Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleYalnız künye2021Scopus SJRQ1Green supplier selection for textile industry: a case study using BWM-TODIM integration under interval type-2 fuzzy sets
Celik, Erkan; Yucesan, Melih; Gul, Muhammet
Although environmental awareness has reached a high level, enterprises—regardless of their working domains—follow the concept of greenness for their practices. This awareness among the stakeholders and supply chain experts has a positive impact on the purchasing departments of enterprises in various sectors to consider greenness in their procurement processes. The critical decision that must be made in green supply chain management (GSCM) is supplier selection. In the textile industry, a highly competitive market in recent years, suppliers for this industry have crucial roles in business activities considering environmental issues. Therefore, green supplier selection (GSS) in the textile industry is considered a must-be process for the stakeholders. In this study, a GSS problem is tackled as a multi-criteria decision process. Best worst method (BWM) and TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) methods are merged under an improved fuzzy concept of interval type-2 fuzzy sets (IT2FSs). In determining green suppliers’ evaluation criteria, BWM with interval type-2 fuzzy numbers (IT2F-BWM) is used. In selecting green suppliers, an interval type-2 fuzzy TODIM (IT2F-TODIM) is applied. Considering the characteristics of IT2FSs, BWM, and TODIM methods either individually and in integrated style, the proposed approach can handle uncertainty in the decision-making of GSS. To demonstrate the applicability of the approach, a case study in the Turkish textile industry is performed. Three green supplier alternatives (S1, S2, and S3) are assessed under forty-two sub-criteria. The study shows the most significant sub-criteria are recognized as dye and print quality, product design and pattern suitability, profit on the product, variation in price, and purchase cost. S2 green supplier has been selected as the most appropriate one. A sensitivity analysis is also fulfilled to check variation in the ranking of green suppliers.
AtıfScopus88WoS72OpenAlex100
İncele - MakaleYalnız künye2021Scopus SJRQ1Systems failure analysis using Z-number theory-based combined compromise solution and full consistency method
Yousefi, Samuel; Valipour, Mahsa; Gul, Muhammet
Financial and time constraints force managers to put limited failure modes in priority to implement corrective and preventive actions. Thus, how prioritization can be done more constructively is of particular importance. This study aims to introduce an improved Failure Modes and Effects Analysis (FMEA) technique based on an extension of the Combined Compromise Solution (CoCoSo) method and the Full Consistency Method (FUCOM) to assess and prioritize failures in a production process. These developed methods called Z-CoCoSo and Z-FUCOM rely on the Z-number theory. They can consider uncertainty and reliability simultaneously in determining the weights of risk factors and the value of these factors in the studied problem. The proposed approach can cover some shortcomings of the conventional FMEA technique employed in identifying potential failures before their occurrence. Applying this approach enables experts to consider different weights for risk factors and uncertainty in the risk assessment process and provides them with a reliable ranking with high separability. Implementing the introduced approach for a real case study in the automotive parts industry has been compared with FMEA and other existent versions of the used methods demonstrating its reliable prioritization.
AtıfScopus57WoS56OpenAlex57İncele - Kitap BölümüYalnız künye2021Fine–kinney occupational risk assessment method and its extensions by fuzzy sets: A state-of-the-art review
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
The Fine–Kinney method (Fine in J Saf Res 3:157–166, 1971; Kinney and Wiruth in Practical risk analysis for safety management. Naval Weapons Center, pp 1–20, 1976), which was first introduced as an occupational health and safety risk analysis tool in the 1970s, is a systematic methodology that provides a mathematical formula for calculating the risk that arises due to a specified hazard. In the traditional version of Fine–Kinney as suggested in its original version, a risk score (RS) is calculated as a result of mathematical multiplication of probability (P), exposure (E), and consequence (C) parameters. These calculated risk scores are used to establish priorities for the corrective efforts in order to eliminate risks or reduce their effects to a reasonable level. This simple and useful method is preferred and implemented by small and medium-sized enterprises. In the academic literature, it has been applied for many risk analysis problems, although it includes several drawbacks recently revealed. In this method, no weight assignment is made for each risk parameter. Also, it is hard to assess consequence, exposure, and probability, precisely. Multi-criteria decision making (MCDM) is a pool of methods used in occupational health and safety risk analysis both by international standard-setting organizations and scholars from the literature. In classical MCDM methods, performance values and weights of decision criteria are known precisely and are specified with crisp numbers. However, many real-world problems contain uncertainties, and the knowledge and judgment of experts cannot be expressed precisely. Fuzzy-based MCDM methods, which are developed to reflect types and degrees of uncertainties better, produce more accurate results compared to classical methods. In this chapter, we first present the basics of Fine–Kinney method, including its implementing procedure, basic terminology, and drawbacks. Then, we provide a state-of-the-art review of Fine–Kinney occupational risk assessment method and its extensions by fuzzy sets. Graphical results obtained from the review are demonstrated to show the current state. Future work suggestions are also included to the chapter to show the possible gaps and possible opportunities.
AtıfScopus12OpenAlex12İncele - MakaleYalnız künye2021Scopus SJRQ1Extension of FEMA and SMUG models with Bayesian best-worst method for disaster risk reduction
Yanilmaz, Sumeyye; Baskak, Dilber; Yucesan, Melih; Gul, Muhammet
Turkey is one of the countries that face many natural and man-made disasters. The entire geography of Turkey is affected by these disasters and the secondary disasters resulting from them. Tunceli is located in the Eastern Anatolia Region of Turkey and is a disaster-prone region. Therefore, it is important to carry out an adaptable hazard analysis for the region and support the national disaster risk reduction struggle. In this study, a comprehensive disaster hazard analysis was conducted for Tunceli province, and potential mitigation measures were discussed. As methodological background, FEMA (Federal Emergency Management Agency) and SMUG (Seriousness Manageability Urgency Growth) models, which are well-known methods, were extended under the Bayesian Best-Worst Method (BWM). Bayesian BWM is a pairwise comparison-based multi-criteria decision-making method that takes a probabilistic view of the experts' group decision without losing information, providing less pairwise comparison and higher consistency. Nine different disaster hazards for the Tunceli region are prioritized by the proposed approach. Initially, weights of the risk parameters in FEMA and SMUG and the priority values of disaster hazards based on each parameter were calculated. Then, ranking orders were determined. In addition, more precise evaluations were made for the results obtained with the credal ranking graphs. Some comparative studies were also included in the study to test the solidity of the approach. According to the results, both models showed that the top priority hazard for Tunceli is “earthquake”. Also, flood, mass movement, terrorism, and epidemics are hazards with higher priority to be taken into account. Considering the final preference values of disaster hazards for Tunceli province, the first three hazards for the FEMA model are earthquake with 0.192, mass movement with 0.141 and flood with 0.114, respectively. In the SMUG model, earthquake with 0.194, flood with 0.129 and epidemic disease with 0.120 are in the first three places.
AtıfScopus35WoS25OpenAlex32İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using interval type-2 fuzzy qualiflex
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
In this chapter, we improved Fine–Kinney occupational risk assessment approach with interval type-2 fuzzy QUALIFLEX (IT2FQUALIFLEX). QUALIFLEX is an outranking multi-attribute decision-making method proposed by an extension of the Paelinck’s (Pap Reg Sci Assoc 36:59–74,[1]), generalized Jacquet-Lagreze’s permutation method. Similar to other outranking solution-based approaches, it considers the solution which is a comparison of hazards. In this chapter, we adapted the interval type-2 fuzzy sets (IT2FSs) into QUALIFLEX as it reflects the uncertainty well in decision-making. IT2FQUALIFLEX algorithm under the Fine–Kinney concept provides a useful and solid approach to the occupational health and safety risk assessment. In addition to proposing this new approach, a case study is performed in the chrome plating unit. A validation is also performed in this study. Finally, the proposed approach is implemented in Python.
AtıfScopus7OpenAlex7İncele - Kitap BölümüYalnız künye2021Fine–kinney-based occupational risk assessment using interval type-2 fuzzy topsis
Gul, Muhammet; Mete, Suleyman; Serin, Faruk; Celik, Erkan
This chapter proposed an improved Fine–Kinney occupational risk assessment approach using a well-known MCDM method “TOPSIS” under interval type-2 fuzzy set concept. It is defined as a technique for order preference by similarity to ideal solution by Hwang and Yoon [1]. It is based on separation from ideal and anti-ideal solution concept. Since the initial crisp data-based version is insufficient by time in reflecting the uncertainty in decision-maker’s opinions, fuzzy sets are integrated to the TOPSIS algorithm to provide a solid and comprehensive method. Interval type-2 fuzzy set is an improved version of the type-1 fuzzy set. It is also a special version of a general type-2 fuzzy set. Since general type-2 fuzzy systems contain complex computational operations, they cannot be easily applied to real-world problems such as occupational risk assessment. Interval type-2 fuzzy sets are the most frequently used type-2 fuzzy sets due to their ability in handling more uncertainty and producing more accurate and solid results. The Fine–Kinney concept is merged with the interval type-2 fuzzy set concept and TOPSIS for the first time through the literature. To demonstrate the applicability of the proposed approach, a case study is carried out in a chrome plating unit of a gun factory. Some beneficial validation and sensitivity analysis are also performed. Finally, as a creative contribution of our book, the implementation of the proposed approach in Python is performed.
AtıfScopus2OpenAlex3İncele - MakaleYalnız künye2020Scopus SJRQ1Assessment of occupational risks from human health and environmental perspectives: a new integrated approach and its application using fuzzy BWM and fuzzy MAIRCA
Gul, Muhammet; Ak, M. Fatih
Occupational safety issues encountered in the worksite environment are the issues that companies should consider in improving their operations with a view to human health and environmental awareness. Many methods with different rationales have been existed in the literature to prioritize hazards according to their risk levels and to mitigate their consequences. In this study, a new model is developed for occupational risk assessment by merging two well-known multi-criteria decision-making methods named best and worst method (BWM) and multi attribute ideal real comparative analysis (MAIRCA) under fuzzy environment. The proposed model differentiates from other similar models by three aspects. First, it considers severity of a hazard and its associated risk from the human and environmental riskiness perspectives. Secondly, it applies fuzzy BWM (F-BWM) to calculate the relative importance of three risk factors named as “probability, frequency and severity” of traditional Fine–Kinney method. Thirdly, it applies fuzzy MAIRCA (F-MAIRCA) to rank hazards according to their risk level using importance values obtained by F-BWM. To show applicability of the approach, a case study of risk assessment in a marble factory is fulfilled. Additionally, a number of validation studies including benchmarking analysis with fuzzy VIKOR and fuzzy TOPSIS methods; a sensitivity analysis by varying importance weights of risk factors are carried out to highlight the solidity of the proposed approach.
AtıfScopus80WoS70İncele - MakaleAçık Erişim2020Scopus SJRQ1Evaluation of hospital disaster preparedness by a multi-criteria decision making approach: The case of Turkish hospitals
Ortiz-Barrios, Miguel; Gul, Muhammet; López-Meza, Pedro; Yucesan, Melih; Navarro-Jiménez, Eduardo
Considering the unexpected emergence of natural and man-made disasters over the world and Turkey, the importance of preparedness of hospitals, which are the first reference points for people to get healthcare services, becomes clear. Determining the level of disaster preparedness of hospitals is an important and necessary issue. This is because identifying hospitals with low level of preparedness is crucial for disaster preparedness planning. In this study, a hybrid fuzzy decision making model was proposed to evaluate the disaster preparedness of hospitals. This model was developed using fuzzy analytic hierarchy process (FAHP)-fuzzy decision making trial and evaluation laboratory (FDEMATEL)-technique for order preference by similarity to ideal solutions (TOPSIS) techniques and aimed to determine a ranking for hospital disaster preparedness. FAHP is used to determine weights of six main criteria (including hospital buildings, equipment, communication, transportation, personnel, flexibility) and a total of thirty-six sub-criteria regarding disaster preparedness. At the same time, FDEMATEL is applied to uncover the interdependence between criteria and sub-criteria. Finally, TOPSIS is used to obtain ranking of hospitals. To provide inputs for TOPSIS implementation, some key performance indicators are established and related data is gathered by the aid of experts from the assessed hospitals. A case study considering 4 hospitals from the Turkish healthcare sector was used to demonstrate the proposed approach. The results evidenced that Personnel is the most important factor (global weight = 0.280) when evaluating the hospital preparedness while Flexibility has the greatest prominence (c + r = 23.09).
AtıfScopus87WoS69OpenAlex97İncele - KitapYalnız künye2020Computational intelligence and soft computing applications in healthcare management science
Gul, Muhammet; Celik, Erkan; Mete, Suleyman; Serin, Faruk
In today's modernized world, the field of healthcare has seen significant practical innovations with the implementation of computational intelligence approaches and soft computing methods. These two concepts present various solutions to complex scientific problems and imperfect data issues. This has made both very popular in the medical profession. There are still various areas to be studied and improved by these two schemes as healthcare practices continue to develop.
AtıfOpenAlex7İncele - EditoryalYalnız künye2020Preface
Gul, Muhammet; Celik, Erkan; Mete, Suleyman; Serin, Faruk
AtıfScopus1İncele - MakaleYalnız künye2020Scopus SJRQ1A manufacturing failure mode and effect analysis based on fuzzy and probabilistic risk analysis
Gul, Muhammet; Yucesan, Melih; Celik, Erkan
This study proposes an improved failure mode and effect analysis (FMEA) with fuzzy Bayesian Network (FBN) and fuzzy best-worst method (FBWM) to assess failures in plastic production. To eliminate the drawbacks of the classical risk priority number (RPN) computation of FMEA, this approach is developed. Unlike classical RPN, a new parameter hierarchy is constructed, and three sub-parameters are injected into the approach. These parameters are weighted by the aid of FBWM. Hereafter, a fuzzy rule-based system is constructed by incorporating Bayesian Network (BN). Also, a sensitivity analysis is performed to observe the final FMEA score changes in accordance with the change of subjective probability values. Finally, a comparative analysis with two approaches of classical FMEA and FBWM-based FMEA (without a fuzzy rule-based system incorporating BN) is fulfilled. The results of the study are strengthened with the experts’ opinions regarding the importance of failure modes for the final product and the whole system and supported them by experience feedback in the observed facility.
AtıfScopus68WoS59OpenAlex68İncele - MakaleYalnız künye2020Scopus SJRQ1Emergency department network under disaster conditions: The case of possible major Istanbul earthquake
Gul, Muhammet; Fuat Guneri, Ali; Gunal, Murat M.
Emergency departments (EDs) provide health care services to people in need of urgent care. Their role is remarkable when extraordinary events that affect the public, such as earthquakes, occur. In this paper, we present a hybrid framework to evaluate earthquake preparedness of EDs in cities. Our hybrid framework uses artificial neural networks (ANNs) to estimate number of casualties and discrete event simulation (DES) to analyse the effect of surge in patient demand in EDs, after an earthquake happens. At the core of our framework, Earthquake Time Emergency Department Network Simulation Model (ET-EDNETSIM) resides which can simulate patient movements in a network of multiple and coordinated EDs. With the design of simulation experiments, different resource levels and sharing rules between EDs can be evaluated. We demonstrated our framework in a network of five EDs located in a region of which is estimated to have the highest injury rate after an earthquake in Istanbul, Turkey. Results of our study contributed to the planning for expected earthquake in Istanbul. Simulating a network of EDs extends the individual ED studies in the literature and furthermore, our hybrid framework can help increase earthquake preparedness in cities around the world. On the methodological side, the use of ANN, which is a member of machine learning (ML) algorithms family, in our hybrid framework also shows the close links between ML and DES.
AtıfScopus30WoS31OpenAlex40İncele - MakaleYalnız künye2020Scopus SJRQ2Application of Pythagorean fuzzy AHP and VIKOR methods in occupational health and safety risk assessment: the case of a gun and rifle barrel external surface oxidation and colouring unit
Gul, Muhammet
The field of occupational health and safety (OHS) focuses on reducing occupational accidents to an acceptable level. OHS covers systematic efforts aimed at providing employee health, safety and welfare in the workplace. This study proposes a new approach for risk assessment in the field of OHS. It integrates the Pythagorean fuzzy analytic hierarchy process (PFAHP) and fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (FVIKOR) into a risk assessment process. The PFAHP is used in weighting the risk parameters. FVIKOR is then applied to prioritize the hazards. To demonstrate the applicability and validity of the proposed approach, a case study of a barrel external surface oxidation and colouring unit of a gun and rifle production facility is performed. A comparison is also provided between the proposed approach and an intuitionistic fuzzy sets-based approach. The proposed approach is found to produce reliable outcomes that better represent the vagueness of the decision-making process.
AtıfScopus99WoS100OpenAlex133İncele - MakaleAçık Erişim2020Scopus SJRQ2A novel risk evaluation approach for frequently encountered risks in ship engine rooms
Başhan, Veysi; Demirel, Hakan; Gul, Muhammet
The purpose of this study is to evaluate risks which are frequently encountered in the engine room on-board. In this context, twenty common risks are assessed using the neutrosophic analytic hierarchy process (N-AHP) and trapezoidal fuzzy technique for order preference by similarity to ideal solution (TrF-TOPSIS). In maritime risk evaluation, since it is frequently required the linguistic assessment of decision-makers to achieve a robust risk assessment tool, neutrosophic sets and fuzzy sets are used together in this study. Neutrosophic sets represent real-world problems effectively by considering all aspects of decision-making situations, (i.e. truthiness, indeterminacy, and falsity). Therefore, AHP is integrated with neutrosophic sets to assign weights of risk parameters initially. Then, the encountered risks are prioritized by TrF-TOPSIS. Finally, preventative actions for the risks have been discussed. In conclusion of the study, it is shown that skin exposure to the fuels/oils, exposure to chemicals and exposure to high pressure and temperature liquids are the most important risks through the engine room on-board. This study both emphasizes the importance of preventing damage to crew in the risk assessment of ship engine rooms and aims to increase the level of safety control and minimize the potential environmental impacts of a ship's damage.
AtıfScopus17WoS13OpenAlex14İncele - Kitap BölümüYalnız künye2020NARX neural networks model for forecasting daily patient arrivals in the Emergency Department
Yucesan, Melih; Mete, Suleyman; Serin, Faruk; Celik, Erkan; Gul, Muhammet
Regarding measuring of service quality at the emergency departments (ED), essential parameters are length of stay (LOS) and waiting times. Patient arrivals, which is related to LOS and waiting times, is hard to forecast and is affected by many parameters. Therefore, authors employed a Nonlinear Autoregressive Exogenous (NARX) model for forecasting of ED arrivals. NARX models are used extensively in many applications that show non-linear and dynamic behavior, but as far as authors know, the NARX method has not yet been used in the forecast of ED arrivals before. In this study, calendar and climatic variables are defined as input parameters. Patient Arrivals is defined as output parameter. A commercial software, MATLAB, was used to train and test the data set. To find the best network architecture Levenberg- Marquardt (LM) and Bayesian Regularization (BR) algorithms, different lags, and number of neurons were tested. R-squared and mean square error (MSE) are used to evaluate the accuracy of the tested networks.
AtıfScopus2OpenAlex4İncele - Kitap BölümüYalnız künye2020A fuzzy decision-making model for the key performance indicators of hospital service quality evaluation
Yucesan, Melih; Mete, Suleyman; Gul, Muhammet; Celik, Erkan
One of the major concerns of the healthcare industry throughout the world is to provide better hospital service quality. Management and delivery of hospital healthcare services are achieved in a competitive environment in Turkey. For this reason, to make better decisions, the services provided by the public and private hospitals should be monitored and evaluated according to the viewpoint of medical stakeholders. This chapter presents a cause-and-effect, decision-making model in evaluating hospital service quality criteria. Since the decision-making process involves the vagueness of human judgments, a combination of fuzzy sets and decisionmaking trial and evaluation laboratory (DEMATEL) is used. Results of the study demonstrate that medical equipment level of the hospital, the attitude of nurses and medical staff to patients, pharmacists' advice on medicine preservation, medical staff with professional abilities, outpatient waiting time for medical treatment, and number and quality of the bathrooms available have more impact on the entire hospital service quality. In conclusion, the proposed approach will contribute to better providing of healthcare services at a higher quality level.
AtıfScopus5OpenAlex5İncele - MakaleYalnız künye2020Scopus SJRQ2Hospital service quality evaluation: an integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS
Yucesan, Melih; Gul, Muhammet
Providing better hospital service quality is one of the major concerns of healthcare industry in the world. Since health services in Turkey are provided in a very competitive environment, for making a better choice, the services delivered by the public and private hospitals should be evaluated according to the viewpoint of stakeholders in terms of satisfaction. In this study, a model proposal is presented based on the concept of Pythagorean fuzzy analytic hierarchy process and Pythagorean fuzzy technique for order preference by similarity to ideal solution method to provide an accurate decision-making process for evaluating the hospital service quality. We study under fuzzy environment to reduce uncertainty and vagueness, and use linguistic variables parameterized by Pythagorean fuzzy numbers. The proposed approach is separated from others with the integration of the methods in a way providing a systematic fuzzy decision-making process. A case study including 32 service quality criteria and two public and one private hospitals in Turkey assessed by 32 evaluators by medical staff, hospital executives, auxiliaries, and patients is performed to demonstrate the applicability and validity of the proposed approach. On conclusion, integrated model produces reliable and suggestive outcomes better representing the vagueness of decision-making process.
AtıfScopus164WoS132OpenAlex190İncele - MakaleYalnız künye2020Scopus SJRQ4Development and application of a novel hybrid occupational risk assessment model
Gul, Muhammet
Occupational Risk Assessment (ORA) is so crucial for safety management in the weapons industry since numerous hazards may lead to human casualties. Therefore, occupational health and safety stakeholders suggest proactive approaches in reducing risks to an acceptable level. Therefore, this paper aims to develop a novel hybrid ORA model for the weapons industry. The approach merges TODIM with Fine-Kinney concept. Risk parameters used in traditional Fine-Kinney method are weighted by Fuzzy Analytic Hierarchy Process (FAHP). Then, hazards and associated risks are prioritised using the approach. As an illustration, the gun and rifle assembly line of a weapon factory is handled. The application is carried out to improve operational safety and protect employee health. From both theoretical and practice aspects, it contributes to the literature by handling the problem in an integrated style of Fine-Kinney, FAHP and TODIM and by improving overall safety level of the observed factory and by suggesting potential action plans.
AtıfScopus4İncele - MakaleYalnız künye2020Scopus SJRQ2An FMEA-based TOPSIS approach under single valued neutrosophic sets for maritime risk evaluation: the case of ship navigation safety
Başhan, Veysi; Demirel, Hakan; Gul, Muhammet
As in terrestrial facilities, safety is one of the most important issue in ships. Vessels navigating in many parts of the world face many different, tough and dangerous navigational risks. In this context, twenty-three fundamental risks which are frequently encountered in ship navigation were considered in this study and examined by an FMEA-based TOPSIS approach under single valued neutrosophic sets. Because of the lack of data in the literature, the opinions of the experts (Masters) who have many years of experience in the sector were taken. As a result of the study, extreme weather conditions, injury of crew, loss of input of sensory equipment (depth, gyro, speed etc.), struck by ropes, exposure to high speed machineries under high pressures, loss of maneuverability are very important among these risks. Considering these risks, corrective-preventive action plans and managerial implications for ship navigation have been presented. Consequently, the results of this study have an important warning and solution recommendation regarding ship navigation risks.
AtıfScopus123WoS96OpenAlex113İncele - MakaleAçık Erişim2020Scopus SJRQ2An integrated approach of best-worst method (bwm) and triangular fuzzy sets for evaluating driver behavior factors related to road safety
Moslem, Sarbast; Gul, Muhammet; Farooq, Danish; Celik, Erkan; Ghorbanzadeh, Omid; Blaschke, Thomas
Driver behavior plays a major role in road safety because it is considered as a significant argument in traffic accident avoidance. Drivers mostly face various risky driving factors which lead to fatal accidents or serious injury. This study aims to evaluate and prioritize the significant driver behavior factors related to road safety. In this regard, we integrated a decision-making model of the Best-Worst Method (BWM) with the triangular fuzzy sets as a solution for optimizing our complex decision-making problem, which is associated with uncertainty and ambiguity. Driving characteristics are different in different driving situations which indicate the ambiguous and complex attitude of individuals, and decision-makers (DMs) need to improve the reliability of the decision. Since the crisp values of factors may be inadequate to model the real-world problem considering the vagueness and the ambiguity, and providing the pairwise comparisons with the requirement of less compared data, the BWM integrated with triangular fuzzy sets is used in the study to evaluate risky driver behavior factors for a designed three-level hierarchical structure. The model results provide the most significant driver behavior factors that influence road safety for each level based on evaluator responses on the Driver Behavior Questionnaire (DBQ). Moreover, the model generates a more consistent decision process by the new consistency ratio of F-BWM. An adaptable application process from the model is also generated for future attempts.
AtıfScopus96WoS83OpenAlex93İncele