Step-wise Weight Assessment Ratio Analysis Research Articles

Cold Chain Logistics Management of Medicine with an Integrated Multi-Criteria Decision-Making Method.

Medicine is the main means to reduce cancer mortality. However, some medicines face various risks during transportation and storage due to the particularity of medicines, which must be kept at a low temperature to ensure their quality. In this regard, it is of great significance to evaluate and select drug cold chain logistics suppliers from different perspectives to ensure the quality of medicines and reduce the risks of transportation and storage. To solve such a multiple criteria decision-making (MCDM) problem, this paper proposes an integrated model based on the combination of the SWARA (stepwise weight assessment ratio analysis) and CoCoSo (combined compromise solution) methods under the probabilistic linguistic environment. An adjustment coefficient is introduced to the SWARA method to derive criteria weights, and an improved CoCoSo method is proposed to determine the ranking of alternatives. The two methods are extended to the probabilistic linguistic environment to enhance the applicability of the two methods. A case study on the selection of drug cold chain logistics suppliers is presented to demonstrate the applicability of the proposed integrated MCDM model. The advantages of the proposed methods are highlighted through comparative analyses.

COMPARISON OF THREE FUZZY MCDM METHODS FOR SOLVING THE SUPPLIER SELECTION PROBLEM

The evaluation and selection of an optimal, efficient and reliable supplier is becoming more and more important for companies in today’s logistics and supply chain management. Decision-making in the supplier selection domain, as an essential component of the supply chain management, is a complex process since a wide range of diverse criteria, stakeholders and possible solutions are embedded into this process. This paper shows a fuzzy approach in multi – criteria decision-making (MCDM) process. Criteria weights have been determined by fuzzy SWARA (Step-wise Weight Assessment Ratio Analysis) method. Chosen methods, fuzzy TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution), fuzzy WASPAS (Weighted Aggregated Sum Product Assessment) and fuzzy ARAS (Additive Ratio Assessment) have been used for evaluation and selection of suppliers in the case of procurement of THK Linear motion guide components by the group of specialists in the “Lagerton” company in Serbia. Finally, results obtained using different MCDM approaches were compared in order to help managers to identify appropriate method for supplier selection problem solving.

An integrated approach of SWARA and fuzzy COPRAS for maintenance technicians’ selection factors ranking

In spite of proliferation of maintenance work-force research, the maintenance community has deficient insight into the technicians’ selection process. Building on studies focusing on technical crew selection and uncertainties, this paper offers a framework to potentially remedy this lack. First, the establishment of a fuzzy-rooted structure and connection of it with step-wise weight assessment ratio analysis (SWARA) and complex proportional assessment of alternatives (COPRAS) can enlarge the research community’s comprehension of the competent selection process and could be initiated and completed by selection teams for maintenance technicians. Second, the put forward structure confronts the widespread description of where to obtain technicians, directing attention from the steps-to-selection to mere sources of obtaining technicians. Thus, this paper establishes the manner, in a particular context that the integration of fuzzy-SWARA and COPRAS could add to the research community’s perception of tackling uncertainties all around the maintenance technicians, while building on ideas from the human resource management literature as well as the technical engineering literature.

A multi-criteria decision-making framework for building sustainability assessment in Kazakhstan

Kazakhstan is the largest greenhouse gas emitter in Central Asia. The country has a significant renewable energy potential from solar, wind, hydro and biomass. Despite this, very small amounts of alternative energy sources have been used. Renewable sources such as wind, solar, small hydro and bioenergy currently contribute less than 1% of the country's energy mix. The building sector in Kazakhstan accounts for 30% of final energy consumption. In this regard, the role of the construction industry is extremely important due to its significant share in energy consumption and carbon emissions. This paper presents the results of the development of Kazakhstan's Building Sustainability Assessment framework. Stepwise weight assessment ratio analysis (SWARA) method was employed to calculate and allocate weights of assessment categories and indicators in the assessment framework. The reliability of the developed framework was validated by comparing its performance sensitivity with fours rating systems, namely, BREEAM, LEED, CASBEE, and SBTool for the categories of the proposed framework. The output of the research can produce a useful reference to the green building policymakers in the country. Also, the proposed framework can be adapted for use in Kazakhstan’s neighboring countries which share similar climatic zones and conditions.

Spatial Prediction of Landslide Susceptibility Using GIS-Based Data Mining Techniques of ANFIS with Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO)

The most dangerous landslide disasters always cause serious economic losses and human deaths. The contribution of this work is to present an integrated landslide modelling framework, in which an adaptive neuro-fuzzy inference system (ANFIS) is combined with the two optimization algorithms of whale optimization algorithm (WOA) and grey wolf optimizer (GWO) at Anyuan County, China. It means that WOA and GWO are used as two meta-heuristic algorithms to improve the prediction performance of the ANFIS-based methods. In addition, the step-wise weight assessment ratio analysis (SWARA) method is used to obtain the initial weight of each class of landslide influencing factors. To validate the effectiveness of the proposed framework, 315 landslide events in history were selected for our experiments and were randomly divided into the training and verification sets. To perform landslide susceptibility mapping, fifteen geological, hydrological, geomorphological, land cover, and other factors are considered for the modelling construction. The landslide susceptibility maps by SWARA, SWARA-ANFIS, SWARA-ANFIS-PSO, SWARA-ANFIS-WOA, and SWARA-ANFIS-GWO models are assessed using the measures of the receiver operating characteristic (ROC) curve and root-mean-square error (RMSE). The experiments demonstrated that the obtained results of modelling process from the SWARA to the SAWRA-ANFIS-GWO model were more accurate and that the proposed methods have satisfactory prediction ability. Specifically, prediction accuracy by area under the curve (AUC) of SWARA, SWARA-ANFIS, SWARA-ANFIS-PSO, SWARA-ANFIS-GWO, and SWARA-ANFIS-WOA models were 0.831, 0.831, 0.850, 0.856, and 0.869, respectively. Due to adaptability and usability, the proposed prediction methods can be applied to other areas for landslide management and mitigation as well as prevention throughout the world.

Prioritizing the solutions of reverse logistics implementation to mitigate its barriers: A hybrid modified SWARA and WASPAS approach

Abstract Reverse logistics has achieved recognition due to environmental disturbance, government policies, sustainability, globalization, warranty returns, end-of-life components, etc. However, business associations face numerous complexities and difficulties in executing reverse logistics activities due to the presence of several barriers. This research aims to identify and prioritize the solutions for mitigating the impact of barriers to reverse logistics implementation. This study proposes a hybrid framework using Modified Step-Wise Weight Assessment Ratio Analysis (SWARA) and Weighted Aggregated Sum Product Assessment (WASPAS) to achieve the objective of this research. The relative effect of barriers is evaluated using Modified SWARA, while WASPAS is used to prioritize the solutions of barriers to reverse logistics implementation. The empirical case investigation of an Indian electrical manufacturing industry is conducted to demonstrate the applicability of the proposed framework. The solution ‘Formulate and enforce strict yet supportive laws, policies for returns and end of life components’ is most prominent for mitigating barriers. This research presents a structured and systematic approach for organizations to mitigate reverse logistics implementation barriers through the proposed solutions. Also, this research lists out few novel barriers and its solutions from the case company prospective. The proposed solutions are effective in solving multiple barriers simultaneously. The research may give significant statute to the decision-makers and domain experts to build up their arrangement of organizational activity for short terms as well as for the long haul for implementing reverse logistics.

A Framework for Valuation and Prioritization of Patents Using a Combined MADM Approach. Case Study: Nanotechnology

Patent valuation and prioritization is one of the main activities for the management of intellectual property assets in an organization. So far, numerous attempts have been made to determine the value of patents, some of which have not been efficient due to ignoring some effective dimensions or considering the same importance for all aspects. To overcome this challenge, this research aims to provide a framework for valuing and prioritizing patents using a combination of MADM methods. For this purpose, first, the indicators for patent valuation and prioritization were taken from the literature and aggregated and finalized based on opinions of experts of technology management as well as nanotechnology in the form of a Delphi method. Second, the indicators were weighted, and their importance specified based on expert opinions using the questionnaire tool and stepwise weight assessment ratio analysis (SWARA) method. Third, the additive ratio assessment (ARAS) method was used to value and prioritize the patents. For this reason, 12 nanotechnology patents, registered in 2016 at the Iranian Administration of Registration of Documents, were valued and ultimately prioritized. The results from the criteria weights indicate that commercial and market potential and the economic value should be selected as the most critical dimensions. Also, among the indicators, the project investment cost, the costs of production and commercialization and the economic relevance, were selected as the most critical indicators. Among the 12 patents examined, “Gelatin-Chitosan/Carbon Nanotube Composite Scaffolds for Bone Tissue Engineering Applications” was identified as the most valuable patent.

Performance Evaluation Of The Hydropower Plants Using Various Multi-Criteria Decision-Making Techniques

Annual growth of 2.3 % since 1990 to 2017 in the hydropower sector in India indicates it holds a vital position in the growth of electricity generation in the country. For effective and efficient running of the hydropower projects, maintenance schedules and performance evaluation have to be done. Thus, this paper presents the performance evaluation of four different hydro-powerhouses belonging to a different class. Multi-criteria decision making (MCDM) method stepwise weight assessment ratio analysis (SWARA) is used to calculate the weights. The weights calculated by SWARA are employed to assess the performance scores or ranks of Indira Sagar Project (ISP), Canal Head Power House (CHPH) and River Bed Power House (RBPH) at Sardar Sarovar Narmada Nigam Ltd. (SSNNL) by integrating SWARA with the MCDM techniques like weighted aggregate sum product assessment (WASPAS), technique for order of preference by similarity to ideal solution (TOPSIS) and preference ranking organization method for enrichment evaluation (PROMETHEE). A comparative analysis of these integrated methods is presented for improved future studies in the area of decision making. The results in this paper show performance rankings of the available alternatives, calculated using integrated SWARA-WASPAS, SWARA-TOPSIS and SWARA-PROMETHEE methods. Performance ranks obtained by SWARA-WASPAS and SWARA-TOPSIS methods are in the order ISP, RBPH, CHPH and LSPH, which shows similarity with the on-field performances and are well suited for the performance evaluation of hydropower projects

SEVUCAS: A Novel GIS-Based Machine Learning Software for Seismic Vulnerability Assessment

Since it is not possible to determine the exact time of a natural disaster’s occurrence and the amount of physical and financial damage on humans or the environment resulting from their event, decision-makers need to identify areas with potential vulnerability in order to reduce future losses. In this paper, a GIS-based open source software entitled Seismic-Related Vulnerability Calculation Software (SEVUCAS), based on the Step-wise Weight Assessment Ratio Analysis (SWARA) method and geographic information system, has been developed to assess seismic vulnerability by considering four groups of criteria (i.e., geotechnical, structural, socio-economic, and physical distance to needed facilities and away from dangerous facilities). The software was developed in C# language using ArcGIS Engine functions, which provide enhanced visualization as well as user-friendly and automatic software for the seismic vulnerability assessment of buildings. Weighting of the criteria (indicators) and alternatives (sub-indicators) was done using SWARA. Also, two interpolation methods based on a radial basis function (RBF) and teaching–learning-based optimization (TLBO) were used to optimize the weights of the criteria and the classes of each alternative as well. After weighing the criteria and alternatives, the weighted overlay analysis was used to determine the final vulnerability map in the form of contours and statistical data. The difference between this software and similar ones is that people with a low level of knowledge in the area of earthquake crisis management can use it to determine and estimate the seismic vulnerabilities of their houses. This visualized operational forecasting software provides an applicable tool for both government and people to make quick and correct decisions to determine higher priority structures for seismic retrofitting implementation.

Dam construction material selection by implementing the integrated SWARA–CODAS approach with target-based attributes

The selection of the optimal material in engineering design procedures of any construction project due to the complexity of future circumstances could be considered as a complex problem. Similar complex selection problems can be efficiently implemented with the support of Multiple Attribute Decision Making (MADM) methods. The traditional MADM methods focus both on beneficial or non-beneficial attributes to determine a rank order of feasible alternatives and to select the best one. Nevertheless, like many engineering design problems, some attributes could be assessed based on target values. Therefore, target values of attributes along with beneficial and non-beneficial attributes makes a decision-making method more robust. Despite practical and functional applications of the target-based MADM approaches particularly in engineering design problems, only a few studies have made attempts to implement such methods. The presented study tackles a material selection problem by applying a hybrid decision-making approach supported on the Step-Wise Weight Assessment Ratio Analysis (SWARA) method and COmbinative Distance-based ASsessment (CODAS) technique containing target-based attributes. A case-study concerning the selection of optimal cement material type based on a real-world conceptual dam construction project in Iran has been analyzed by the proposed method considering two categories of attributes, i.e., managerial issues and technical specifications.

Assessing Quality of Mobile Applications Based on a Hybrid MCDM Approach

With the expansion in the quantity of cell phone utilization, mobile applications are developing significantly in today's high-tech environment. With this high demand, the quality of mobile applications is turning into a major issue. The organizations are still finding a way to develop quality applications. The number of quality models has already been proposed for assessing the quality of a mobile application but none of them provide a holistic view towards quality assurance. The present research work proposes an empirical evaluation of the SQM-MApp quality model using a hybrid multi-criteria decision-making approach named ELimination Et Choix Traduisant la REalité (ELimination and Choice Expressing REality) (ELECTRE-TRI) method and step-wise weight assessment ratio analysis (SWARA) method for ranking and determining weights of chosen quality factors respectively. The proposed approach specifically is for the mobile applications that are from the gaming domain. Also, validation of the proposed approach is performed by assessing the quality of gaming applications.

Internal Combustion Engine Analysis of Energy Ecological Parameters by Neutrosophic MULTIMOORA and SWARA Methods

The investigation for new innovative solutions to reduce transport pollution is a priority for the European Union (EU). This study includes energy and a sustainable environment, as well as transport, logistics, and information and communication technologies. Energy ecological parameters of internal combustion depend on many factors: fuel, the fuel injection time, engine torque, etc. The engine’s energy ecological parameters were studied by changing engine torques, using different fuels, and changing the start of the fuel injection time. The selection of the optimum parameters is a complex problem. Multicriteria decision-making methods (MCDM) present powerful and flexible techniques for the solution of many sustainability problems. The article presents a new way of tackling transport pollution. The analysis of the energy ecological parameters of the experimental internal combustion engine is performed using the neutrosophic multi-objective optimization by a ratio analysis plus the full multiplicative form (MULTIMOORA) and step-wise weight assessment ratio analysis (SWARA) methods. The application of MCDM methods provides us with the opportunity to establish the best alternatives which reflect the best energy ecological parameters of the internal combustion engine.

A multi-criteria decision-making framework for agriculture supply chain risk management under a circular economy context

PurposeThe implementation of circular economy strategies is one of the central objectives of several governments seeking a transition toward a sustainable development. Circular economy in agriculture deals with the production of agricultural commodities making an efficient use of resources and avoiding unnecessary waste and carbon emission generation. Disruptions in the production and supply of critical agricultural products can have serious negative repercussions for firms and consumers of the food supply chain. In recent decades, disruptions generated by natural disasters such as hurricanes, thunderstorms and floods have greatly impacted social communities and industrial sectors. Supply chain risks approaches are seen to contribute key elements to address the impacts of natural disaster toward the implementation of circular economy in agriculture, helping to prevent collapses in the production and supply of food. The purpose of this paper is to study and identify flood risk drivers and their effects on the sustainability of an agriculture supply chain in connection with a circular economy strategy. By using an extended Step-wise Weight Assessment Ratio Analysis method combined with a multi-criteria decision analysis, the most essential flood drivers with a degree of importance are reported here. Then, the authors propose an Evaluation of Data based on average ASsessment method, to rank different agricultural projects that pretend to mitigate the flood risks and its impacts on crop areas. The application of this research lies within the framework of a real agricultural project founded by the European Commission Scientific Section, called RUC-APS.Design/methodology/approachThe authors use management science-based tools to address circular economy in agriculture. The authors propose a multi-criteria-based methodology to assess the risks of flooding in crops areas. To validate the proposed methodology, a case example from Spain is discussed to rank different agricultural projects that pretend to mitigate the flood risks and its impacts on crop areas.FindingsThe proposed multi-criteria methodology confirmed a successful application to rank different agricultural projects that pretend to mitigate the flood risks and its impacts on crop areas. Organizations and firms in the agricultural business can use the methodology to identify risks drivers and to detect the best projects to mitigate the highest impacts of flooding risks in crops areas.Originality/valueThe authors use supply chain risks approaches to address the impacts of natural disaster on the implementation of circular economy in agriculture. The authors propose a robust multi-criteria-based methodology to assess the risks of flooding in crops areas and we used to determine the best mitigating projects to face flooding risks on crop areas.

A multi-criteria decision-making framework for selecting a suitable maintenance strategy for public buildings using sustainability criteria

This article tackles how to select an adequate maintenance strategy for public buildings by using novel multi-criteria decision-making (MCDM) models to validate their appropriateness for sustainable practices. The new innovation is the unique advantage of fuzzy axiomatic design (FAD) to consider the design requirements for public buildings. The stepwise weight assessment ratio analysis (SWARA), weighted additive sum product assessment (WASPAS), fuzzy axiomatic design (FAD) and the additive ratio assessment (ARAS) are competently integrated. Questionnaire data from a public building was used to evaluate and order the criteria in the rehabilitation exercise. The principal results are: For environmental and social criteria, the most and least suitable maintenance strategies are condition-based (S3) and preventive maintenance (S1) strategies, respectively. The most and least suitable maintenance strategies are corrective maintenance (S4) and S1 (ARAS), S4 and S1 (FAD), S1 and S3 (weighted additive method), respectively. Based on the aggregated criteria and the solution methods, the most suitable order for the case study maintenance strategies is S2>S1>S3>S4. This study shifts attention to MCDM from the old literature perspectives of risks and life-cycle methods in the strategic choice of maintenance for public buildings.

Prospecting for polymetallic mineralization using step-wise weight assessment ratio analysis (SWARA) and fractal modeling in Aghkand Area, NW Iran

The processing and analysis of airborne geophysical data for polymetallic mineralization in Aghkand area at East Azerbaijan Province (NW Iran) were carried out with a view to establishing the prospective mineralized zones. This was done in two stages: (i) The magnetic and radiometric data were used to produce different maps including total magnetic intensity (TMI), reduction to the pole (RTP), magnetic lineation, intrusive, ternary, alteration, and other maps as well as the updated geological map of the area which when correlated with the geological map shows the concentration of potential areas at the western part; and (ii) the fractal model of concentration-area (C-A) was applied to find the main anomalous areas of RTP map, and the results were checked with geological units. The main anomalous areas in the RTP map were found from the western to the southwestern part of the area, consisting of andesite, tuffs, and dacite rocks. For validation purposes, the log-ratio matrix was used to correlate the main anomalous areas derived from the RTP map with mineral potential map. The prospective map of potential polymetallic mineralization was developed through integration of different exploration datasets using step-wise weight assessment ratio analysis (SWARA). The overall accuracy rate of RTP map when correlated with mineral potential map is 99%. Results are in good compliance with airborne geophysics data and indicate the presence of intrusive masses which is probably located in the western part of the study area.

An integrated fuzzy SWARA and fuzzy AD approach for outsourcing provider selection

PurposeUnlike previous literature, this study offers a novel integrated fuzzy approach to the field of outsourcing decisions. The purpose of this paper is to use design ranges of evaluation criteria that satisfy the functional requirements (FRs) of decision makers to solve the outsourcing provider selection problem.Design/methodology/approachIn this study, considering the expected significance of outsourcing evaluation criteria, and the FRs of decision makers expressed in linguistic terms, a robust multi-criteria decision-making (MCDM) tool based on the integrated use of fuzzy Step-wise Weight Assessment Ratio Analysis and weighted fuzzy axiomatic design methods is proposed for use in decision process.FindingsThe proposed method is applied to a Turkish chemical company. A sensitivity analysis is performed and the outcomes of the proposed integrated framework are compared with those of other MCDM methods such as fuzzy-based Technique for Order Preference by Similarity to Ideal Solution, fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje and fuzzy Multi-Objective Optimization on the basis of Ratio Analysis. This validates the usefulness and practicality of the proposed methodology.Practical implicationsThe main contribution of this study is that it defines specific requirements that will assist company managers in eliminating alternatives that do not satisfy the needs and expectations of their company.Originality/valueThis paper compares the present study with other studies in the field of manufacturing. Additionally, it provides a well-documented case study, which makes the paper of value to researchers interested in the practical applications of MCDM methods.

Comparative Evaluation of Sustainable Design Based on Step-Wise Weight Assessment Ratio Analysis (SWARA) and Best Worst Method (BWM) Methods: A Perspective on Household Furnishing Materials

For a few years, there has been an increasing consciousness to design structures that are concurrently economic and environmentally responsive. Eco-friendly inferences of building designs include lower energy consumption, reduction in CO2 emissions, assimilated energy in buildings and enhancement of indoor air quality. With the aim of fulfilling design objectives, designers normally encounter a situation in which the selection of the most appropriate material from a set of various material alternatives is essential. Sustainability has been developing as a new concept in all human activities to create a better balance between social, environmental and economic issues. Designing materials based on the sustainability concept is a key step to enable a better balance because there is no need to re-structure phases and procedures to make the system more efficient in comparison to previous models. Some of the most commonly used materials are household furnishing materials, which can be electrical devices, kitchen gears or general furnishing materials. The volume of production and consumption of these materials is considerable, therefore a newer sustainable plan for a better designed system is justifiable. In the literature, the application of multi-attribute decision-making (MADM) methods has been found to be very suitable for evaluating materials and developing general plans for them. This study contributes by applying two approaches based on MADM methods for weighting the criteria related to the sustainable design of household furnishing materials. Step-Wise Weight Assessment Ratio Analysis (SWARA) and Best Worst Method (BWM) are two specialized and new methods for weighting criteria with different approaches. This paper has not only investigated the weighting of important and related criteria for sustainable design but has also evaluated the similarities and differences between the considered weighting methods. A comparative study of SWARA and BWM methods has never been conducted to date. The results show that, except pairwise comparisons, SWARA and BWM are certainly similar and in some cases SWARA can be more accurate and effective.

Hybrid artificial intelligence models based on a neuro-fuzzy system and metaheuristic optimization algorithms for spatial prediction of wildfire probability

This study provides a new comparative analysis of four hybrid artificial intelligence models for the spatially explicit prediction of wildfire probabilities. Each model consists of an adaptive neuro-fuzzy inference system (ANFIS) combined with a metaheuristic optimization algorithm, i.e., genetic algorithm (GA), particle swarm optimization (PSO), shuffled frog leaping algorithm (SFLA), and imperialist competitive algorithm (ICA). A spatial database was constructed based on 159 fire events from the Hyrcanian ecoregion (Iran) for which a suite of predictor variables was derived. Each predictor variable was discretized into classes. The step-wise weight assessment ratio analysis (SWARA) procedure was used to assign weights to each class of each predictor variable. Weights indicate the strength of the spatial relationship between each class and fire occurrence and were used for training the hybrid models. The hybrid models were validated using several performance metrics and compared to the single ANFIS model. Although the single ANFIS model outperformed the hybrid models in the training phase, its accuracy decreased considerably in the validation phase. All hybrid models performed well for both training and validation datasets, but the ANFIS-ICA hybrid showed superior predictive performance of spatially explicit wildfire prediction and mapping for the dataset. The results clearly demonstrate the ability of the optimization algorithms to overcome the over-fitting problem of the single ANFIS model at the learning stage of the fire pattern. This study contributes to the suite of research that seeks to obtain reliable estimates of relative likelihoods of natural hazards.

Planning the application of blockchain technology in identification of counterfeit products: sectorial prioritization

Abstract This paper Decision making at the top level is very complex. One important responsibility of the policy makers and the governance system is to plan the safety and security to its citizen and consumers for the firms. This research address of the main concern of counterfeiting goods in today’s time. This research identify the potential and needs of the distributed ledger technologies like blockchain and their application potential to combat the problem of counterfeiting in Indian economy. The research uses SWARA (Step-wise Weight Assessment Ratio Analysis)-WASPAS (Weighted Aggregated Sum Product Assessment) methodology after expert opinion gathered to understand the problem better and it results into the prioritization of application of blockchain in different industries. SWARA is applied to evaluate the weights of the criteria and WASPAS to evaluate and prioritize the alternatives.

The evaluation of websites in the textile industry by applying ISO/IEC 9126-4 standard and the EDAS method

Nowadays, modern companies perform the largest part of their communications with their consumers over the Internet, usually in order to promote their own products and services. There are almost no companies today that do not promote their products and services through the Internet and websites. Therefore, measuring the quality of a website is significant from the company’s point of view in order to maintain the competitive advantage in the long run; thus, the quality of a website has become an area of great importance. This paper aims to present a new multiple-criteria decision-making approach, together with the “quality in use” ISO/IEC 9126-4 criteria devoted to the evaluation of the quality of websites in the textile industry. The proposed approach is based on the use of the newly-developed Evaluation Based on Distance from Average Solution (EDAS) method for the ranking of alternatives, i.e. in our case websites, whereas for the purpose of determining the weights, the adapted Step-wise Weight Assessment Ratio Analysis (SWARA) method is applied. In order to demonstrate usability, efficiency and simplicity a numerical example of the evaluation of the websites of the textile industry in Serbia is conducted.