Search Results (92)

Supplier selection is one of the critical processes that entail multiple complex deliberations. The selection of an appropriate alternative supplier is a highly intricate process, primarily due to there being multiple criteria which are exceptionally subjective. This paper aims to develop a practical framework for choosing a suitable precast supplier by integrating the Value Engineering (VE) concept, Stepwise Weight Assessment Ratio Analysis (SWARA), and the Weighted Aggregated Sum Product Assessment (WASPAS) technique. This paper introduces a novel method to estimate the quality weights of alternative suppliers’ criteria (CQW) by linking factory capacity with the coefficients of the nine significant criteria, computed using principal component analysis (PCA). None of the formal studies make this link directly. The framework’s findings were validated by comparing its results with an expert assessment of five Saudi supplier alternatives. The results revealed that the framework’s results agree with the expert’s judgment. The method of payment criterion received the highest weight, indicating that it was considered the most important of the nine criteria identified. Combining PCA and VE with the WASPAS technique resulted in an unprecedentedly effective selection tool for precast suppliers. Full article

The development of technology has influenced agricultural production and the establishment of the Agriculture 4.0 system in practice. This research is focused on the selection of equipment and machinery suppliers for the needs of the MAMEX Company. When selecting suppliers, an approach based on the application of an intuitionistic fuzzy set for decision-making was used. This approach allows the uncertainty present in decision-making to be incorporated, considered, and, hopefully, reduced in order to make a final decision on which of the observed suppliers is the most suitable for this company. Ten criteria were used that enable the application of sustainability in the supply chain. Eight local suppliers of equipment and machinery were observed with these criteria. The results obtained by applying the SWARA (Step-wise Weight Assessment Ratio Analysis) method showed that the most important criterion for selecting suppliers is the reliability and quality of equipment and machinery, while the results of the CORASO (COmpromise Ranking from Alternative Solutions) method showed that the SUP2 supplier is the best choice for establishing partnership relations with the MAMEX company. This supplier should help the MAMEX company improve its business and achieve better results in the market. The contribution of this research is to improve the application of intuitionistic fuzzy sets in decision-making, and to emphasize the importance of equipment and machinery in agricultural production in the Agriculture 4.0 system. Full article

Maintenance 4.0 studies have become a focus for managers and employees when developing effective and efficient maintenance policies. In this study, the barriers to Maintenance 4.0 applications in the textile industry are investigated, and these barriers are weighted using the Stepwise Weight Assessment Ratio Analysis (SWARA) method based on Pythagorean fuzzy numbers. Solutions to address these barriers are presented. As a result of this study, Organizational and Managerial emerged as the most important main criterion. Operational was identified as the second most significant main criterion, followed by Technical Competence. Data-Related and Cybersecurity ranked fourth in terms of importance. On the other hand, Human Resources and Training and Financial were found to be the least important main criteria. These two criteria received lower importance scores compared to the others, with Financial being the criterion with the lowest overall significance. Sensitivity analyses were performed for six different scenarios by changing the importance weights of the decision-makers. The ranking of the criteria only slightly changed with the weights; this means that the results obtained in Case 1 are robust and reliable. Even in Case 6, where the expert weight ratios were completely reversed, the results did not change significantly. This highlights an important point regarding the reliability of the assessment. Full article

Macroeconomic indicators are essential measures that reflect the overall economic wellbeing of a region or country and have a significant impact on investment decisions. The data on macroeconomic indicators for Turkish development regions facilitate a comparison of macroeconomic performance between these regions. This kind of analysis can help enhance the development levels of the regions while ensuring resources are used efficiently. This study compares the macroeconomic performance of Turkish development regions between 2019 and 2022 using a hybrid multi-criteria analysis method. A total of 26 regions were evaluated based on seven criteria: GDP, GDP per capita, employment rate, number of enterprises, export, unemployment rate, and import. The criteria were weighted using the Step-Wise Weight Assessment Ratio Analysis (SWARA) method and ranked using the Combined Compromise Solution (CoCoSo) method. This study addresses a gap in the literature by analyzing the macroeconomic performance of Turkish regions, aiming to reduce economic disparities. The results showed that the Istanbul region had the best performance over the 4-year period, while Eastern Anatolia experienced a consistently declining performance, ranking last. Some regions had fluctuating performances, while others maintained steady outcomes. This study advances research by offering a more reliable and comprehensive analysis, thereby contributing to the improvement of future studies on regional economic development. Full article

The optimisation of airport infrastructure capacities lacks adequate tools that would enable airport owners and managers to make strategic decisions related to sustainable development and strengthening multimodal connectivity. Assessing the sustainability of the transport system is one of the important issues in creating transport policies worldwide. In this research, the methodology of multi-criteria decision making (MCDM) was used, which can be applied to decision making and the evaluation of transport projects, considering more than one criterion in the selection process. The Stepwise Weight Assessment Ratio Analysis (SWARA) method is one of the new MCDM methods. The SWARA method will assess the weights of the selected main criteria and sub-criteria for the multimodal connection of airports to the railway transport infrastructure. In this method, the expert plays an important role in the evaluation and calculation of the criteria weights. This research also aims to respond to the need to define a framework for objective and transparent decision-making based on the assessment of the weighting factors of the selected main criteria and sub-criteria. To assess the justification for the choice of railway transport for connecting airports, financial, traffic, environmental, and availability criteria were used. Full article

Assessing the urban green transportation development level (UGTDL) is of great significance for addressing traffic issues in megacities and promoting urban sustainable development. An evaluation framework for the UGTDL is proposed based on Multi-Criteria Decision Analysis (MCDA) methods. Firstly, from both macro and micro perspectives, a comprehensive evaluation indicator system is constructed, covering multiple dimensions such as traffic spatial organization efficiency, green travel, new energy vehicle development, traffic safety, and the traffic environment. Secondly, to address the uncertainties and fuzziness in the evaluation process, the Probability Language Term Set (PLTS) is introduced to represent expert evaluation information, thereby reducing the information loss. Thirdly, the improved Step-wise Weight Assessment Ratio Analysis (SWARA) method is employed to calculate the weights of the indicators, improving the computational efficiency. Finally, the extended Combined Compromise Solution (CoCoSo) method is used to calculate the UGTDL, avoiding the compensatory issues in the traditional decision-making methods. The proposed approach is applied to assess the UGTDL in Guangzhou from 2020 to 2023. The results show that the UGTDL scores for Guangzhou from 2020 to 2023 are 1.6367, 2.2325, 2.1141, and 1.8575, respectively. Sensitivity analysis verifies the effectiveness and stability of the approach. Further obstacle analysis shows that the promotion of new energy vehicles (NEVs) has led to a marginal decrease in the utility of Guangzhou’s UGTDL. In the future, Guangzhou should take further measures to improve the traffic space organization efficiency and traffic safety. Full article

The effective selection of highway projects is essential for driving economic growth and facilitating trade in Saudi Arabia’s cities. However, current studies lack a comprehensive approach that assesses highways based on a full spectrum of economic, environmental, and social cost–benefit factors tailored to Saudi Arabia’s construction industry. This study addresses this gap by developing a framework that incorporates the aspects. The methodology comprises five steps: (1) a literature review to identify benefit and cost criteria; (2) expert surveys to select significant criteria; (3) the application of the stepwise weight assessment ratio analysis (SWARA) method to determine criteria weights; (4) structured expert interviews to establish criteria quality weights; and (5) validation through application to three case studies, comparing the results with those obtained using the ANP method. The findings show that economically efficient road choices yield increased productivity and support industrial growth, while the most significant environmental benefit is reducing carbon emissions. Social benefits, as emphasized by experts, include accident reduction. Cost factors are also considered, with savings on vehicle operation costs identified as the most significant, as opined by the expert surveyed. Among the analyzed highways, Khurais Road, Riyadh, was the most efficient from the SWARA approach, with a value of 0.8, and the ANP case study conducted, with a normalized score of 0.045 and 0.230 for both benefits and cost criteria. Full article

With the development of technology, the need for software and software products to manage, control, and develop activities in many sectors is increasing daily. In order to create suitable software that will meet the needs of businesses and customers, the software application must be tested in detail before reaching the end user. For this reason, software testing processes are gaining importance in software development activities. This article discusses which errors are critical to solve in complex situations for the reliability and quality of the software product and the relationship between errors. In this study, the classical FMEA method was primarily used to identify and prioritize errors in an ongoing project of a company that provides software services in the defense industry. Later, to eliminate the shortcomings of the classical FMEA method, a new model, the weighted FMEA method (which calculates the risk priority score with five sub-severity components), was developed and applied. In the newly developed weighted FMEA method, the weights were determined by the fuzzy SWARA (Step-Wise Weight Assessment Ratio Analysis) method since the weights of the severity subcomponents were not the same. The risk priority number (RPN) of error types was calculated using classical FMEA and weighted FMEA. Since the RPNs calculated with weighted FMEA are calculated with more subcomponents, the chances of the RPNs’ errors appearing the same are much less than the RPNs calculated with classical FMEA. This situation indicates that the RPNs calculated with weighted FMEA are obtained from a more profound analysis. Full article

Smart technologies are increasingly used in agriculture, with drones becoming one of the key tools in agricultural production. This study aims to evaluate affordable drones for agricultural use in the Posavina region, located in northern Bosnia and Herzegovina. To determine which drones deliver the best results for small and medium-sized farms, ten criteria were used to evaluate eight drones. Through expert evaluation, relevant criteria were first established and then used to assess the drones. The selected drones are designed for crop monitoring and are priced under EUR 2000. Using the fuzzy A-SWARA (Adapted Step-wise Weight Assessment Ratio Analysis) method, it was determined that the most important criteria for drone selection are control precision, flight autonomy, and ease of use, all of which are technical attributes. The fuzzy MARCOS method revealed that the best-performing drones are also the most affordable. The drones D5, D4, and D8 demonstrated the best results. These findings were confirmed through comparative analysis and sensitivity analysis. Their features are not significantly different from those of more expensive models and can, therefore, be effectively used for smart agriculture. This study demonstrates that drones can be a valuable tool for small farms, helping to enhance agricultural practices and productivity. Full article

Management of reputational risk is crucial for financial institutions to establish a solid foundation for strategic decisions, gain customer trust, and enhance resilience against environmental adversities, as they largely operate on digital platforms. Since this becomes even more significant as online transactions and digital interactions amplify the visibility and potential impact of reputational issues in the context of electronic commerce, it is essential to thoroughly investigate environmental factors to achieve a comprehensive understanding of reputational risk. However, measuring and evaluating their influence on reputational risk is challenging due to their inherent connection to human perception. This study aims to explore the factors influencing reputational risk of financial organizations to mitigate potential reputational losses by addressing uncertainties associated with concepts such as vagueness. The employed methodology integrates the Decision-Making Trial and Evaluation Laboratory and Fuzzy Cognitive Map techniques using linguistic fuzzy terms. This approach focuses on both the direct effects of factors on reputational risk and the indirect effects arising from interdependencies between factors. Linguistic fuzzy variables enable us to consider the hesitation of the experts and the vagueness of human judgment. To validate the results, factors are also weighted using the fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) method. The most influential factors identified by both methods are market value, revenue, risk culture, shareholder value, firm performance, reputation awareness, and return on equity. Additionally, factors affecting other factors include firm performance, revenue, and growth opportunities. Full article

With the growth of the worldwide population and depletion of natural resources, the sustainable development of food systems cannot be ignored. The demand for agri-food waste valorization practices like high-value compounds production has received widespread attention; however, numerous challenges still exist. The present study aims to identify those challenges of agri-food waste valorization and propose effective solutions based on smart technologies. Based on a systematic review of the literature, the study combs existing challenges of agri-food waste valorization and constructs a six-dimension conceptual model of agri-food waste valorization challenges. Moreover, the study integrates a Fermatean fuzzy set (FFS) with multi-criteria decision-making (MCDM) methods including stepwise weight assessment ratio analysis (SWARA), decision-making trial and evaluation laboratory-interpretative structural modeling method (DEMATEL-ISM), and quality function deployment (QFD) to evaluate the weights of each dimension, find causal interrelationships among the challenges and fundamental ones, and rank the potential smart solutions. Finally, the results indicate that the “Government” dimension is the severest challenge and point out five primary challenges in agri-food waste valorization. The most potential smart solution is the “Facilitating connectivity and information sharing between supply chain members (S8)”, which may help government and related practitioners manage agri-food waste efficiently and also facilitate circular economy. Full article

Building façades represent one of the most critical elements affecting a city’s quality of life, and they impact the country’s economic income by attracting visitors. However, performance data on façades are limited or incomplete, making it challenging for designers to evaluate their effectiveness in energy efficiency, thermal performance, durability, and other key performance metrics. This paper presents a comprehensive framework for evaluating and prioritizing material selection criteria in building cladding, establishing the relationship with available alternatives, and integrating decision-making processes with Building Information Modeling (BIM) to automate the Value Engineering (VE) concept. The material selection criteria from the literature and international standard manual were identified, and their criteria weight was then evaluated using SWARA (stepwise weight assessment ratio analysis). Additionally, WASPAS (weighted aggregated sum product assessment) was utilized to evaluate the alternative cladding materials based on the defined criteria and their associated quality weight (QW). The life cycle cost (LCC) of the alternatives was computed. The VE was computed and then ranked based on the QW and LCC of the alternatives. The procedure was connected to the BIM model to automate the assessment, specifying the necessary parameters and the BIM computation. A case study of an office building façade was conducted to validate the proposed framework. In this study, the significant criteria were durability, wind load resistance, and thermal insulation. This approach enables executives to evaluate cladding selection, ensuring efficient decision-making processes. The proposed method and its results were subjected to expert testing, and the satisfaction rate exceeded 80%, confirming the framework’s reliability in evaluating alternatives. This paper enhances the understanding of material selection methodologies and provides a valuable contribution to the field of construction management. Full article

The expansion of the open-pit exploitation of mineral raw materials, and especially the energy resources of fossil fuels, makes open-pit coal mines spatially dominant objects of large mining basins. Exploitation activities are accompanied by negative ecological impacts on the environment, which requires the integral planning, revitalization, reclamation, and rehabilitation of the disturbed area for human use in the post-exploitation period. The post-exploitation remediation and rehabilitation of open-pit mining areas and disposal sites, i.e., space disturbed by mining activities and accompanying facilities, are complex synthetic multidisciplinary multiphase engineering project tasks. In this paper, a hybrid fuzzy MCDM model (Multiple-Criteria Decision-Making) was developed for the selection of a reclamation solution for the Tamnava-West Field open-pit mine. IMF SWARA (Improved Fuzzy Stepwise Weight Assessment Ratio Analysis) was applied to define the weights of 12 criteria of different structures used in the evaluation of reclamation solutions. The Fuzzy ROV (Range of Value) method was applied to select the reclamation solution from a total of 11 solutions previously obtained using a process approach. The results of the hybrid IMF SWARA—Fuzzy ROV model show that forestry is the best solution for the Tamnava-West Field open-pit mine. After the results had been obtained, verification analyses of the proposed model were performed and the best stable proposed reclamation solution was determined. Full article

This article describes an effective approach for selecting suitable plant species for afforestation in post-mining rehabilitation. The research was conducted in the Western Black Sea region of Turkey. The aim of the research is to perform accurate criteria weighting and species prioritization for afforestation in post-mining degraded areas. This helps to ensure consistent conditions for the future use of the site as a forest, sustainability of nature, and selection of appropriate species adapted to the difficult post-mining conditions. In this study, which is a multi-criteria decision-making problem (MCDM), the weights of the criteria were determined by stepwise weight assessment ratio analysis (SWARA), and the priority ranking of the species was determined by the analytic hierarchy process (AHP). Analyses were carried out with 10 afforestation criteria and five tree species. According to the analysis, the top three ranked criteria are Economic Efficiency > Carbon Stock and Credit > Reducing Afforestation Cost. The five species’ priority ranking is Robinia pseudoacacia L. (0.456) > Alnus glutinosa subsp. glutinosa (0.248) > Populus nigra subsp. nigra (0.146) > Salix alba L. (0.103) > Quercus robur subs. robur (0.048). The hybrid approach is expected to increase the effectiveness of post-mining rehabilitation works. Full article

The capacity of transport infrastructure is one of the very important tasks in transport engineering, which depends mostly on the geometric characteristics of road and headway analysis. In this paper, we have considered 14 road sections and determined their efficiency based on headway analysis. We have developed a novel interval fuzzy-rough-number decision-making model consisting of DEA (data envelopment analysis), IFRN SWARA (interval-valued fuzzy-rough-number stepwise weight-assessment-ratio analysis), and IFRN WASPAS (interval-valued fuzzy-rough-number weighted-aggregate sum–product assessment) methods. The main contribution of this study is a new extension of WASPAS method with interval fuzzy rough numbers. Firstly, the DEA model was applied to determine the efficiency of 14 road sections according to seven input–output parameters. Seven out of the fourteen alternatives showed full efficiency and were implemented further in the model. After that, the IFRN SWARA method was used for the calculation of the final weights, while IFRN WASPAS was applied for ranking seven of the road sections. The results show that two sections are very similar and have almost equal efficiency, while the other results are very stable. According to the results obtained, the best-ranked is a measuring segment of the Ivanjska–Šargovac section, with a road gradient = −5.5%, which has low deviating values of headways according to the measurement classes from PC-PC to AT-PC, which shows balanced and continuous traffic flow. Finally, verification tests such as changing the criteria weights, comparative analysis, changing the λ parameter, and reverse rank analysis have been performed. Full article