using data from 17 important roads of a South African city and combining several methods such as CRiteria Importance through Intercriteria Correlation (CRITIC), data envelopment analysis (DEA), and measurement of alternatives and ranking according to compromise solution (MARCOS). Taking the elements of the DEA method, two new approaches for calculating the weights of criteria, the DEA-1 and DEA-2 models, were formed and integrated with the CRITIC method to obtain the final values of criteria weights. The MARCOS method was applied to evaluate 17 alternatives, for each direction separately. The aim of developing such a model is to use the advantages of obtaining objectivity of criteria weights through linear programming and correlation of values of the collected data. Also, the MARCOS method, as one of the newer and applicable methods, provides additional significance. Extensive sensitivity analyses were conducted to validate the model. The findings suggest that there are a certain number of roads that have a high level of safety for both directions, as well as a group of risky roads, which need traffic improvement measures. Thus, the results indicate that the model is sensitive to various approaches and can prioritize vulnerable roads comprehensively based on which safety measures can be taken.

To run a business successfully, quality determination and customer relations are very important factors. Therefore, it is necessary to measure quality and identify critical points of business. In this paper, an original integrated model for measuring the service quality of reverse logistics (RL) was developed for the company Komunalac Teslić, which was used as an example. The Delphi and Full Consistency Method (FUCOM) was applied to determine the significance of the quality dimensions, while a modified SERVQUAL (SQ) model was used to measure the service quality of the logistics. An original SQ questionnaire was formed with a total of 21 statements that were arranged in five standard dimensions. Examining the reliability of the questionnaire for quality dimensions using the Cronbach Alpha coefficient, it was found that the measurement scales for dimensions are appropriate in terms of user expectations, while in terms of quality perception there is no measurement scale for the empathy dimension. An extensive statistical analysis was then performed to verify the results. A Signum test was applied to identify the relationship between the responses in terms of expectations and perceptions, i.e., to examine their differences. The findings obtained by this research show that the expectations were higher than the perceived quality of the services and that there was a significant statistical difference for 12 of the SQ statements. For two statements, there was a significant statistical difference in favor of perceived quality compared to expectations. Based on the results obtained, the company must improve its services in order for service quality to be at a satisfactory level.

Traffic management is a significantly difficult and demanding task. It is necessary to know the main parameters of road networks in order to adequately meet traffic management requirements. Through this paper, an integrated fuzzy model for ranking road sections based on four inputs and four outputs was developed. The goal was to determine the safety degree of the observed road sections by the methodology developed. The greatest contribution of the paper is reflected in the development of the improved fuzzy step-wise weight assessment ratio analysis (IMF SWARA) method and integration with the fuzzy measurement alternatives and ranking according to the compromise solution (fuzzy MARCOS) method. First, the data envelopment analysis (DEA) model was applied, showing that three road sections have a high traffic risk. After that, IMF SWARA was applied to determine the values of the weight coefficients of the criteria, and the fuzzy MARCOS method was used for the final ranking of the sections. The obtained results were verified through a three-phase sensitivity analysis with an emphasis on forming 40 new scenarios in which input values were simulated. The stability of the model was proven in all phases of sensitivity analysis.

PurposeForests are negatively affected from rapid world population increase and industrialization that create intense pressures on natural resources and the possibility of an achieving circular economy. Forests can be considered as essential resources for providing sustainable society and meeting the requirements of future generations and circular economy. Therefore sustainable production tools as part of circular economy can be handled as one of the basic indicators for achieving circular economy. Accordingly the main purpose of this study is developing a novel rough – fuzzy multi-criteria decision-making model (MCDM) for evaluation sustainable production for forestry firms in Eastern Black Sea Region.Design/methodology/approachFor determining 18 criteria weights a novel Rough PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method is developed. Eight decision-makers (DMs) participated in the research, and to obtain group rough decision matrix, rough Dombi weighted geometric averaging (RNDWGA) operator has been applied. For evaluation forestry firms fuzzy MARCOS (Measurement of alternatives and ranking according to COmpromise solution) method was utilized.FindingsAfter application developed model the fourth alternative was found as the best. Sensitivity analysis and comparison were made to present the applicability of this method.Originality/valueDevelopment of novel integrated Rough PIPRECIA-Fuzzy MARCOS model with emphasis on developing new Rough PIPRECIA method.

Multi-criteria decision-making methods (MCDM) represent a very powerful tool for making decisions in different areas. Making a rational and reliable decision, while respecting different factors, is a challenging and difficult task; MCDM models have a great impact on achieving this goal. In this paper, a new MCDM technique is presented—ranking alternatives by defining relations between the ideal and anti-ideal alternative (RADERIA), which was tested for the evaluation of human resources (HR) in a transportation company. The RADERIA model has three key advantages that recommend it for future use: (1) the RADERIA model has a new approach for data normalization that enables defining the normalization interval according to the judgments of a decision-maker; (2) an adaptive model for data normalization of the RADERIA model allows tough conversion into various forms of decreasing functions (linear, quadratic equation, etc.); and (3) the resistance of the RADERIA model to the rank reversal problem. Furthermore, in many simulations, the RADERIA method has shown stability when processing a larger number of datasets. This was also confirmed by a case study with 36 alternatives, as considered in this paper. The results and verification of the proposed new method were acquired through a comprehensive verification of the complexity of the results. The complexity of the results was executed through (1) comparison with four other multi-criteria methods, (2) checking the resistance of the RADERIA model to the rank reversal problem, and (3) the analysis of the impact of changes in the measurement scale on the ranking results.

Edmundas Kazimieras Zavadskas, Irena Đalić, Željko Stević Institute of Sustainable Construction, Vilnius Gediminas Technical University, LT 10223 Vilnius, Lithuania. Faculty of Economics, University of Banja Luka, Majke Jugovića 4, Banja Luka 78000, Bosnia and Herzegovina. Faculty of Transport and Traffic Engineering, University of East Sarajevo, Vojvode Mišića 52, Doboj 74000, Bosnia and Herzegovina.

In this paper, based on the Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, a matrix of Threats, Opportunities, Weaknesses and Strengths (TOWS) was formed. It represents possible business strategies of the transport company. To choose the right plan, a model based on the integration of Fuzzy PIvot Pairwise RElative Criteria Importance Assessment (fuzzy PIPRECIA), Full Consistency Method (FUCOM) and Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS) methods, has been formed. A case study was conducted in the transport company from Bosnia and Herzegovina which provides services on the domestic and the European Union market for 20 years and belongs to a group of small and medium enterprises (SMEs). The SWOT analysis in this transport company was the basis for forming the TOWS matrix, which represents a set of possible business strategies. These strategies are the basis for developing five basic alternatives. The transport company should choose the best one of them for future business. The research focuses on forming a model for choosing the best strategy by which the transport company seeks to improve its business. Decision-making (DM) is not a straightforward sequence of operations, so the harmonization of methods as well as the verification of their results, are essential in the research. This model is applicable in SMEs that make these and similar decisions. Using this model, companies can adjust their business policies to the results of the model and achieve better business results. This research is the first that allows the use of such a model in making strategic decisions.

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Decision making is constantly present in agriculture. Choosing the wrong variety carries the risk that the investment in terms of sowing does not pay off at all. Therefore, it is necessary to choose the variety that gives the best results. In order to achieve this, it is necessary to apply multi-criteria decision-making of available varieties, which is, in this paper, done on the example of hybrid varieties of rapeseed that were created by selection at the Institute of Field and Vegetable Crops in Novi Sad. By applying fuzzy logic, a novel integrated Multi-Criteria Decision-Making (MCDM) model is developed and rapeseed varieties were evaluated. For determining four main and 20 subcriteria, fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method has been applied based on fuzzy Bonferroni operator, while for ranking alternatives fuzzy MABAC (Multi-Attributive Border Approximation area Comparison) method has been used. The results obtained using the novel integrated fuzzy MCDM model showed that the variety A2 – Zorica has the best results, followed by A1 - NS Ras, while the worst results were seen by the variety A5 - Zlatna. These results were confirmed using other five fuzzy MCDM methods. Sensitivity analysis—changing criteria weights showed the worst results in the variety A6 - Jovana, which took last place in the application of 18 scenarios. The presented model and the results of this research will help farmers to solve this decision problem.

Asphalt production plants play an important role in the field of civil engineering, but also in the entire economic system since the construction of roads enables uninterrupted functioning within it. In this paper, the ranking of asphalt production plants on the territory of the Autonomous Province of Vojvodina has been performed. The modern economy needs contemporary models and methods to solve complicated MCDM problems and, for these purposes, it has been developed an original Interval Rough Number (IRN) Multi-criteria decision-making (MCDM) model that implies an extension of two methods belonging to the field with interval rough numbers. After forming a list of eight most significant criteria for assessing the efficiency of asphalt production plants, the Interval Rough Number PIvot Pairwise RElative Criteria Importance Assessment (IRN PIPRECIA) method was developed to determine the significance of the criteria. A total of 21 locations with asphalt mixture installation were considered. For that purpose, seven asphalt production plants were included, and for their ranking, the IRN EDAS (Evaluation based on Distance from Average Solution) method was created. The aim of this paper is to develop a novel interval rough model that can be useful for determining the efficiency of asphalt production plants. Averaging in group decision-making (GDM) for both methods was performed using an IRN Dombi weighted geometric averaging (IRNDWGA) aggregator. The obtained results show that (A15) Ruma (SP)–Mačvanska Mitrovica–Zasavica has the best characteristics out of the set of locations considered in this study. However, Alternatives A6 and A19 are also variants with remarkably good characteristics since there is very little difference in values compared to the first-ranked alternative. Also, the obtained results have shown that the developed model is applicable, which is proven through a comparative analysis.