This study proposes a novel hybrid Multi-Criteria Decision Analysis (MCDA) framework integrating Stochastic Fuzzy Normalization (STFN) with Stochastic Identification of Weights (SITW) to enhance the modeling and replication of sustainability rankings. The methodology is applied to a dataset of 21 European countries, utilizing six key indicators related to material consumption, waste generation, circular economy, environmental value added, and energy productivity. The proposed STFN–SITW–TOPSIS model successfully reconstructs the structure of the Sustainable Development Report 2022 ranking, achieving high fidelity through reidentification of both fuzzy normalizations and criteria weights. Comparative analyses demonstrate that SITW-based weights outperform conventional objective weighting methods such as Criteria Importance Through Intercriteria Correlation (CRITIC), Entropy, and Equal weighting in terms of rank alignment and structural consistency. A comprehensive sensitivity analysis confirms the model’s robustness and identifies the most influential criteria. The findings highlight the importance of integrating external reference information into MCDA frameworks, offering a data-driven, flexible, and explainable approach to sustainability assessment and broader decision support systems.

European countries’ efforts to achieve goals such as reducing the environmental damage caused by development require an increase in the share of renewable energy sources (RES) in energy-using industries. Such an energy policy makes it possible to reduce the consumption of fossil fuels, which contributes to improving the quality of the environment and reducing the depletion of natural resources. Efficient energy systems providing a secure energy supply should be diversified, i.e., based on a sustainable share of RES in the various branches of the economy. In the assessment of sustainable RES-based energy systems, multi-criteria decision analysis methods (MCDA), which allow simultaneous consideration of multiple aspects arising from the requirement for RES diversification, are proving useful. However, not all methods consider the strong sustainability paradigm including reduced criteria compensation relevant to sustainability assessment. In order to address this research gap, we propose the SSP-SPOTIS (Strong Sustainability Paradigm based Stable Preference Ordering Towards Ideal Solution) method to model the reduction of linear criteria compensation. The SSP-SPOTIS method has several advantages, such as robustness to ranking reversals, a simple algorithm, and the possibility to determine reference solutions individually. The mentioned advantages, combined with consideration of the strong sustainability paradigm, make the proposed approach useful in practical sustainability assessment problems. In this paper, the applicability of SSP-SPOTIS is demonstrated for the problem of assessing the sustainable share of RES in the economies of selected European countries. The results obtained indicate that the most sustainable share of RES is presented by Nordic countries such as Sweden, Norway, Denmark, and Finland. In addition, Estonia, and Austria were also among the well-scored countries.

This paper presents research involving the selection of floating photovoltaics (FPV) system constructions under Polish conditions using a multi-criteria method incorporating criteria compensation reduction following the strong sustainability paradigm.The applied method is called SSP-COPRAS (Strong Sustainability Paradigm based Complex Proportional Assessment).The selection was carried out among four FPV designs and one reference conventional ground-mounted PV (GMPV) system.Data were obtained from the reference research paper.The results proved that the FPV system has a noticeable potential for making it competitive with GMPV, especially when technical criteria and criteria compensation reduction play an important role.However, GMPV's higher ratings, especially in terms of economics, show that FPV would have to reach a higher product maturity to become realistically competitive.

This paper aims to introduce a novel Temporal SWARA-SPOTIS method for multi-criteria temporal assessment.The proposed method combines the Step-Wise Weights Assessment Ratio Analysis (SWARA) method for determining the significance values of particular periods and the Stable Preference Ordering Towards Ideal Solution (SPOTIS) method for the multi-criteria assessment.The developed method was applied for assessing the sustainable use of renewable energy sources (RES) by European countries in various branches of the economy and industry, considering multiple criteria and the dynamics of results change over time.The application of the proposed method is presented in an illustrative example covering the assessment of 30 selected European countries over the five years 2015-2019.The presented approach proved its usefulness in the problem investigated and provided reliable results indicating that the bestscored countries regarding sustainable use of RES are dominantly the Nordic countries.

Sustainable transport can contribute to many beneficial changes, such as reducing greenhouse gas emissions and pollutants into the atmosphere, improving the country's energy security, and enhancing energy efficiency.Therefore, it is essential to provide a framework for reliable measurement of sustainable transport, enabling its evaluation in terms of diversity and the significance of renewable energy sources (RES).This paper presents a methodological framework for a multi-criteria assessment of sustainable transportation.The proposed framework is based on three multi-criteria decision analysis (MCDA) methods: SPOTIS (Stable Preference Ordering Towards Ideal Solution), ARAS (Additive Ratio Assessment), and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution).The application of the proposed tool is demonstrated in an illustrative example of the assessment of European countries in terms of the share of alternative fuels in final energy consumption in road transport.The authors used the proposed framework to perform a comparative analysis considering three MCDA methods and two methods for determining the significance of evaluation criteria: equal and entropy weighting methods.The investigation has proven the practical suitability of the proposed tool in the problem of multi-criteria sustainable transport assessment.Furthermore, conducted analysis indicated that Sweden is characterized by the most sustainable transport in terms of significance and share of alternative fuels and RES and their diversification.

Assessment of the sustainability of countries for afordable and clean Energy requires a framework with relevant criteria, simultaneous inclusion of multiple criteria in the evaluation, and consideration of the dynamics of changes in performance over time. A wide variety of multi-criteria decision analysis (MCDA) approaches using different algorithms for multi-criteria aggregation are currently available. These methods are suitable for sustainability assessment because they allow the consideration of multiple criteria, the construction of a hierarchical structure of criteria, and the assignment of significance to criteria weights. However, MCDA methods have the limitation of being able to evaluate a data set for a single moment in time, which is insufficient for the sustainability paradigm. The mentioned limitation of MCDA motivates researchers to develop approaches that adapt MCDA methods to temporal assessment. The purpose of this paper is to present the application of a method called Data vARIability Assessment Technique for Order of Preference by Similarity to Ideal Solution (the DARIA-TOPSIS method) for multi-criteria temporal assessment of European countries for affordable and clean energy. This aspect of sustainability is included in Sustainable Development Goal 7 proposed by United Nations in the 2030 Agenda for Sustainable Development. The DARIA-TOPSIS method combines the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for multi-criteria evaluation with a Gini coefficient-based measure of result variability. The method has identified the best-scored countries in terms of implementing sustainable energy policies focused on affordable and clean energy, including Norway, Iceland, and Sweden.

Reliable assessment of countries’ energy policy implementation across multiple dimensions and sectors requires appropriate tools and methods. Monitoring the situation of countries in terms of renewable energy sources (RES) makes it possible to rank them and assess their progress. Multi-criteria decision analysis methods (MCDA) are valuable in this field because they allow considering multiple conficting criteria and prioritizing according to the preferences given by decision-makers. This work presents the application of two MCDA methods to assess the sustainable use of RES in different sectors in 30 European countries. The applied methods, which are COmbinative Distance-based ASsessment (CODAS) and Weighted Aggregated Sum Product Assessment (WASPAS), include in their algorithms additional adjustable parameters which enable performing sensitivity analysis of the evaluated alternatives. In this way, it is possible to determine the stability of the considered solutions in the rankings. The study identified the best-ranked countries regarding sustainable RES usage, including the Nordic countries such as Sweden, Norway, Iceland, and Finland. In addition to the Nordic countries, Austria is also among the best-scored countries.

Objective evaluation in problems considering many, often conflicting criteria is challenging for the decision-maker.This paper presents an approach based on MCDA methods to objectify evaluations in the camera selection problem.The proposed approach includes three MCDA methods, TOPSIS, VIKOR, COMET, and two criterion weighting techniques.Two ranking similarity coefficients were used to compare the resulting rankings of the alternatives: W S and rw.The performed research confirmed the importance of the appropriate selection of multicriteria decision-making methods for the solved problem and the relevance of comparative analysis in method selection and construction of objective rankings of alternatives.

E-commerce is currently one of the most rapidly growing branches of the economy. Increasing competition in the market for this field creates the need for continuous improvement of service quality and the need to stand out from others. More and more consumers are taking advantage of the opportunity to purchase products and services over the Internet. Many products on the market and the existence of many criteria to be taken into account create difficulties in making an objective decision when choosing the most appropriate product. Multi-criteria decision-making methods (MCDMs) are designed to help make the most appropriate decision in multi-criteria problems. Literature studies have proven that they are a widely used and suitable tool to assist choice when purchasing products and services. The possibility of their application in online sales as a consumer decision support tool seems promising both to meet customers’ growing needs and strengthen the position of online outlets in the market for these services. This paper presents an approach involving applying four MCDM methods TOPSIS, VIKOR, PROMETHEE II and COMET, in solving the multi-criteria problem of selecting the most favourable model of headphones. The obtained results confirm the usefulness and adequacy of the selected set of methods in choosing purchased products and devices and indicate the great potential of MCDM methods in the field of online commerce and services.

This paper presents a new approach to evaluate sustainable energy consumption in selected European countries for the industrial sector and to identify which country is leading in this respect. Energy consumption has been on a continuously rising trend due to industrial development, migration of people from rural to urban areas and growing energy demand in the service sector. Therefore, it is essential to increase the share of renewable sources in energy consumption because it allows reducing the share of non-renewable sources, which significantly contribute to carbon dioxide emissions to the atmosphere. The assessment of the effectiveness of actions taken to improve the sustainability of energy consumption requires the consideration of many different criteria. The practical usefulness of multi-criteria decision analysis (MCDA) methods in this task has been proven in the literature. The structure of the model evaluated was based on criteria made available by the European Statistical Office (EUROSTAT). The study was conducted using four MCDA methods (TOPSIS, VIKOR, COMET and PROMETHEE II). The results obtained proved the usefulness and adequacy of the selected MCDA methods in assessing the problem in question. It was possible to clearly identify the country with the most sustainable energy consumption in terms of the established principles.

Mobile phones are devices that are nowadays widely used by people. The development of technology has resulted in them being used not only for talking and messaging. They have functionalities that make them similar to personal computers. These devices are used to send and receive e-mails, browse the web, organize time, take pictures, play games, listen to music. There is also a possibility of installing various applications on them. The capabilities of these devices are closely related to their parameters, such as memory card size, internal memory, RAM, camera resolution. Price, which increases with the improvement of the parameters, also is a significant criterion of choice. Therefore, the choice of the most appropriate mobile phone model to match the consumer’s expectations requires the consideration of many criteria. Choosing the best option when making a decision is challenging because many factors influence the final decision. Additionally, they can be very diverse and difficult to take into account as a whole. An excellent solution to this problem is multi-criteria decision analysis (MCDA) methods, which support choosing from a wide variety of criteria. In this paper, four methods from the MCDA group - COMET, PROMETHEE II, VIKOR and TOPSIS - were used to determine the best mobile phone model among a group of alternatives. It is a complicated issue given the number of models available on the market and the number of parameters to consider when comparing. These methods have been successfully applied in the past to solve problems of similar complexity. All alternatives were analyzed using each method. Then the results were compared to each other to evaluate their similarity. Thus, the best mobile phone was selected for every applied method, and an attempt was made to find out the effect of MCDA method selection on the final ranking. The results obtained show that the tool based on MCDA methods is useful, appropriate, and effective in supporting consumer decisions when choosing mobile phones.

Decision-making problems in an uncertain environment can be solved using fuzzy multi-criteria decision-making methods. One such problem is the problem of housing selection, where it is challenging to determine data explicitly. Many people struggle with the difficulty of determining what conditions they would like to live in. It is hard for them to determine their housing preferences based only on data from the offers. Numerical values do not clearly define many parameters. Both apartment buyers and realtors use values such as much or little, precisely represented by fuzzy numbers. This paper proposes a solution to the housing selection problem using fuzzy MCDA techniques such as Fuzzy MMOORA, Fuzzy WASPAS, Fuzzy TOPSIS and Fuzzy VIKOR. Then the obtained ranking of alternatives was compared using ranking similarity coefficients such as weighted Spearman coefficient and WS ranking similarity coefficient. The proposed approaches produce similar results, indicating that the decision models reflect preferences well. At the end of the paper, conclusions and further research directions are presented.

Everyday situations each day more often require us to solve sometimes even complex decisional problems. Such conditions may include the problem of choice when purchasing services, products or devices. The ever-increasing assortment of products and services makes it more and more time-consuming for customers to choose the most suitable product for them. Following their intuition or considering only some selection criteria may result in an unsatisfactory choice. Decision making in multi-criteria selection problems needs the consideration of many factors, which are often conflicting. For this purpose, more people reach for multi-criteria decision methods (MCDM). These methods provide an easy way of solving a given problem under certain circumstances. With the increasing popularity of those methods, more are developed each day. This paper presents an approach based on four MCDM methods applied to solve the problem of choosing the most favourable CPU model available on the market regarding price and performance, among other criteria. For this purpose, COMET, TOPSIS, VIKOR and PROMETHEE II methods were performed. Later, a comparative analysis of the rankings obtained using the applied methods was conducted. Rankings provided by used methods were compared using correlation coefficients. The research showed that choosing a specific method is relevant for the results and that real-life problems can be successfully solved using multi-criteria decision methods. The obtained results confirm the suitability of MCDM methods as a decision support tool for consumers’ product selection. Applications based on MCDM allowing customers to perform multi-criteria analysis of a set of products could contribute to increased consumer satisfaction and growth of popularity and competitiveness of online stores providing them.