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Aluminum parts are used in the aviation industry because of the need for light. However, in addition to lightness, critical parts that must have high strength properties have also been developed. The corrosion resistance, resistance to high temperatures, and workability were investigated in this case. It becomes difficult to choose among many aluminum materials that can be alternatives to each other when these features are included. The developed approach, which considers many of the features listed above and ultimately recommends to the user the most suitable aluminum material for the relevant critical part, will be used in overcoming the difficulties in this process. A material selection model is proposed in this paper for this purpose, and the decision-making model is demonstrated with examples from the aviation industry. Therefore, the developed model, which will enable the selection of the most suitable materials among alternative materials, especially for critical parts in the aviation industry, will guide professionals working in this field. For this purpose, the fuzzy TOPSIS method is used in the study, and suitable alternatives are determined. Finally, a robustness analysis is proposed to determine the most suitable aluminum material for highly uncertain situations. We apply a stability evaluation study based on process control theory in the robustness analysis. [ABSTRACT FROM AUTHOR]

Prototyping with incremental sheet forming is becoming the newest trend in the manufacturing industry due to its flexibility and low cost for generating customized components based on client needs. The main goal of this paper is to minimize the manufacturing time, surface roughness, and forming force requirement in the incremental forming process by optimizing the process parameters. The incremental forming experiments were performed on a CNC milling machine as per Taguchi L9 (33) orthogonal array by varying the tool diameter, step depth and wall angle in three levels. The optimization of the selected performance characteristics has been performed by the application of integrated fuzzy analytic hierarchy process and fuzzy technique for order of preference by similarity to ideal solution methods. Finally, analysis of variance has been used to understand the effect of process parameters on the individual response variables. The result shows that step depth was a highly significant parameter with the highest contribution of 70.31% followed by wall angle at 20.71%. Tool diameter is the least significant parameter with an 8.97% contribution. The effectiveness of the suggested technique was further verified by performing the confirmation experiment with optimum parameter. [ABSTRACT FROM AUTHOR]

Customer perception is an important consideration factor in evaluating the quality of human-computer interaction services. Sustainable user experiences and marketing strategies can be created by analyzing customer perception. By understanding consumer satisfaction with product services in the customer perception area, appropriate product service failure prevention strategies can be formulated. A service failure evaluation model is proposed in this study, which considers the customer tolerance area to accurately evaluate consumers' behavioral experiences from purchasing to using products. The concept of tolerance area is introduced, and a combination of the fuzzy Failure Mode and Effect Analysis (FMEA) method and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is used to construct a human-computer interaction service failure evaluation model. Potential service failure factors of smart speakers are accurately evaluated by this model, and these service failure factors are ranked within the tolerance area. The research identifies voice misinterpretation and signal connectivity issues as the primary risk factors impacting the quality of human-computer interaction for smart speakers. The application of this method not only enhances the evaluation of smart speaker human-computer interaction services quality but also aids in the precise identification and prioritization of critical failure modes. The proposed service failure prevention strategies can reduce consumer dissatisfaction and provide innovative references for smart product design and marketing. The findings bolster empirical evidence for service failure prevention strategies in smart products and pave the way for novel perspectives on enhancing the quality of human-computer interaction services. [ABSTRACT FROM AUTHOR]

This study investigates the factors influencing C O 2 emissions in Romania from 1990 to 2023 using the Autoregressive Distributed Lag (ARDL) model. Before the ARDL model, we identified a set of six policies that were ranked using Fuzzy Electre, Topsis, DEMATEL, and Vikor. The multi-criteria decision-making (MCDM) methods have highlighted the importance of a circular policy on C O 2 emission reduction, which should be a central focus for policymakers. The results of the ARDL model indicate that, in the long term, renewable energy production reduces C O 2 emissions, showing a negative relationship. Conversely, an increase in patent applications and urbanization contributes to higher C O 2 emissions, reflecting a positive impact. In total, five key factors were analyzed: C O 2 emissions per capita, patent applications, gross domestic product, share of energy production from renewables, and urbanization. Notably, GDP does not significantly explain C O 2 emissions in the long run, suggesting that economic growth alone is not a direct driver of C O 2 emission levels in Romania. This decoupling might result from improvements in energy efficiency, shifts towards less carbon-intensive industries, and the increased adoption of renewable energy sources. Romania has implemented effective environmental regulations and policies that mitigate the impact of economic growth on C O 2 emissions. [ABSTRACT FROM AUTHOR]

Purpose: The objective of this study is to investigate the concept of "earthquake resistance" in high-rise buildings and assess the current level of structural strength in the areas where these structures are situated. The study aims to identify and implement necessary measures to enhance resilience in these areas. A comprehensive literature review was conducted to develop a conceptual framework focusing on earthquake resistance's meanings, stages and physical elements to achieve these goals. Design/methodology/approach: This study focuses on Istanbul, a city known for its high earthquake risk, specifically targeting the Atasehir district. The research utilizes the DEMATEL (Decision-Making Trial and Evaluation Laboratory) method to evaluate urban resilience parameters. Additionally, the Fuzzy TOPSIS (Preference Ranking Technique by Similarity) method is employed to analyze the location of five buildings in Atasehir, using criterion weights derived from this methodology. Findings: The findings indicate that resilience varies depending on the distance of the buffers. Moreover, the amount and quality of urban equipment in the study areas have a significant impact on the earthquake resistance level of the surrounding areas where high-rise buildings are situated. Building upon this analysis, the study suggests the implementation of measures aimed at augmenting the quantity and quality of urban facilities in the study areas, consequently enhancing urban resilience. Originality/value: The originality and value of this study lie in its examination of seismic resilience within the context of high-rise buildings and the identification of necessary measures to increase resilience in areas where these structures are prevalent. By focusing on Istanbul, a city with a high earthquake risk, and specifically selecting the Atasehir district as the study area, this research provides a comprehensive conceptual framework for understanding urban resilience and its physical components. Moreover, the study offers a fresh perspective on urban resilience by highlighting the influence of tall buildings on the surrounding areas. Ultimately, it provides practical recommendations for architects, urban planners and other stakeholders to improve regional earthquake resilience. [ABSTRACT FROM AUTHOR]

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The healthcare industry has been put to test the need to manage enormous amounts of data provided by various sources, which are renowned for providing enormous quantities of heterogeneous information. The data are collected and analyzed with different Data Analytic (DA) and machine learning algorithm approaches. Researchers, scientists, and industrialists must manage or select the best approach associated with DA in healthcare. This scientific study is based on decision analysis between the DA factors and alternatives. The information affects the whole system in a rational manner. This information is very important in healthcare sector for appropriate prediction and analysis. The evaluation discusses its benefits and presents an analytic framework. The Fuzzy Analytic Hierarchy Process (Fuzzy AHP) approach is used to address the weight of the factors. The Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) address the rank of the data analytic alternatives used in healthcare sector. The models used in the article briefly discuss the challenges of DA and approaches to address those challenges. The assorted factors of DA are capture, cleaning, storage, security, stewardship, reporting, visualization, updating, sharing, and querying. The DA alternatives include descriptive, diagnostic, predictive, prescriptive, discovery, regression, cohort and inferential analyses. The most influential factors of the DA and the most suitable approach for the DA are evaluated. The 'cleaning' factor has the highest weight, and 'updating' is achieved at least by the Fuzzy-AHP approach. The regression approach of data analysis had the highest rank, and the diagnostic analysis had the lowest rank. Decision analyses are necessary for data scientists and medical providers to predict diseases appropriately in the healthcare domain. This analysis also revealed the cost benefits to hospitals. [ABSTRACT FROM AUTHOR]

Noise pollution in hospitals has increased over the last few years to a level that can threaten the health and productivity of staff and patient safety. There are many control measures to reduce hospital noise. However, there is still no consensus on the best measures. This study aims to prioritize the control measures for reducing hospital noise. The work is divided into three phases. The first phase identifies and categorizes noise sources in hospitals through a review of the state-of-the art literature using Scopus®, ProQuest, PubMed, Google Scholar, Embase,™ and Web of Science™. The second phase identifies possible strategies for reduction of hospital noise and the best criteria for their adoption using findings from the literature review and interviews with corresponding experts. The third phase uses Fuzzy Analytic Hierarchy Process (FAHP) method and the Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS) method to weigh the criteria and to prioritize the control measures. Based on the results, hospital noise sources were classified into four groups: outdoor noise sources (29.7%), noise produced by domestic facilities (20.8%), indoor noise from human activities (27.5%), and noise produced by diagnostic and treatment equipment (22%). The study further arrives at a set of 9 criteria and 22 alternatives ranked using FAHP and fuzzy TOPSIS. The criteria's weights were determined using the FAHP method, with feasibility (0.175), effectiveness (0.143), and interference with staff activities (0.140) being the most important criteria. It was found that engineering controls such as substitution of noisy equipment (rank = 1), using acoustic enclosures (rank = 2), using double-glazed windows (rank = 2), and soundproofing walls, doors, and windows (rank = 3) have priority for reducing hospital noise. [ABSTRACT FROM AUTHOR]

Pilot recruitment is critical as they pose a multifaceted challenge for civilian and military organizations due to the complex traits impacting their missions and performance. In this study, a novel set of criteria and sub‐criteria were determined to compare twelve candidate pilots. Numerically immeasurable, imprecise, and non‐linear continuous fuzzy linguistic traits (variables) were studied which make the work unique and challenging due to individual preferences and disagreements between decision‐makers (DMs). The outcomes of three distinct fuzzy multiple criteria decision‐making (MCDM) approaches; fuzzy TOPSIS, fuzzy VIKOR, and fuzzy PROMETHEE were evaluated with trapezoidal fuzzy numbers (TFNs) to sort the positions of candidate pilots. Moreover, a unique defuzzification ranking method was employed to adjust the results of fuzzy MCDM methods for the synthesis and evaluation of outcomes of the pilot selection problem. All these efforts make the paper original and outstanding. Our findings and analysis suggested that fuzzy TOPSIS and PROMETHEE methods' outcomes showed maximum close similarity for ranking positions. However, substantial distinctions were noted when comparing these outcomes with the fuzzy VIKOR approach. Yet, the mission of predicting and revealing the best candidates is related to several traits, their weights, and the methods selected. Therefore, since vague information and ambiguous preferences match fuzzy superiority, a comprehensive and unbiased evaluation was achieved, ensuring the integrity of the decision‐making process. The results can be employed to enhance the safety and efficiency of airline operations and ensure that the most qualified and competent pilots are selected for the job. [ABSTRACT FROM AUTHOR]

Prioritizing Lean Six Sigma (LSS) projects that align with company objectives is crucial, yet traditional methods struggle with associated subjective criteria. This study proposed a hybrid Best Worst Method - Fuzzy TOPSIS approach to prioritize LSS projects for a project consulting company. The method integrates expert opinion from 3 decision-makers on 7 main criteria and 24 sub-criteria to select the optimal LSS projects in project management consulting company. Triangular fuzzy numbers were used to describe the responses. The fuzzy positive and negative solutions of the five alternatives were calculated. Results indicate project alternative 3 (ERP Deployment Project) is the optimal choice with the highest closeness coefficient (0.68651), while project alternative 2 (Warehouse Automation Project - 0.54077), project 1 (Data Warehousing Project -- 0.46731), project 4 (Battery life improvement -- 0.54077), and project 5 (Improvement of OEE -- 0.34093) follow closely, thus ensuring efficient project selection. Emphasis should be placed on project 3 when considering the 7 criteria while the other projects are closely monitored in the ranking order. Future research can explore the combination of other multi-criterion decision making approaches that enrich criteria weights and address the subjectivity of decision-makers' opinion. The hybrid methodology used in this work is applicable in other disciplines where selection and ranking problems exists. [ABSTRACT FROM AUTHOR]

Previous studies in the literature have shown that Digital Marketing (DM) can be a factor influencing competitiveness and the performance of marketing actions so that a company can correctly reach the target audience. From this literary assumption, it is imperative to evaluate tools that can help marketing managers in decision-making to select the most social media platform to use the DM. In this context, this article aims to analyze the performance of social media platforms for using the strategies DM in organizations. from the point of view of experts from different organizations that use DM for marketing actions. To provide empirical evidence, the selection of criteria was based on the eight dimensions of the DM mix to the lens of multi-criteria decision-making based on the inter-criteria correlation method (CRITIC). This method adhered to the order of preference by similarity technique to find an ideal solution with the help of the Fuzzy TOPSIS environment. The results discovered corroborate the previous literature and stand out, mainly by showing that the main criterion with greater weight among the eight analyzed dimensions was promotion (Cr5). Based on this finding, these results indicate that the best performing alternative for DM actions for the specific case was the A1-Facebook platform. This article brings reflections, and presents a robust tool of quantitative analysis in addition to bringing theoretical and managerial contributions that can direct DM strategies in the consumer's journey through social media platforms. [ABSTRACT FROM AUTHOR]

Every new storage tank in the oil sector is required to be calibrated before using them for oil storage and also to be re-calibrated as statutorily required. Depending on the prevailing regulatory guidelines in the country, either a wet or geometrical method of calibration is adopted. This study examines various geometrical methods of tank calibration vis–a–vis their strengths and weaknesses. Tank farm owners (operators) are always faced with the challenge of selecting the best geometrical method of tank calibration while considering some number of factors. To address this aforementioned issue, this study was embarked upon to rank the known four (4) geometrical methods of tank calibration using Fuzzy TOPSIS (F-TOPSIS) approach. Three different experts were drawn from reputable calibration companies to respond to the questionnaire based on the following criteria: Accuracy; Hazard involved; Time consumed; Drudgery involved; and Cost. The interdependencies among the criteria were considered, and a triangular fuzzy set was adopted. The results revealed that the Electro-Optical Distance Ranging (EODR) is the best alternative with a closeness coefficient of 0.974, while the Optical Reference Line Method was ranked least with a closeness coefficient of 0.197. To validate the result of rating by F-TOPSIS, another hybrid MCDM, Fuzzy Analytic Hierarchy Process (FAHP) was used to rank the alternatives, and EODR was also ranked as the best alternative. Sensitivity analysis was carried out for five different scenarios to validate the robustness of the decision-making tool used in this study. All the scenarios considered for the sensitivity analysis ranked EODR and OTM (Optical Triangulation Method) first and second, respectively. So, it can be concluded that EODR is the best geometrical method of tank calibration. Though the cost of using EODR might be higher than other methods, this is being compensated for by higher accuracy, less time with less exposure to hazards. It can also be confirmed that F-TOPSIS is a formidable MCDM tool that finds its usage in every facet of life for a robust decision-making process. [ABSTRACT FROM AUTHOR]

Abstract Customer perception is an important consideration factor in evaluating the quality of human-computer interaction services. Sustainable user experiences and marketing strategies can be created by analyzing customer perception. By understanding consumer satisfaction with product services in the customer perception area, appropriate product service failure prevention strategies can be formulated. A service failure evaluation model is proposed in this study, which considers the customer tolerance area to accurately evaluate consumers’ behavioral experiences from purchasing to using products. The concept of tolerance area is introduced, and a combination of the fuzzy Failure Mode and Effect Analysis (FMEA) method and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is used to construct a human-computer interaction service failure evaluation model. Potential service failure factors of smart speakers are accurately evaluated by this model, and these service failure factors are ranked within the tolerance area. The research identifies voice misinterpretation and signal connectivity issues as the primary risk factors impacting the quality of human-computer interaction for smart speakers. The application of this method not only enhances the evaluation of smart speaker human-computer interaction services quality but also aids in the precise identification and prioritization of critical failure modes. The proposed service failure prevention strategies can reduce consumer dissatisfaction and provide innovative references for smart product design and marketing. The findings bolster empirical evidence for service failure prevention strategies in smart products and pave the way for novel perspectives on enhancing the quality of human-computer interaction services.

Abstract The healthcare industry has been put to test the need to manage enormous amounts of data provided by various sources, which are renowned for providing enormous quantities of heterogeneous information. The data are collected and analyzed with different Data Analytic (DA) and machine learning algorithm approaches. Researchers, scientists, and industrialists must manage or select the best approach associated with DA in healthcare. This scientific study is based on decision analysis between the DA factors and alternatives. The information affects the whole system in a rational manner. This information is very important in healthcare sector for appropriate prediction and analysis. The evaluation discusses its benefits and presents an analytic framework. The Fuzzy Analytic Hierarchy Process (Fuzzy AHP) approach is used to address the weight of the factors. The Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) address the rank of the data analytic alternatives used in healthcare sector. The models used in the article briefly discuss the challenges of DA and approaches to address those challenges. The assorted factors of DA are capture, cleaning, storage, security, stewardship, reporting, visualization, updating, sharing, and querying. The DA alternatives include descriptive, diagnostic, predictive, prescriptive, discovery, regression, cohort and inferential analyses. The most influential factors of the DA and the most suitable approach for the DA are evaluated. The ‘cleaning’ factor has the highest weight, and ‘updating’ is achieved at least by the Fuzzy-AHP approach. The regression approach of data analysis had the highest rank, and the diagnostic analysis had the lowest rank. Decision analyses are necessary for data scientists and medical providers to predict diseases appropriately in the healthcare domain. This analysis also revealed the cost benefits to hospitals.

Abstract This study addresses the growing anxiety and depression among Chinese university students by evaluating and ranking music education strategies to alleviate these issues. We integrates Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). FAHP was utilized to determine the weight of factors such as academic pressures, social relationships, and cultural norms, while fuzzy TOPSIS ranked the effectiveness of music education interventions based on these weights. The results revealed that ‘Mental health stigma’ and ‘Academic Pressures and Rigidity’ are among the highest weighted factors, significantly impacting student anxiety. ‘Music Appreciation and Music-Based Self-Care’ emerged as the most effective strategy. These results highlight the importance of direct involvement in music-related activities for improving student mental health.

Abstract The literature has explored various methods for assessing minimum environmental flow. Implementing holistic approaches proves to be prohibitively expensive and impractical for many small and medium projects. Hence, desktop and cost-effective methods are commonly employed without an integrated decision-making system to justify the assessed values. This study introduces a systematic decision-making framework aimed at selecting the most suitable method for assessing the actual needs of river habitats. Employing a fuzzy technique known as the Order Preference Similarity to the Ideal Solution (FTOPSIS), the study considers factors such as physical, thermal, and dissolved oxygen habitat suitability, maximum habitat area, and water demand loss function to determine the most appropriate method among established ones, including the Tennant method, flow duration curve analysis method, wetted perimeter method, and physical habitat simulation method. The results prioritize physical habitat simulation, wetted perimeter by slope method, and flow indices of 70%, 75%, and 80% by flow duration curve analysis method as the optimal approaches for assessing minimum environmental flow. This proposed decision-making system offers a viable platform to explore the applicability of existing cost-effective methods for assessing minimum environmental flow. It also serves as an effective mechanism for reducing negotiations among stakeholders by comprehensively considering all relevant aspects in the environmental management of river ecosystem requirements.

This study addresses the growing anxiety and depression among Chinese university students by evaluating and ranking music education strategies to alleviate these issues. We integrates Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). FAHP was utilized to determine the weight of factors such as academic pressures, social relationships, and cultural norms, while fuzzy TOPSIS ranked the effectiveness of music education interventions based on these weights. The results revealed that 'Mental health stigma' and 'Academic Pressures and Rigidity' are among the highest weighted factors, significantly impacting student anxiety. 'Music Appreciation and Music-Based Self-Care' emerged as the most effective strategy. These results highlight the importance of direct involvement in music-related activities for improving student mental health. [ABSTRACT FROM AUTHOR]

The literature has explored various methods for assessing minimum environmental flow. Implementing holistic approaches proves to be prohibitively expensive and impractical for many small and medium projects. Hence, desktop and cost-effective methods are commonly employed without an integrated decision-making system to justify the assessed values. This study introduces a systematic decision-making framework aimed at selecting the most suitable method for assessing the actual needs of river habitats. Employing a fuzzy technique known as the Order Preference Similarity to the Ideal Solution (FTOPSIS), the study considers factors such as physical, thermal, and dissolved oxygen habitat suitability, maximum habitat area, and water demand loss function to determine the most appropriate method among established ones, including the Tennant method, flow duration curve analysis method, wetted perimeter method, and physical habitat simulation method. The results prioritize physical habitat simulation, wetted perimeter by slope method, and flow indices of 70%, 75%, and 80% by flow duration curve analysis method as the optimal approaches for assessing minimum environmental flow. This proposed decision-making system offers a viable platform to explore the applicability of existing cost-effective methods for assessing minimum environmental flow. It also serves as an effective mechanism for reducing negotiations among stakeholders by comprehensively considering all relevant aspects in the environmental management of river ecosystem requirements. [ABSTRACT FROM AUTHOR]

Mining is a high-risk industry where occupational accidents are common due to its complex nature. Therefore, providing a more holistic and dynamic risk assessment framework is essential to identify and minimize the potential risks and enhance safety measures. Unfortunately, traditional risk assessment methods have limitations and shortcomings, such as uncertainty, differences in experience backgrounds, and insufficiency to articulate the opinions of experts. In this paper, a novel risk assessment method precisely for such cases in the mining sector is proposed, applied, and compared with traditional methods. The objective of this study is to determine the risk scores of Turkish Coal Enterprises, based on non-fatal occupational accidents, which operates eight large-scale open-cast coal mine enterprises in Türkiye. The causes of the accidents were categorized into 25 sub-criteria under 6 main criteria. The risk scores for these criteria were computed using the Pythagorean fuzzy Analytical Hierarchy Process (PFAHP) method. The first shift (8–16 h) (0.6341) for the shift category is ranked highest out of the 25 sub-risk factors, followed by maintenance personnel (0.5633) for the occupation category; the open-cast mining area (0.5524) for the area category, the 45–57 age range (0.5279) for employee age category, and the mining machine (0.4247) for the reason category, respectively. The methodologies proposed in this study not only identify the most important risk factors in enterprises, but also provide a mechanism for risk-based rankings of enterprises by their calculated risk scores. The enterprises were risk-based ranked with the fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) method and Paksoy approach based on interval type-2 fuzzy sets (IT2FSs). The findings indicate that the first three risk score rankings of enterprises are the same for both approaches. To examine the consistency of the applied methods, sensitivity analyses were performed. The results of the study also indicate that the proposed approaches are recommended for effective use in the mining sector due to their ease of application compared to other methods and their dynamic nature in the risk assessment process. [ABSTRACT FROM AUTHOR]

To maximize its synergetic effect across the cycle from prevention to response to post-crime management, crime prevention requires a balanced combination of spatial urban design and advanced crime prevention technologies for crime prediction and real-time response. This study derived intelligent Crime Prevention Through Environmental Design (CPTED) services and suggested a decision model based on the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to implement these services in municipal control centers. The analysis results are summarized as follows. First, this study established a fuzzy TOPSIS-based decision-making support model enabling local government control centers to effectively select intelligent CPTED service elements. Second, overall, operator-led Closed-Circuit Television (CCTV) and platform control technologies were identified as significant components of intelligent CPTED service elements. Third, a comparison by city size revealed that large cities in the Seoul metropolitan area rated system services for control based on advanced crime prevention infrastructure (e.g., the crime monitoring systems and real-time control drones/robots) relatively higher. In contrast, small and medium-sized cities in other provinces rated services that were perceptible to residents and improved crime-prone environments (e.g., artificial intelligence (AI) video analysis for living safety) relatively higher. [ABSTRACT FROM AUTHOR]

This study investigates the extent to which circular economy (CE) practices are adopted within supply chains in the Brazilian context. An expert survey was conducted to assess eight critical factors for the integration of CE practices in supply chains. The collected data was analyzed using a modified version of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), specifically the Fuzzy TOPSIS class. Sensitivity analyses were performed to validate the robustness of the results. The findings indicated that practices related to economic and risk management, cleaner production, top management support, and knowledge management were categorized as having medium maturity. Conversely, practices associated with governance, product development, infrastructure, and social and cultural changes are still in an early stage. This research provides insights for organizations by identifying areas of strength and areas requiring attention in the adoption of CE practices within Brazilian supply chains. Policymakers can use the findings to design targeted policies and incentives that encourage and facilitate the development of circularity in supply chains, thus promoting CE principles. This research highlights the importance of addressing specific factors related to CE practices within supply chains, providing a framework for further investigations and strategies to bridge the gap between CE and supply chain management. The findings suggest that there are social and cultural challenges associated with the adoption of CE practices, implying a need for awareness campaigns, education, and community involvement to drive positive social change and adoption of CE principles. [ABSTRACT FROM AUTHOR]

Optimization of an intra-city express delivery network from three to two levels is of great interest to suppliers and customers for reducing costs and improving service efficiency. One feasible solution is to identify critical nodes in the three-level network and upgrade them as transshipment facilities in the two-level one. However, traditional optimization models seldom combine empirical business data, composite metrics, and objective evaluation rules. We proposed an approach integrating empirical data, multi-criteria decision-making methods based on the real-world application of the SF Express Chengdu branch. We also developed a mathematical optimization model using statistical and operations management techniques combined with logistics expertise for a location decision. First, the appropriateness of each service point as a candidate transshipment facility is evaluated from internal and external perspectives by applying multiple centrality assessment from complex network theory and fuzzy Technique for Order Preference by Similarity to an Ideal Solution, respectively. Second, 16 candidate transshipment facilities are selected by combining these two ways. Then, a multi-objective integer programming model is built to obtain the optimal number, locations of transshipment facilities, and the corresponding service points covered by each transshipment facility. Using this multi-methodologic approach, we show that the optimized two-level network is economically feasible and simply applicable, with the total cost and average delivery time reduced by 18.41% and 6 h, respectively. This article is of practical significance and provides an important reference for optimizing ground express service networks for other large cities. [ABSTRACT FROM AUTHOR]

Group decision-making in capital investment involves a collaborative process where multiple stakeholders contribute their perspectives, insights, and expertise to evaluate investment opportunities and make informed decisions. This process's practical and methodological aims can vary depending on the organization's goals, industry, and market conditions. Researching capital investment group decision-making is motivated by several factors, such as optimizing investment decisions, enhancing performance, managing risk, adapting to changing conditions, and building knowledge and expertise. The investment decision relates to the distribution of financial resources. Investors select the most appropriate investment opportunities based on risk profiles, investment aims, and expected returns. Fuzzy multicriteria group decision-making in capital investment extends the traditional decision-making process to accommodate multiple criteria that are often uncertain, vague, or subjective in nature. This paper aims to suggest a technique known as the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (fuzzy TOPSIS) for group decision-making about investment in the respective vehicle. The fuzzy TOPSIS technique represents a decision for experts, which is multicriteria and includes an aggregated decision-making process. This paper shows the application of this method when choosing the best alternative, considering the choice of vehicle. [ABSTRACT FROM AUTHOR]

The optimal low impact development (LID) design for restoring the water cycle within watersheds considering climate change is crucial for adaptation to future climate change. In this study, a practical and effective allocation method for permeable pavement was proposed to restore the water cycle within watersheds considering future climate change. A total of 15 general circulation models (GCMs) of the Coupled Model Intercomparison Project (CMIP) Phase 6 were used to simulate future climate variables according to two shared socioeconomic pathway (SSP) scenarios. The stormwater management model (SWMM) was employed for long-term hydrological simulation. The installation priority of permeable pavement in sub-watersheds was robustly determined using coupled fuzzy TOPSIS and VIKOR methods. The results of this study confirmed that the different climate predictions of each GCM could affect the prioritization results. Furthermore, it was confirmed that the allocation method adopted in this study improved water cycle restoration more effectively than when allocating the available capacity at once according to priority. The results of this study could help accurately determine the LID capacity of each sub-watershed under limited resources. [ABSTRACT FROM AUTHOR]

This study investigates the application of the fuzzy logic method for scoring open-ended items, specifically comparing its effectiveness against traditional scoring methods. Utilizing the fuzzy TOPSIS method within the mathematics domain, this research established seven criteria for evaluating open-ended responses, developed in consultation with three experts. Due to constraints imposed by the pandemic, the study did not proceed with a real-world application; instead, it simulated data for 25 students to compare the rankings derived from traditional and fuzzy logic methods using the MS Excel program. The research produced three distinct rankings using the conventional method and analyzed the correlation between these rankings and those generated by the fuzzy TOPSIS method, employing the Spearman rank correlation coefficient. The findings reveal a significantly positive correlation between the rankings obtained through traditional methods and those acquired via the fuzzy logic approach, suggesting the latter's potential as an effective alternative for evaluating open-ended responses. [ABSTRACT FROM AUTHOR]

To solve difficulties involving various groups' decision-making problems, this work has been proposed to develop a logical aggregation approach to aggregate decision-makers' crisp data into Pythagorean fuzzy numbers. By combining the established strategy with the Pythagorean fuzzy TOPSIS method, a hybrid Pythagorean fuzzy multiple criteria group decision-making methodology is presented. Based on fuzzy rules inference and the Takagi–Sugeno technique, a novel function is created to represent the degrees of uncertainty in decision-makers' data. As an example, the material selection process in practical additive manufacturing designs is provided to show how the proposed methodology may be applied to actual applications. Sensitivity analysis is used to evaluate the effectiveness of the suggested methodology. The outcomes demonstrate that the plan was successful in producing a PFN that accurately reflects the decision-maker's knowledge. [ABSTRACT FROM AUTHOR]

This study aims to verify the main factors influencing turnover intention in the Iran hospitality industry. The objective of this study is to construct a fuzzy AHP and fuzzy TOPSIS model to evaluate the dimensions of the hotel employee turnover intention model. The performance evaluation for employee turnover intention includes work itself, supervision, coworkers relationship, salary and benefit, career opportunities, job stress, perceived risk, and job insecurity. These dimensions generate a final evaluation for ranking priority among the employee turnover intention of the proposed model. The importance of dimensions is evaluated by 20 experts, and decision-making is processed through the fuzzy concept and fuzzy environment. From the critical fuzzy AHP and fuzzy TOPSIS analysis results, the study shows that the most important dimensions of employee turnover intention in the hotel industry model are salary and benefits. Moreover, the results indicate that the least important dimensions are the Co-workers Relationship, Supervision, and Career Opportunities. The second group dimensions that impact employee turnover in the context of the COVID-19 epidemic are work itself, job stress perceived risk, and job insecurity. In addition, this study's results show that three-star hotels have the highest value of turnover intention; the second is the Four and Five-star hotels, and the third is the below three-star hotels. The results of the study will help businesses in the field of hospitality have a more comprehensive view of human resource management activities. Especially, this study provides implications for hotel managers in understanding employee behavior and their turnover intention during the context of the COVID-19 epidemic based on the eight proposed dimensions. [ABSTRACT FROM AUTHOR]

Contractors play an integral role in construction projects, and their qualifications directly impact various aspects of a project's success. The unbiased selection of contractors is a challenge in the construction industry worldwide, particularly in public projects where impartiality in the final selection is essential. Numerous factors must be considered when evaluating contractors, making the selection process challenging for the human brain. This paper introduces and compares two methods for assessing contractor prequalification by applying the fuzzy theory. The idea is to facilitate using human judgments in a mathematical system for decision-making with regard to selecting contractors. The method is based on identifying a fuzzy weight for the selection criteria using the Buckley method. Fuzzy TOPSIS and Fuzzy SAW methods are then used for the qualification ranking of the contractors. The proposed models are assessed using a case study. A sensitivity analysis was also conducted to compare the two models. The introduced method is expected to improve the quality of the qualification-based selection of contractors and prevent possible losses from hiring unsuitable contractors. [ABSTRACT FROM AUTHOR]

Purpose: The COVID-19 pandemic has caused significant disruptions to global supply chains (SCs), affecting the production, distribution, and transportation of goods and services. To mitigate these disruptions, it is essential to identify the barriers that have impeded the seamless operation of SCs. This study identifies these barriers and assesses their impact on supply chain network (SCN). Design/methodology/approach: To determine the relative importance of different barriers and rank the affected industries, a hybrid approach was employed, combining the best-worst method (BWM) and the technique for order preference by similarity to an ideal solution (TOPSIS). To accommodate the inherent uncertainties associated with the pandemic, a triangular fuzzy TOPSIS was used to represent the linguistic variable ratings provided by decision-makers. Findings: The study found that the airlines and hospitality industry was the most affected by the barriers, accounting for 46% of the total, followed by the healthcare industry (23%), the manufacturing industry (19%), and finally the consumer and retail industry (17%). Research limitations/implications: This study is limited to the four critical industries and nine identified barriers. Other industries and barriers may have different weights and rankings. Nevertheless, the findings offer valuable insights for decision-makers in SC management, aiding them in mitigating the impact of COVID-19 on their operations and enhancing their resilience against future disruptions. Originality/value: This study enhances understanding of COVID-19's impact on SCN and provides a framework for assessing disruptions using multi-criteria decision-making processes. The hybrid approach of BWM and TOPSIS in a fuzzy environment is unique and offers potential applicability in various evaluation contexts. [ABSTRACT FROM AUTHOR]

This feasibility study explores the viability of solar PV-powered Reverse Osmosis (RO) desalination in five locations in Visakhapatnam, India. The assessment integrates technical, economic, environmental, social, and political considerations using Multi-Criteria Decision Analysis (MCDA) with Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) and Fuzzy Analytic Hierarchy Process (Fuzzy AHP) methods to handle uncertainties in decision-making. The study evaluates the technical feasibility of the integration, conducts economic analysis, examines environmental impacts, investigates social benefits, and challenges, and analyzes the political landscape. The former emphasizes the significance of understanding challenges and potential solutions associated with RO desalination, aiming for sustainable development aligned with local and global goals. Yarada and Bheemili were the most suitable locations selected based on Fuzzy TOPSIS and Fuzzy AHP, respectively. The study also highlighted the need for public awareness and government support for desalination projects. [ABSTRACT FROM AUTHOR]

The emergence of Industry 4.0 (I4.0) is reshaping industries worldwide, driven by rapid technological progress and the need for open innovation. This study focuses on understanding the interdependencies of driving factors of I4.0 maturity in developing countries using Fuzzy Multi-Criteria Decision Analysis (MCDA) methods. By analyzing Indonesia, Pakistan, and Venezuela, the research aims to foster open innovation and address the unique challenges these nations face in adopting I4.0 technologies. I4.0 maturity models are essential for evaluating current maturity levels and identifying areas for improvement. However, the complexity and interdependence of various factors—ranging from data science and technology to policy, governance, and open innovation dynamics, such as social open innovation and the role of SMEs—complicate this process. This study employs Fuzzy TOPSIS and Fuzzy DEMATEL to identify the critical factors influencing I4.0 maturity and analyze their interdependencies and prioritization. The results indicate that 'Data and Information' and 'Willingness to Change' are crucial across all countries, while strategic differences between large enterprises and SMEs highlight the need for tailored approaches. This research highlights the importance of continuous IT investment, digital leadership, collaborative ecosystems, and agile strategies in fostering open innovation and driving I4.0 adoption. This research contributes to the theoretical and practical understanding of I4.0 maturity, offering valuable insights for practitioners and academics to explore the dynamic interactions of I4.0 factors and their impact on operational efficiency.

Assessing air quality with multiple parameters is crucial and demands meticulous analysis due to its profound impact on human health and the environment. Traditional air quality techniques might overlook uncertainties in pollutant data. The fuzzy logic approach adeptly handles such uncertainties. This study thoroughly analyses two approaches: Fuzzy Multi-Attribute Decision Making (MADM) methods and the Fuzzy Inference System (FIS). Fuzzy MADM methods, including the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), are employed with a combined weighting approach involving Analytical Hierarchy Process (AHP) and Entropy. The FIS approach utilizes the Mamdani method built using MATLAB 2021b’s fuzzy logic toolbox. The air quality is assessed for the Diwali festival for the year 2022 in the various regions of Tamil Nadu, India. Spearman’s rank correlation is utilized to determine the result accuracy of fuzzy MADM and FIS. The fuzzy MADM methods attained a higher correlation of 0.88 compared to the Mamdani FIS of 0.84. Fuzzy MADM proves most effective in air quality assessment. [ABSTRACT FROM AUTHOR]

Buying decisions are influenced by a variety of factors that can give rise to impulsive, unplanned, or even irrational purchases. Research has examined the motivational factors that foster organic food consumption, but no study has explored the relative weights of these factors and whether their effects vary depending on the type of food. This study adopted the cognitive-affective perspective to examine the antecedents of online impulsive buying of organic food using a sample of 452 consumers living in Baghdad, Iraq. The fuzzy AHP and fuzzy TOPSIS methods were used to rank five organic food alternatives. The results revealed that the effects of cognitive factors on organic food purchases differ from those of affective factors. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper was to understand the difficulties related to asset management observed by experts in Brazilian organizations in light of the requirements outlined in the ISO 55001:2014 standard. Design/methodology/approach: A survey was performed with asset management experts. The collected data were analyzed using frequency analysis, hierarchical cluster analysis and fuzzy technique for order preference by similarity to deal solution (TOPSIS). Findings: Based on data analysis, the most critical difficulties observed were related to managing and controlling the impact of changes in the company that affect asset management objectives; to the committing to and supporting the asset management system by the top management of the organization; to manage the processes for dealing with risks and opportunities for the asset management system and plans, and correcting failures in asset performance; and to plan and conduct actions in an integrated manner to identify and minimize adverse impacts associated with the asset management system, and afterwards verifying their effectiveness. Originality/value: The findings of this study have important theoretical and practical contributions, since they indicate the most critical points observed in asset management in Brazil, which can be used as a source for future research and by professionals to prioritize difficulties in future planning and develop action plans to overcome them. The step-by-step methodological approach presented in this study provides professionals and researchers with a replicable method of identifying potential asset management difficulties in a given specific reality. [ABSTRACT FROM AUTHOR]

In this study, a customized version of a less-preferred methodology in decision-making processes, i.e., the interval type-2 fuzzy ORESTE (IT2F-ORESTE), is proposed, and its effectiveness for selecting the most viable projects is demonstrated. The findings are evaluated against those of fuzzy TOPSIS, which is among the most preferred methods, to provide evidence that the proposed method achieves comparable and even superior results. To this end, multicriteria decision-making studies conducted between 2016 and 2021 were examined. Subsequently, 30 automotive manufacturing projects were evaluated over seven criteria using the fuzzy TOPSIS and customized IT2F-ORESTE methods. The results revealed that IT2FORESTE assigned the highest ranks to projects with high earning potential, low cost, low number of operations, and high production capacity, whereas fuzzy TOPSIS failed to select the best project. To the best of the authors' knowledge, this is the first study to utilize this new IT2F-ORESTE method in project evaluation within the automotive industry and demonstrate its superiority over that of conventional methods. [ABSTRACT FROM AUTHOR]

Women's empowerment programs play a critical role in achieving the United Nations' (UN's) sustainable development goal of "Gender Equality". However, non-profit organizations (NPOs) running women's empowerment (WE) programs face challenges in monitoring, assessing, and evaluating the social impact (SI) and program performance due to the lack of solid guidelines. This study aims to analyze the impact and outcome evaluation indicators of WE programs by providing a quantitative tool. A multi-criteria decision-making (MCDM) model is proposed to identify and prioritize the performance indicators by utilizing Fuzzy TOPSIS (FTOPSIS) and Fuzzy AHP (FAHP) in a combined methodology. Results validated the identification and classification of the indicators by their importance and viability. In a qualitative study with NPOs working on WE in Turkey, social impact and outcome evaluation indicators are defined and ranked by criteria set in the proposed combined MCDM framework. The study aims to contribute to the theoretical frameworks and practices on social impact and outcome evaluation of women's empowerment. [ABSTRACT FROM AUTHOR]

This paper aims to apply a multi-criteria decision-making (MCDM) framework to evaluate the environmental performance of the medical service supply chain using a case study in India. An application of MCDM method, the fuzzy TOPSIS (Technique for order of preference by similarity to ideal solution) model, is used for Medical Support Service Provide firms (MSSPF) environmental performance evaluation. We require multiple and conflicting criteria to fix real-life decision-making challenges, which in turn led to the inception of (MCDM). However, MCDM is contracted with various contradictory requirements in which the knowledge of decision-makers is generally vague and thereby more challenging. In this situation, inclusions of fuzzy set theory in MCDM Methods would be good to solve the MCDM problem. In this study, the authors used a fuzzy TOPSIS MCDM model to solve the evaluation framework. Data were collected from the experts from the MSSPF about the more perfect criteria to assess environmental performance using a questionnaire. Case assesses the environmental performance, based on defined criteria, of three MSSPF by the experts. Fuzzy TOPSIS Method ranks three MSSPF according to environmental performance in the following order: Firm B, Firm A and Firm C. The result suggested that 'Firm B' performed superior environmental performance followed by 'Firm A' and 'Firm C'. This evaluation framework will help MSSPF to identify potential areas of further improvement in Environmental performance, and thereby creates strategies to overcome and formulate new innovations. Notably, this is one of the few studies to have used this method to gauge the environmental performance of the medical service supply chain in India. [ABSTRACT FROM AUTHOR]

The growing interest in digitalization signals a need for technology-oriented supply chain operations in the construction industry. Electronic procurement (e-procurement) aims to convert traditional procurement approaches into web-based/online platforms. Even though e-procurement is an effective tool that may improve supply chain management, the extent of e-procurement implementation has been slow to date. This study investigates the barriers that hinder e-procurement implementation in construction supply chains with the aim of prioritizing solutions to the identified barriers relative to time, cost, quality, and construction owner satisfaction. A comprehensive literature survey was performed, and a focus group discussion was organized for the purpose of the study, which resulted in the identification of 28 barriers. Then, a total of 131 construction practitioners were contacted to evaluate the barriers through a questionnaire survey. The responses were analyzed using the fuzzy Technique for Order Preference by Similarities to Ideal Solution (fuzzy TOPSIS) for prioritization. Finally, 15 semi-structured interviews were conducted to gain a deeper insight into the transformation process from the conventional procurement route to the e-procurement solution. Findings highlight that issues related to unexpected order cancellations, large variations in material costs, and the uncertain nature of the industry that requires a large number of changes are ranked as the most significant barriers. Given the highly competitive environment and the high demand for advanced technologies in the construction industry, a new paradigm can enhance the efficiency of supply chain operations. Exploring and eliminating the potential difficulties of adopting e-procurement in the procurement process may be a good start. Overall, this research is expected to facilitate the transformation of the procurement process by addressing the critical barriers identified by practitioners. [ABSTRACT FROM AUTHOR]