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Natural aquifers used for human consumption are among the most important resources in the world. The Locumba basin faces significant challenges due to its limited water availability for the local population. In this way, the search for possible aquifer recharge zones is crucial work for urban development in areas that have water scarcity. To evaluate this problem, this research proposes the use of the hybrid Fuzzy AHP methodology in conjunction with the TOPSIS algorithm to obtain a potential aquifer recharge map. Ten factors that influence productivity and capacity in an aquifer were implemented, which were subjected to Fuzzy AHP to obtain their weighting. Using the TOPSIS algorithm, the delineation of the most favorable areas with high recharge potential was established. The result shows that the most influential factors for recharge are precipitation, permeability, and slopes, which obtained the highest weights of 0.22, 0.19, and 0.17, respectively. In parallel, the TOPSIS result highlights the potential recharge zones distributed in the Locumba basin, which were classified into five categories: very high (13%), high (28%), moderate (15%), low (28%), and very low (16%). The adapted methodology in this research seeks to be the first step toward effective water resource management in the study area.

Climate change threatens human survival and development. Cities, as the main gathering places for human production and life, serve as the focal points for the implementation of the policies related to energy efficiency, energy transition, and environmental protection. This study constructs an index system for the evaluation of carbon-neutral cities from the perspectives of carbon sources and carbon sinks. The system includes thirteen indicators under six dimensions. It combines objective and subjective data (i.e., statistical data and expert evaluations) by integrating two approaches: the fuzzy analytic hierarchy process (fuzzy AHP) and vise kriterijumska optimizacija i kompromisno resenje with hesitant fuzzy sets (HFS-VIKOR). We verify the efficacy of the proposed approach through a case study of thirteen low-carbon pilot cities in China. The results indicate that among these cities, Shenzhen performs the best, followed by Guangzhou and Hangzhou, while Kunming, Baoding, and Tianjin show poor performance in terms of carbon neutrality. Kunming and Baoding exhibit shortcomings mainly in carbon sources, while Tianjin faces deficiencies in both carbon sources and carbon sinks. Sensitivity analysis and comparative analysis show the availability and effectiveness of the proposed method. The proposed radar chart further highlights the improvement directions for each city to achieve carbon neutrality.

This paper investigates the Indoor Environmental Quality (IEQ) factors influencing occupant satisfaction in commercial buildings in Iran, contrasting the views of building experts (architects and engineers) with those of building occupants. Employing the fuzzy analytical hierarchy process (FAHP), this study focuses on the four primary IEQ factors: thermal comfort, indoor air quality, visual comfort, and acoustic comfort. The study aims to bridge the gap between expert evaluations and occupant perceptions of IEQ factors in commercial buildings in Iran. By examining the disparities in prioritising IEQ factors between these two groups, the study sheds light on the complexities of IEQ assessment and highlights the importance of considering diverse perspectives in optimising indoor environments. Our methodology includes a survey conducted among 30 building experts (15 architects and 15 building engineers) and 102 occupants, employing FAHP to derive the relative importance weights of each IEQ factor. The results highlight significant disparities between architects, engineers, and occupants in prioritising these factors. Architects emphasise visual comfort (42%), while engineers and occupants view thermal comfort (53% and 41%) as the most crucial factor for occupant satisfaction. The study underscores the complexity of IEQ in commercial buildings and the diverse perspectives influencing its assessment. It contributes to the broader discourse on optimising IEQ, emphasising the need for a comprehensive approach that encompasses both technical expertise and occupant experience.

Beekeeping management is greatly influenced by spatial factors (e.g., land use/land cover, roads, or electrical energy networks), so GIS are a powerful tool to overlap and relate a variety of spatial data levels and, consequently, a very useful tool for beekeeping activity planning. This study was developed within the intervention area of three controlled zones managed by Portuguese Beekeepers Associations. The methodology, based on multi-criteria decision analysis, integrates several criteria, such as hydrographic networks, road networks, soil occupation, solar radiation, and electromagnetic radiation sources. These criteria were proposed and evaluated through online questionnaires carried out with beekeepers. Concerning the selected criteria and the respective geographical data, the most relevant were land use/land cover and water availability, with a significance of 44% and 24%, respectively. The beekeeping suitability map enabled us to evaluate the degree of compliance for the actual location of apiaries, with 60% of the apiaries being installed in high potential areas. In the context of beekeeping planning, the potential of the techniques applied seems to be an important tool for optimizing the location of apiaries and the profitability of beekeeping.

In today’s digital age, businesses are tasked with adapting to rapidly advancing technology. This transformation is far from simple, with many companies facing difficulties navigating new technological trends. This paper highlights a key segment of a comprehensive strategic model developed to address this challenge. The model integrates various planning and decision-making tools, such as the Balanced Scorecard (BSC), Objectives and Key Results (OKR), SWOT analysis, TOWS, and the Spherical Fuzzy Analytic Hierarchy Process (SFAHP). Integrating these tools in the proposed model provides businesses with a well-rounded pathway to manage digital transformation. The model considers human elements, uncertainty management, needs prioritization, and flexibility, aiming to find the optimal balance between theory and practical applications in real-world business scenarios. This particular study delves into the use of SFAHP, specifically addressing the challenge of effectively selecting the most suitable strategy among various options. This approach not only brings a new perspective to digital transformation but also highlights the importance of choosing the right strategy. This choice is crucial for the overall adaptation of businesses. It shows how carefully applying the SFAHP method is key. Combining this with a successful digital transformation strategy is essential. Together, they provide practical and efficient solutions for businesses in a fast-changing technological environment.

Most of Korea’s precipitation is concentrated between June and September, and 65% of the country’s territory is covered with mountains, which means there is less time for rainfall to reach the surface. These hydrological characteristics pose challenges in securing and managing water resources. Moreover, the Yeongdong Area of Gangwon Province does not easily allow the construction of reservoirs and dams, which adds to the difficulty of developing structural measures to address water shortage caused by water supply restrictions. One measure proposed for addressing damage to residents, as well as social conflicts caused by water shortages, is to use underground dams and other high-capacity underground facilities to secure water for Korea’s eastern coastal areas. Unlike dams and reservoirs above the ground, underground dams are not affected by floods and offer an eco-friendly way to address the continuous water demand growth by storing water in underground spaces. This study prioritizes underground dam sites in six areas in the Yeongdong Area of Gangwon Province (Goseong, Sokcho, Yangyang, Gangneung, Donghae, and Samcheok) by conducting an expert survey and analyzing the results with the analytic hierarchy process (AHP) and fuzzy AHP. The findings indicate that the Sangcheon River in Sokcho, where an underground dam already exists, satisfies the criteria proposed in this study. We expect the study’s findings and methods to be used to determine suitable dam sites and water resource management plans.

The airline sector is critical in today’s globalized society, supporting the efficient movement of people and products worldwide. Airlines continuously seek methods to enhance their operational performance to remain competitive in the face of increased competition. This study focuses on the application of multi-criteria decision making (MCDM) techniques to improve the ground operational performance of low-cost carriers (LCCs), also known as low-cost (budget) airlines. In recent years, MCDM techniques have gained considerable attention in addressing complex decision problems with complex goals. This research aims to bridge this gap by proposing a comprehensive framework combining MCDM techniques to enhance airline operational strategies and increase performance. The study utilizes qualitative and quantitative data, drawing on previously published materials on MCDM techniques in the aviation sector. It utilizes a fuzzy Analytic Hierarchy Process (AHP) and a fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies. A case study is conducted to evaluate the ground operational performance of three airline companies based in Türkiye, considering five main criteria and eighteen sub-criteria. The findings of this research will contribute to a comprehensive understanding of operational performance in the airline sector. The study’s findings show that five primary criteria’s estimated weights are examined; it is seen that “Flight Schedule and Routes (FSR)” has the highest importance weight of 0.30. With a weight value of 0.26, “Counter Services (CS)” has the second most significant impact. “Ticketing (T)”, which ranks third in terms of its impact on the solution, has a weight value of 0.19. Upon reviewing the analysis’s findings, it can be seen that the third alternative is relatively prominent among the others. Airline_3 ranked first with a weight value of 0.361, while Airline_2 ranked second with a weight value of 0.331. Airline_1 ranked last with an actual weight of 0.308. The study provides highlights of the implications and limitations of the research and suggests future research directions.

Many practical issues arise when dealing with solid waste management, and there are also environmental effects to be considered. Selecting landfill sites requires extra care with respect to many factors such as the environment, health hazards for people, and the cost of transportation. Furthermore, cities have their own rules, methods, and practices for managing and selecting the best locations for collecting solid waste. In this research, multi-criteria decision analysis (MCDA) was presented and used to evaluate the appropriateness of and suggest the best locations for landfill sites in Najran, KSA. Some remote sensing data and the ArcGIS software were used to prepare nine thematic layers, including drainage density, groundwater depth, land use, soil type, road network, surface elevation, surface slope, distance from residential areas, and distance from protected areas. To evaluate the layer weightings, a questionnaire with pairwise comparisons was distributed among experts and analyzed using the analytical hierarchy process (AHP) and fuzzy set technique. The one-factor-at-a-time (OFAT) sensitivity test was conducted to test the sensitivity of the evaluated weightings. A landfill suitability index (LSI) map was created using raster calculator tools and divided into five classes: limited suitability (LSI value 1.39–2.49), least suitable (2.50–3.03), relatively suitable (3.04–3.48), suitable (3.49–3.91), and most suitable (3.92–4.66). According to the statistical analysis, 18.0% and 18.2% of the total area were within the most suitable and suitable landfill regions, while 21.2%, 14.9%, and 9.5% accounted for relatively suitable, least suitable, and limited suitability areas, respectively. The employed technique and its findings can provide an appropriate guideline to assist the municipality of Najran city, regional planners, and decision-makers in selecting an optimal landfill site in the future. This study also presented some recommendations to enhance the suitability map of landfill sites in Najran city.

Recently, the demand for citizen-sensible service solutions such as traffic, crime prevention, and disasters in smart cities is increasing. In order to provide technology-based smart city services, local government control centers could be utilized. Accordingly, this paper presented a method for selecting a control center-based dynamic object information utilization service model through in-depth interviews with 26 related local government control center operation personnel. A comparative analysis according to the size of the local government to which the evaluator belongs was also performed. As a methodology, Fuzzy AHP was used, which can support rational decision-making by mathematically expressing ambiguous phenomena such as subjective and uncertain judgments. The summary of the research results is as follows. Services related to recent incidents in South Korea (e.g., school zone traffic accidents and lowland inundation) were identified as very important. These social issues are significant factors in policy decisions. In comparing the results for each urban scale, the importance of pedestrian safety services on backside roads and main road traffic services was found to be important in the metropolitan area and regional, medium, and small cities, respectively. This was attributed to metropolitan cities with high population density, and medium and small cities experiencing alienated traffic information. In metropolitan areas, new services are highly important owing to the demand for a more scientific control service and future mobility based on a sound control infrastructure. In medium and small cities, facility management services were assessed relatively highly owing to the poor conditions of regional cities with a lack of supervising personnel in the field and a lack of surveillance system infrastructure. This paper was able to confirm the difference in service preference by city size, and it is necessary to select the optimal service model considering these results.

Given the prevailing arid climate and rapid population growth, groundwater resources face unprecedented challenges globally, including depletion, seawater intrusion, and contamination. Managed aquifer recharge (MAR) technologies have emerged as valuable solutions to address these pressing issues. However, identifying suitable regions for MAR activities is a complex task, particularly at the country level. Therefore, in this study, we propose a robust approach that combines the fuzzy analytical hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) to delineate suitable sites for MAR structures. The proposed model was applied to Djibouti, a hot, dry, and water-stressed country. We identified a set of nine decision criteria and conducted a pairwise comparison survey to determine their relative importance. Additionally, the TOPSIS method was employed to integrate the decision layers and prioritize the study area. The results highlight the significance of rainfall, the slope, and the NDVI as the most influential decision parameters, while the drainage density has the least impact. A suitability analysis reveals that 16.38%, 17.96%, and 30.41% of the country have a very high, high, and moderate potential for MAR activities, respectively. Furthermore, a sensitivity analysis demonstrates the stability of the proposed model, affirming the usefulness of the generated suitability map.

Renewable energy is one of the main components of a sustainable world and its future. The consumption of electricity from renewable sources in Croatia has an impressive rate of 53.5%, but offshore wind turbines (OWT) have not yet been installed in the Adriatic Sea. The aim of this study is to determine the possibilities for offshore wind farm (OWF) positioning in the Croatian part of the Adriatic Sea using marine spatial planning (MSP). Initial research to determine the points of interest was conducted based on wind speed. The authors established ten possible points for further research. Subsequently, different parameters were used as inputs for exclusion. The Fuzzy Analytic Hierarchy Process (AHP) method was used to calculate the weighting coefficients for a suitable set of criteria, exactly six of them. Using a combination of geoinformation system (GIS) analysis and weighting coefficients established through Fuzzy AHP, four points were established as suitable for OWF installation in Croatia. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was used to select the best order for OWF positioning in the eastern part of the Adriatic Sea. To conclude, there are not many options for OWF positioning in Croatia. Furthermore, it is clear that they exist and should be explored further.

The COVID-19 pandemic has affected public transportation worldwide, and its implications need to be evaluated and study deeply on all public transportation aspects. Therefore, an analysis has been created to examine the effects of the pandemic on public transportation service quality decisions to have a better vision of the different stakeholders’ needs to keep the system functioning in a profitable way. Stakeholder participation in complex, multi-criteria decision-making often produces very different results in prioritizing the decision attributes. Rank correlation techniques generally measure the degree of agreement or non-agreement among the evaluator groups. However, the multi-criteria methodology can determine not only ordinal but also cardinal priorities. Consequently, except for the attributes’ positions, the weight values are also significant in the final decision. This paper aims to apply a more sophisticated measure of group agreement than rank correlation. First, the Fuzzy-hierarchical analytical process (FAHP) has been used to find out the aggregated weights, then the Kendall correlation values are computed to reveal stakeholder opinions. Finally, the agreement measure approach has been tested in a real-world case study: the public transport development decision of Amman, Jordan. The analysis shows that by applying the Kendall technique, Kendall could gain a more profound insight into the priority characteristics of different evaluator groups.

Evaluating and ranking schools are noteworthy for parents of students and upstream institutions (in Iran, the Ministry of Education). In this process, quantitative criteria, including educational activities, human resources, space and equipment, and administrative-financial indicators, are commonly investigated. This process is carried out only by the upstream institutions and the view of the system from the perspective of another stakeholder, namely, the students’ parents, are ignored and qualitative-judgmental indicators do not involve the school evaluation results. Consequently, in this study, we used the opinions of five parents of students and five experienced school administrators to capture the perspectives of both key system stakeholders. In addition, to perform a more comprehensive analysis, we added three qualitative criteria that are less noticed within the problem (social environment, health, and students), along with their sub-criteria to the criteria obtained from the research background. We eliminated the less influential sub-criteria using the Delphi technique and continued the study with 10 criteria and 53 sub-criteria. Then, using two widely used methods in this field, AHP and TOPSIS, we determined the weight of the sub-criteria and the ranking based on the experts’ views. In addition, to deal with the ambiguity in experts’ judgments, we transformed the crisp data into fuzzy data. We applied the proposed methodology to rank 15 schools in Tehran, Iran. The results showed that the proposed quantitative criteria significantly impact the schools ranking. In addition, according to the sensitivity analysis results, it was found that ignoring the views of the system from another stakeholder can distort the results. Finally, directions for future research were suggested based on current research limitations.

Quick population increase and the desire for urbanization are the main drivers for accelerating urban expansion on agricultural lands in Egypt. This issue is obvious in governorates with no desert backyards. This study aims to (1) explore the trend of Land Use Land Cover Change (LULCC) through the period of 1991–2018; (2) upgrade the reliability of predicting LULCC by integrating the Cellular Automata (CA)-Markov chain and fuzzy analytical hierarchy process (FAHP); and (3) perform analysis of urbanization risk on LST trends over the Gharbia governorate for the decision makers to implement effective strategies for sustainable land use. Multi-temporal Landsat images were used to monitor LULCC dynamics from 1991 to 2018 and then simulate LULCC in 2033 and 2048. Two comparable models were adopted for the simulation of spatiotemporal dynamics of land use in the study area: CA-Markov chain and FAHP-CA-Markov chain hybrid models. The second model upgrades the potential of the CA-Markov chain for prediction by its integration with FAHP, which can determine the locations of high potential to be urbanized. The outcomes stated a significant LULCC in Gharbia during the study period—specifically, urban sprawl on agricultural land, and this trend is predicted to carry on. The agricultural sector represented 91.2% in 1991 and reduced to 83.7% in 2018. The built-up area is almost doubled by 2048 with respect to 2018. The regression analysis revealed the LST increase due to urbanization, causing an urban heat island phenomenon. Criteria-based analysis reveals the district’s vulnerability to rapid urbanization, which is efficient for data-gap zones. The simulation results make sense since the FAHP-CA-Markov simulated the LULCC in a thoughtful way, considering the driving forces of LULCC, while the CA-Markov chain results were relatively random. Therefore, the FAHP-CA-Markov chain is the pioneer to be relied upon for future projection. The findings of this work provide a better understanding of LULCC trends over the years supporting decision makers toward sustainable land use. Thus, further urbanization should be planned to avert the loss of agricultural land and uninterrupted increasing temperatures.

For decades, Fuzzy Sets Theory (FST) has been consistently developed, and its use has spread across multiple disciplines. In this process of knowledge transfer, fuzzy applications have experienced great diffusion. Among them, Fuzzy Analytic Hierarchy Process (fuzzy AHP) is one of the most widely used methodologies today. This study performs a systematic review following the PRISMA statement and addresses a bibliometric analysis of all articles published on fuzzy AHP in journals indexed in Web of Science, specifically in Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI). The analyzed database includes 2086 articles published between 1994 and 2022. The results show the thematic clusters, the evolution of the academic conversation and the main collaboration networks. The main contribution of this article is to clarify the research agenda on fuzzy AHP. The results of the study allow academics to detect publication opportunities. In addition, the evidence found allows researchers and academics setting the field’s agenda to advise the editors of high-impact journals on gaps and new research trends.

This study aims to discuss a risk assessment of navigation safety for ferries. In this research, the risk factors (RFs) for the navigation safety of ferries are first investigated from relevant literature and ferry operational features. A fuzzy AHP (Analytic Hierarchical Process) approach is then proposed to weight those RFs, after which a continuous risk-matrix model is then developed to determine the RFs’ risk levels. Finally, to validate the practical application of the proposed model, ferries traveling across the Taiwan Strait were empirically investigated. The results may provide practical information for ferry operators to improve their safety performances. Further, the proposed risk assessment approach may provide references for related research in the safety management of short-distance passenger ships.

The ongoing COVID-19 pandemic has caused a paradigm shift in all aspects of contemporary human life. Everyday activities such as shopping have shifted from traditional methods to the ever-more growing online variants, allowing for an increase in electronic commerce (e-commerce) industry. As more services become available online, consumers often rely on trusted services, which are often reflected on the web and mobile platforms they are presented on. In this paper, we study the factors for successful e-commerce platform design in the Western Balkans region using Fuzzy Analytical Hierarchy Process (FAHP) with triangular fuzzy numbers. After an extensive literature overview, interviews with representatives of top-ranking e-commerce companies in the region, and the analysis of experts’ opinions, we select a number of factors and sub-factors for prioritization, taking into account pre-pandemic factors, as well as the ones of the pandemic itself. We extend the FAHP model, which now consists of five (instead of three) points of view. Finally, we present and discuss the results in the form of tables and graphs, as well as an overall recommendation of what should be taken into account when designing an e-commerce platform. Our results rank service quality and security factors first and criteria such as multilingual support last.

The primary goal of this research study, in the field of information technology (IT), is to improve the security and durability of software. A quantum computing-based security algorithm springs quite a lot of symmetrical approaches and procedures to ensure optimum software retreat. The accurate assessment of software’s durability and security is a dynamic aspect in assessing, administrating, and controlling security for strengthening the features of security. This paper essentially emphasises the demarcation and depiction of quantum computing from a software security perspective. At present, different symmetrical-based cryptography approaches or algorithms are being used to protect different government and non-government sectors, such as banks, healthcare sectors, defense, transport, automobiles, navigators, weather forecasting, etc., to ensure software durability and security. However, many crypto schemes are likely to collapse when a large qubit-based quantum computer is developed. In such a scenario, it is necessary to pay attention to the security alternatives based on quantum computing. Presently, the different factors of software durability are usability, dependability, trustworthiness, and human trust. In this study, we have also classified the durability level in the second stage. The intention of the evaluation of the impact on security over quantum duration is to estimate and assess the security durability of software. In this research investigation, we have followed the symmetrical hybrid technique of fuzzy analytic hierarchy process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS). The obtained results, and the method used in this estimation, would make a significant contribution to future research for organising software security and durability (SSD) in the presence of a quantum computer.

Public transportation has been encouraged as a significant solution to overcome traffic congestion. An advanced technology, known as advanced public transport system (APTS), was introduced to enhance the effectiveness of public transportation. To support appropriate decisions on selecting application development, significant indicators representing the impacts of the proposed projects are highlighted. This study aims to determine the desirable indicators of developing APTS to achieve smart mobility using the fuzzy Analytical Hierarchy Process (fuzzy AHP) method and allocating weights to each indicator. The perception of a group of intelligent transport system (ITS) experts from three sectors in the Bangkok Metropolitan Regions (BMR) was examined to conduct a fuzzy AHP pairwise comparison. The ranking of 21 indicators categorized within six dimensions in accordance with the specific ITS master plan relating to APTS development is presented. The result presented that the safety dimension obtained the highest rank, and the three most important weight indicators are traffic accident reduction relating to public transportation, smart public transport network density and waiting time for public transportation. In addition, the perspectives towards APTS development and assessment framework development in BMR is highlighted to revise impediment of regulation and encourage integration among stakeholders. Then, the approaches of the APTS evaluation framework in BMR are proposed.

This research aims to help develop aviation safety policies for the general aviation industry, especially for flight training schools. The analytical hierarchy process (AHP), fuzzy AHP, and fuzzy integral methods were used to find variables that impact aviation safety for training pilots in Korea and the United States using survey participants’ experience and perceptions. The results represent the circumstances of aviation safety in the real world where single pilot resource management, especially situational awareness, is crucial. The authors find that integral fuzzy AHP provides more explicit considerations, making up for the ambiguity of the linguistic responses caused by the AHP and fuzzy AHP.

Increasingly, cities worldwide are striving for green travel and slow traffic, and vigorously developing people-oriented urban pedestrian traffic with sustainability has become a fixture in recent discourse. This paper comprehensively considers the sidewalk’s facilities environment and the status of pedestrian traffic flow; divides the urban pedestrian road system (UPRS) into five subsystems around the underpass, overpass, crosswalk, sidewalk, and road crosswalk; and introduces the basic structure as well as the function of each system. Then, the indicators are classified into two types of crosswalk facilities and sidewalk facilities, and a comprehensive pedestrian road indicator system with the combination of subjective and objective is established. Consequently, the integration of the fuzzy AHP and DEA-based symmetrical technique for the subjective evaluation indicator combined with pedestrian traffic characteristics is developed. A nine-step semantics scale of relative importance was used so that the symmetry of the response of pedestrian satisfaction was maintained. Fuzzy evaluation based on AHP is further modeled, and the DEA is employed to achieve an overall evaluation of the quality of service (QoS) for UPRS. The applicability of the established evaluation system is finally verified through a real case study in Harbin, China. The serviceability assessment method in this paper provides a new idea for planners to conduct sustainability evaluation for UPRS in future urban renewal development.

In concept design, effective decision making and management of schemes can shorten the design cycle and improve product quality. The decision maker (DM)’s confidence is one of the critical factors affecting the conceptual design evaluation. Although many studies use quantitative linguistic evaluation for design scheme decision-making, which improves product conceptual design decision-making efficiency and effectiveness, few studies consider the confidence level of a decision. A conceptual design evaluation method based on Z-numbers is proposed to solve this problem, considering the customer requirements and the DM’s confidence. Firstly, the evaluation criteria are determined by analyzing customer requirements; then, the fuzzy analytic hierarchy process in the Z-numbers environment (Z-AHP) is used to determine the criteria weight; Finally, the fuzzy technique for order preference by similarity to ideal solution method in the Z-numbers environment (Z-TOPSIS) is used to evaluate the design schemes to obtain the optimal scheme. The proposed method is applied to the selection of the design scheme of the waste containers in the kitchen. The results show that considering the DM’s self-confidence can achieve a more reasonable and practical evaluation of the conceptual design scheme, and it is easier to obtain the best scheme.

Selecting a better performing contractor at the procurement stage is crucial in achieving a successful outcome for a construction project. The construction industry lacks a systematic and purpose driven method to assess performance of contractors using objective metrics. There are many approaches to measuring construction performance, but most are complicated and have high dependency on data that is difficult to attain. This paper aims to create a model for evaluating construction contractors’ performance based on directly attributable measures that are quantitative and easy to gather. This makes such a model more attractive and easier to use. Initially, a detailed literature review revealed different categories of measures of performance (MoP) and corresponding critical measures of performance (CMoP). Through a series of Delphi-based expert forums, the set of measures were fine-tuned and shortlisted. Fuzzy analytic hierarchy process-based comparisons were then used for developing a contractors’ performance model to quantify their level of performance based on a limited set of organisation-specific and project-specific measures. The results indicate a shift from traditional measures and a higher preference towards non-price measures. The performance model can be further developed to systematically rank the prospective contractors at the procurement stage based on seven non-price measures.

Beekeeping management is greatly influenced by spatial factors (e.g., land use/land cover, roads, or electrical energy networks), so GIS are a powerful tool to overlap and relate a variety of spatial data levels and, consequently, a very useful tool for beekeeping activity planning. This study was developed within the intervention area of three controlled zones managed by Portuguese Beekeepers Associations. The methodology, based on multi-criteria decision analysis, integrates several criteria, such as hydrographic networks, road networks, soil occupation, solar radiation, and electromagnetic radiation sources. These criteria were proposed and evaluated through online questionnaires carried out with beekeepers. Concerning the selected criteria and the respective geographical data, the most relevant were land use/land cover and water availability, with a significance of 44% and 24%, respectively. The beekeeping suitability map enabled us to evaluate the degree of compliance for the actual location of apiaries, with 60% of the apiaries being installed in high potential areas. In the context of beekeeping planning, the potential of the techniques applied seems to be an important tool for optimizing the location of apiaries and the profitability of beekeeping.

Rational decision-making requires assessing the advantages and disadvantages of options, including nonmarket effects (such as environmental effects). This also applies to strategic decision-making in the industrial sector to select alternative renewable energy source (RES). Often, a variety of criteria can be used to select a renewable energy source, whereas no ideal family of criteria for renewable energy selection for industry has been defined in the literature. It was concluded that there is a need to support the actions of industrial development based on RES, which will contribute significantly to overcoming the limitations of the negative effect on the environment in terms of greenhouse gas emissions. There is a clear need for a systematic and polyvalent multicriteria approach to planning in industry. Therefore, a method for choosing the preferred renewable source of electricity for industry has been developed, which considers key criteria of RES choice: Expert opinions, the costs of obtaining the energy and maintaining energy installations, and the volume of electricity from RES. This article offers a modified multicriteria selection method based on a fuzzy analytic hierarchy process (fuzzy AHP) and the technique for preference by similarity to an ideal solution (TOPSIS), integrated with a qualitative price analysis (ACJ). This new method was tested through a case study on selecting a preferred RES in Polish industrial conditions. The research results indicate that the proposed method of choosing the preferred renewable energy source can be used in industrial enterprises that strive to meet their energy needs in accordance with the principles of social responsibility.

Integrated devices incorporating MEMS (microelectromechanical systems) with IC (integrated circuit) components have been becoming increasingly important in the era of IoT (Internet of Things). In this study, a hybrid fuzzy MCDM (multi-criteria decision making) model was proposed to effectively evaluate alternative technologies that incorporate MEMS with IC components. This model, composed of the fuzzy AHP (analytic hierarchy process) and fuzzy VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) methods, solves the decision problem of how best to rank MEMS and IC integration technologies in a fuzzy environment. The six important criteria and the major five alternative technologies associated with our research themes were explored through literature review and expert investigations. The priority weights of criteria were derived using fuzzy AHP. After that, fuzzy VIKOR was deployed to rank alternatives. The empirical results show that development schedule and manufacturing capability are the two most important criteria and 3D (three-dimensional) SiP (system-in-package) and monolithic SoC (system-on-chip) are the top two favored technologies. The proposed fuzzy decision model could serve as a reference for the future strategic evaluation and selection of MEMS and IC integration technologies.

This paper presents an empirical study on the impact of maintenance function on more sustainable manufacturing processes. The work methodology comprises four stages. At first, ten factors of maintenance activities from a sustainable manufacturing point of view were identified. Then, in the second stage, the matrix of crossed impact multiplications applied to a classification (MICMAC) was carried out to categorize these factors based on their influence and dependence values. In the third stage, the criteria for evaluation of maintenance factors were defined, then the fuzzy analytic hierarchy process (F-AHP) was applied to determine their relative weights. In the last stage, the results of MICMAC and F-AHP analyses were used as inputs for the fuzzy technique for order preference by similarity to ideal solution (F-TOPIS) to generate aggregate scores and selection of the most important maintenance factors that have an impact on sustainable manufacturing processes. A numerical example is provided to demonstrate the applicability of the approach. It was observed that factors “Implementation of preventive and prognostic service strategies”, “The usage of M&O data collection and processing systems”, and “Modernization of machines and devices” are the major factors that support the realization of sustainable manufacturing process challenges.

This survey is focussed on distance learning studies, where there can be met a lot of technical obstacles, which creates complications in decision making. To get an ideal solution for these kinds of problems, the Fuzzy TOPSIS (Technique for Order Preference by Similarities to Ideal Solution) is one of the best solutions. Therefore, this paper presents the distance learning quality assessment surveys when the Fuzzy AHP (Analytic Hierarchy Process) and TOPSIS methods are used. Research results describe the application of the Fuzzy AHP—TOPSIS hybrid method. MCDM (Multi-Criteria Decision Making) programs with MATLAB (R2020b) mathematical package were written to calculate the evaluation results for three distance learning courses. In the practical implementation of the proposed distance learning module evaluation methodology, the experts’ evaluation method was applied. Thirty-four judges were chosen with specific knowledge and skills and with very different competencies to assess three alternatives by fourteen criteria. Following the experts’ evaluation, a statistical analysis method was used to process the data. After applying the complex evaluation, the comparative analysis method was used to summarize the obtained results. This work further provides useful guidelines for the development of an easily understandable hierarchy of criteria model that reflects the main goal of study quality assessment.

Fuzzy analytic hierarchy process (FAHP) methodologies have witnessed a growing development from the late 1980s until now, and countless FAHP based applications have been published in many fields including economics, finance, environment or engineering. In this context, the FAHP methodologies have been generally restricted to fuzzy numbers with linear type of membership functions (triangular numbers—TN—and trapezoidal numbers—TrN). This paper proposes an extended FAHP model (E-FAHP) where pairwise fuzzy comparison matrices are represented by a special type of fuzzy numbers referred to as (m,n)-trapezoidal numbers (TrN (m,n)) with nonlinear membership functions. It is then demonstrated that there are a significant number of FAHP approaches that can be reduced to the proposed E-FAHP structure. A comparative analysis of E-FAHP and Mikhailov’s model is illustrated with a case study showing that E-FAHP includes linear and nonlinear fuzzy numbers.

Flood hazards affect the local economy and the livelihood of residents along the South-Central Coast of Vietnam. Understanding the factors influencing floods’ occurrence potentially contributes to establish mitigation responses to the hazards. This paper deals with an empirical study on applying a combination of the fuzzy analytic hierarchy process (AHP), the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS), and a geographic information system (GIS) to assess flood hazards along the South-Central Coast of Vietnam. Data are collected from focus group discussions (FGDs) with five communal authorities; a questionnaire completed by eight hamlet heads in the Phuoc Thang commune (Binh Dinh province); and documents, reports, and thematic maps provided from official sources. A total of 12 maps of flood factors are prepared. The results show that terrain elevation, creek-bottom terrains, high tide-induced flooding area, and distance to water body are the main factors affecting flood hazards. The An Loi hamlet faces the highest risk for floods, followed by Lac Dien, Luong Binh, and Pho Dong. The map of flood hazards indicates the western part is assessed as low hazard, whereas the eastern part is a very high hazard area. The study findings show that the hybrid approach using GIS-based fuzzy AHP–TOPSIS allows connecting decision makers with the influencing factors of flooding. To mitigate floods, both the Vietnam national government and the Binh Dinh provincial government should integrate natural hazard mitigation into socio-economic development policies.

In order to select suitable rainwater harvesting sites within the study area, rainwater harvesting criteria needed to be determined, defined, and structured. Several criteria played an important role in selecting the most suitable rainwater harvesting sites. A multicriteria analysis (MCA) approach, which is widely used to classify potential rainwater harvesting sites, was chosen to help select potential sites in the Wadi Horan region of Iraq. An MCA approach offered a systematic methodology focused on mathematics as well as professional expertise to organize and evaluate complex decisions. Unfortunately, there is no method for choosing among them the most appropriate for a given decision problem, as the choice remains a subjective task. This study used a geographic information system (GIS)-based approach with remote sensing to identify the optimal sites for rainwater harvesting. Four indices: evaporation, cost–benefit, sediment, and hydrology were selected in order to compare the potential sites. The analytic hierarchy process (AHP), fuzzy AHP, and rank order method (ROM) were used to assign weight to the study criteria. The results were then compared using a statistical (variance inverse (VI)) method. A sensitivity analysis was done to test the uncertainties and robustness of the results for each method. The results showed that the ROM and VI methods affected the ranking priority and considered all of the criteria that were sensitive to impact in the ranking process at the different levels compared to the methods of AHP and fuzzy AHP.

In the consumerist world, there is an ever-increasing demand for consumption in urban life. Thus, the demand for shopping malls is growing. For a developer, site selection is an important issue as the optimal selection involves several complex factors and sub-factors for a successful investment venture. Thus, these tangible and intangible factors can be best solved by the Multi Criteria Decision Making (MCDM) models. In this study, optimal site selection has been done out of multiple alternative locations in and around the city of Kolkata, West Bengal, India. The Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) has been applied for shopping mall site selection. The AHP is used to obtain the crispified weight of factors. Imprecise linguistic terms used by the decision-maker are converted to Triangular Fuzzy Numbers (TFNs). This research used integrated sub-factors fuzzy weights using FAHP to FTOPSIS for ranking of the alternatives. Hardly any research is done with the use of sub-factors. In this study, seven factors and seventeen sub-factors are considered, the authors collected data from different locations with the help of municipal authorities and architects. This work further provides useful guidelines for shopping mall selection in different states and countries.

This paper aims to identify, evaluate, and measure the ergonomic factors hampering the production of leather garment-based small and medium-sized enterprises (SMEs). Ergonomic problems faced by the workers largely impact the health of individuals and also the productivity of a firm. Based on experts’ opinions and a literature survey, three emerging categories—namely, occupational disease, personal factors, and the industrial environment—with a total of twenty factors were identified to examine symmetrical impact in five leather garment companies. In this research work, Cronbach’s α was evaluated to check the validity of the ergonomic factors identified through the literature survey. Then, using the fuzzy analytic hierarchy process (FAHP), the identified ergonomic factors were evaluated. A sensitivity analysis was carried out to validate the robustness of the results obtained using the integrated approach. Outdated machinery, vibration, operational setup, fatigue, and poor ventilation and lighting are the top five factors inducing ergonomic-related problems and hampering the production of the leather garment companies in India. These top ergonomic factors are the result of a failure in the provision of an ambient working environment. Providing ergonomically designed working environments may lower the occurrence of ergonomic problems. The findings of this study will assist industrial managers to enhance production rate and to progress towards social sustainability in Indian SMEs. The proposed symmetrical assessment in this study could also be considered as a benchmark for other companies in which human–machine interaction is significant.

In the current literature, there are a clear lack of systems to assist in making decisions about the renewal of technology for healthcare equipment, which means that the limited capacity to invest in new equipment cannot usually be appropriately applied as determined by the care requirements of a community. This may have important repercussions for patients, such as the inability to offer treatment or diagnosis, having to delay treatment or diagnosis, increase the risk of patients and care staff of using obsolete equipment, and preventing early, accurate, and reliable diagnosis, all of which have effects on the quality of care to a community. This study therefore describes the first multicriteria model in a fuzzy environment to assist in decision making related to the renewal of healthcare equipment. The fuzzy analytic hierarchy process (FAHP), which allows for ambiguities, uncertainties, and doubts inherent in real-world decision processes to be taken into account, was used to do this. The model produces a plan with actions to be taken depending on the obtained results. The model includes a novel methodology that consists of modifying the top–down technique to allow for the levels of priority for renewing healthcare equipment to be determined from judgements given by three experts. The model was validated by applying it to a set of medical devices, and we show the results for a surgical C-arm, an X-ray CT room, a neonatal ventilator, a defibrillator, and a video-colonoscope. A program was also created using the NI Labview software to process the model so that it could be applied with a user interface that acts quickly, simply, and intuitively.

Gamification is an innovative teaching technique that may prove hugely beneficial when properly used. For this reason, since 2002, the number of situations in which gamification is used has increased exponentially. This large number of options makes it difficult to choose the best application, especially in circumstances where there is the usual uncertainty that real-life decision making involves. To address this problem, this study creates two models, one using a fuzzy analytic hierarchy process (AHP), and the other, which combines fuzzy AHP with the measuring attractiveness by a categorical-based evaluation technique (MACBETH) approach, to choose the best gamification application for the ‘Operations Management’ course, within the Masters in Industrial Engineering. This is the first contribution in the literature combining fuzzy AHP and MACBETH. The decision centre used was the lecturer who teaches the course. There is no precedent in the literature using fuzzy logic to choose the best gamification application for a course. The results of the study show that Socrative is the best gamification application for this course within the Masters, and, as the models begin to be used in degree courses, the better choice would be Quizizz, the more clearly the earlier the course is taught within the degree programme.

The recent hype in online purchasing has skyrocketed the importance of the electronic commerce (e-commerce) industry. One of the core segments of this industry is business-to-consumer (B2C) where businesses use their websites to sell products and services directly to consumers. Thus, it must be taken care of that B2C websites are designed in a way which can build a trustworthy and long-term relationship between businesses and consumers. Thus, this study assesses and prioritizes factors for designing a successful B2C e-commerce website. The study employs multi-criteria decision making (MCDM), and to minimize any ambiguity and greyness in the decision-making, it integrates fuzzy and grey respectively with the Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to form FAHP and TOPSIS-Grey. Initially, the study conducts a thorough literature survey to screen important factors reported in past studies. Five main factors and nineteen sub-factors were selected for further prioritization. Later, FAHP prioritized factors based on their importance. Finally, based on the FAHP results, TOPSIS-Grey ranked five alternatives (e-commerce websites). FAHP revealed “service quality” as the most successful website designing factor, while TOPSIS-Grey reported “Website-3” as the most successful website, having incorporated the factors required to design a successful website.

Limited groundwater resources in arid regions have been found polluted for drinking purpose due to the presence of natural minerals and radioactive substances, in the sub-soils, higher than the drinking water quality standards. Municipalities in these regions are spending extensive resources to transport (from well fields) and treat this raw water to provide safe water to the community. Regular monitoring of various physical, chemical, and radioactive water quality parameters (WQPs) in raw water generates large datasets, which makes it difficult to come up with convenient findings for both the decision-makers and general public. A hierarchical water quality assessment framework develops three sub-indices, an overall water quality index, and a system for ranking of groundwater wells. Fuzzy analytical hierarchy process (fuzzy-AHP) establishes the importance weights of different WQPs and the sub-indices based on their impacts on human health, treatment processes, distribution system infrastructure, and irrigation applications. Fuzzy VIekriterijumsko KOmpromisno Rangiranje (fuzzy-VIKOR) method aggregates the WQPs’ performance for each well and ranks all the wells in a well field based on their overall pollution levels, i.e., remoteness from the applicable standards. For evaluating the pragmatism of the framework, data of 11 WQPs were obtained for 39 wells operating in three different well fields located along the boundaries and the central part of Buraydah, Qassim, Saudi Arabia. Spatial water quality maps showing physical, chemical, radioactive, and overall water quality assessment results revealed that the oldest well field located in the middle of the city outperforms the other two more recently developed well fields with lesser anthropogenic activities in their catchments. These findings testify that the primary source of contamination in deep aquifers is the natural sub-soil condition. The water quality indices will be useful to demonstrate the current situation of groundwater quality in Qassim Region and will facilitate the decision-makers for defining the intended uses of raw water sources (i.e., drinking, unrestricted irrigation, and restricted irrigation) and rehabilitation and renewal planning of the groundwater wells. The framework is applicable in the Kingdom of Saudi Arabia (KSA), Gulf Region, and elsewhere for groundwater quality assessment with desired modifications.

Nowadays, green supply chain management (SCM) practices are increasing among firms to adopt green practices and reduce the negative effects of supply chain operations on the environment. Firms such as manufacturing, mining, and agriculture have to improve their capacity in green SCM practices because environmental regulations force them to consider these issues. However, green practices are new and require comprehensive study to determine this problem. This study has taken the case of three garment manufacturing firms for the evaluation of green SCM practices in the context of Pakistan. The green SCM requires multi-dimensional techniques; therefore, fuzzy-based multi-criteria decision analysis approaches must be adopted while assessing green SCM practices of firms. This is because fuzzy-based methods obtain a significant solution for complex, vague, and uncertain multi-attribute problems in fuzzy environment. Therefore, in this study, a hybrid decision model comprised of Delphi, and Fuzzy Analytical Hierarchy Process (AHP) methodologies is proposed for assessing the green SCM practices of firms in terms of green design, green purchasing, green production, green warehousing, green logistics, and reverse logistics. The Fuzzy AHP method results reveal that “green purchasing,” “green design,” and “green production” are ranked the most important green indicators. Further, results reveal the ranking of manufacturing firms (alternatives) in the context of green SCM practices. This study shall help industries to focus on green SCM practices and adopt the green manufacturing process.

Cutting tool selection plays an important role in achieving reliable quality and high productivity work, and for controlling the total cost of manufacturing. However, it is complicated for process planners to choose the optimal cutting tool when faced with the choice of multiple cutting tools, multiple conflict criteria, and uncertain information. This paper presents an effective method for automatically selecting a cutting tool based on the machining feature characteristics. The optimal cutting tool type is first selected using a proposed multicriteria decision-making method with integrated fuzzy analytical hierarchy process (AHP). The inputs of this process are the feature dimensions, workpiece stability, feature quality, specific machining type, and tool access direction, which determine the cutting tool type priority after evaluating many criteria, such as the material removal capacity, tool cost, power requirement, and flexibility. Expert judgments on the criteria or attributes are collected to determine their weights. The cutting tool types are ranked in ascending order by priority. Then, the rule-based method is applied to determine other specific characteristics of the cutting tool. Cutting tool data are collected from world-leading cutting tool manufacturer, Sandvik, among others. An expert system is established, and an example is given to describe the method and its effectiveness.

Environmental conflict management gains significance in rational use of natural resources, ecosystem preservation and environmental planning for mineral mines. In Central Coast Vietnam, titan mines are subject to conflicting use and management decisions. The paper deals with an empirical research on applying a combination of the fuzzy Analytic Hierarchy Process (AHP) and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to measure environmental conflicts emerging as a result of titan mining in Vietnam. The methodology used in the paper combines the fuzzy AHP and the fuzzy TOPSIS to rank environmental conflicts and propose conflict prevention solutions in the titan mining industry of Ky Khang coastal commune (Ky Anh district, Central Coast Vietnam). Data was collected by using a questionnaire with 15 locals, 8 communal authorities, 2 district authorities, and 12 scientific experts on titan mining, environmental geology, and sustainability management. The result shows that, titan mining conflicts with the eight criteria of economic sectors at five alternative sites including beach, protected forest, agricultural area, settlement area, and industrial area. The conflicts between titan mining and forestry, agriculture, settlements, fishing and aquaculture are highly valued. The beach area shows most environmental conflict as a result of titan mining, followed by the agricultural area and settlement area. Based on the empirical findings, legal and procedural tools such as environmental impact assessments, strategic environmental assessments, integrated coastal zone management, marine spatial planning, and multi-planning integration advancing environmental management for titan mines in Vietnam are suggested.

This study aimed to analyse and assess desertification risks in the Upper Phetchaburi River Basin. Upstream areas are especially crucial for aquatic ecosystems since the mid- and downstream areas are continuously being utilized for agricultural and community purposes. Many parts of the basin have been at moderate risk of drought. The fuzzy analytical hierarchy process (FAHP) is an effective and widely accepted model used to identify complicated environmental problems and disasters and prioritize factors in environmental studies. This study emphasized on four main factors influencing drought: Climate, physical factors, soil and land utilization factors. Each factor contains ten sub-criteria to identify severity levels and specific issues. The major areas of the basin were facing different risk levels: moderate (21%), high (5.79%) and severe (0.07%). Precipitation and slope gradient were the main factors affecting drought risks. The problematic areas were agricultural areas located in midstream and downstream areas. Therefore, spatial mitigations and possible ways forward should focus on increasing moisture contents—to reduce soil erosion and enhance soil fertility—and create restrictions to ensure appropriate land use. The mitigations must take into account spatially critical factors and must also include an integrated plan for the entire basin area.

The paper presents a possibility to use a new PVM-VSI (Preference Vector Method computed in Vector Space of Increments) method in making decisions that demand that different variants should be considered, while being evaluated with respect to different criteria. Hence, knowledge about them is a must, and that knowledge is not necessarily available quantitatively, whereas the very evaluation should be relatively objective; that is, independent from the decision maker’s preferences or opinions. The paper presents the use of the PVM-VSI method in support decisions related to urban development—to rank projects submitted for implementation within the framework of a citizen budget. The ranking will make it feasible to determine which of the submitted projects will have the dominant influence on the town’s sustainable development, and, subsequently, which ones should be presented to citizens as the better ones out of the projects submitted, and to compare the method mentioned with methods used in similar decision-making problems in the past: Fuzzy AHP (Analytic Hierarchy Process), Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and Fuzzy PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluation).