In international trade,exporters prefer to receive payments as quickly as possible,and importers want to make payments as late as possible.In this respect,the payment field,an essential condition for trade transaction...In international trade,exporters prefer to receive payments as quickly as possible,and importers want to make payments as late as possible.In this respect,the payment field,an essential condition for trade transactions,also represents the positions of exporters and importers conflict.In addition,there are many cases in which various variables must be considered rather than only one specific variable representatively affecting payment,particularly in the case of import-export Small and Medium-Sized Enterprises(SMEs)from emerging countries.A selection of proper payment methods can be categorized as a Multi-Criteria Decision-Making(MCDM)issue.Therefore,this study aims to propose a novel and efficient Spherical Fuzzy Weighted Aggregated Sum Product Assessment based Entropy Objective Weighting method(SF-EW and WASPAS-SF)to evaluate international payment methods with uncertain information.First,SF-EW model is applied to determine the relative weights of critical factors.Second,international payment method alternatives are prioritized by the WASPAS-SF approach.Five essential factors for four international payment methods are proposed based on experts’opinions and the existing literature.A real-world case study from Vietnamese import-export SMEs is presented to validate the applicability of the proposed framework.The results indicated that“Characteristics of payment method(PA)”had the most significant impact on international payment method selection.In comparison,“Letters of Credit(L/C)”was the most reliable payment method with the highest ranking available to international traders.Furthermore,a sensitivity analysis was performed to examine the validity and robustness of the proposed decision support model.Consequently,this study could contribute to international payment services and in the context of globalization and international trade.展开更多
Purpose-This research focuses on a very important research question of determining the appropriate feature selection methods for software defect prediction.The study is centered on the creation of a new method that wo...Purpose-This research focuses on a very important research question of determining the appropriate feature selection methods for software defect prediction.The study is centered on the creation of a new method that would enable the identification of both positive and negative selection criteria and the handling of ambiguous information in the decision-making process.Design/methodology/approach-To do so,we develop an improved method by extending the WASPAS assessment in the context of bipolar complex fuzzy sets,which leads to the bipolar complex fuzzy WASPAS method.The approach also uses Einstein operators to increase the accuracy of aggregation and manage complicated decision-making parameters.The methodology is designed for the processing of multi-criteria decision-making problems where criteria have positive and negative polarities as well as other ambiguous information.Findings-It is also shown that the proposed methodology outperforms the traditional weighted sum or product models when assessing feature selection methods.The incorporation of bipolar complex fuzzy sets with WASPAS improves the assessment of selection criteria by taking into account both positive and negative aspects of the criteria,which contributes to more accurate feature selection for software defect prediction.We investigate a case study related to the identification of feature selection techniques for software defect prediction by using the bipolar complex fuzzy WASPAS methodology.We compare the proposed methodology with certain prevailing ones to reveal the supremacy and the requirements of the proposed theory.Originality/value-This research offers the first integrated framework for handling bipolarity and uncertainty in feature selection for software defect prediction.The combination of Einstein operators with bipolar complex fuzzy sets improves the DM process,which will be useful for software engineers and help them select the best feature selection techniques.This work also helps to enhance the overall performance of software defect prediction systems.展开更多
With the rapid growth of urbanization,smart city development has become a strategic priority worldwide,requiring complex and uncertain decision-making processes.In this context,advanced decision-support tools are esse...With the rapid growth of urbanization,smart city development has become a strategic priority worldwide,requiring complex and uncertain decision-making processes.In this context,advanced decision-support tools are essential to evaluate and prioritize competing initiatives effectively.To support effective prioritization of smart city initiatives under uncertainty,this study introduces a robust decision-making framework based on the t-arbicular fuzzy(t-AF)set—a recent extension of the t-spherical fuzzy set that incorporates an additional parameter,the radius r,to enhance the representation of uncertainty.Dombi-based operational laws are formulated within this context,leading to the development of four power aggregation operators that integrate a support degree to reflect inter-attribute relationships.The structural and theoretical foundations of the operators are rigorously demonstrated.Further,the proposed operators are embedded into an extended weighted aggregated sum product assessment(WASPAS)method to create a comprehensive multi-criteria decision-making model.The practical utility of the proposed approach is demonstrated through a case study involving the evaluation of seven smart city initiatives against eight critical criteria.Comparative analysis against establishedmodels reveals that the proposed approach offers superior ranking consistency,enhanced discrimination power among alternatives,and improved handling of uncertainty—ultimately supporting more reliable and interpretable decision-making outcomes.展开更多
Supplier selection is a vital part of the supply chain and is also a current issue that concerns businesses today as supplier quality directly affects the operations of the organization.Choosing the right supplier can...Supplier selection is a vital part of the supply chain and is also a current issue that concerns businesses today as supplier quality directly affects the operations of the organization.Choosing the right supplier can help businesses increase productivity,competitiveness in the market,and profits without having to lower the quality of the products.However,choosing a supplier is not a simple matter,it requires businesses to consider many aspects about their suppliers.Therefore,the goal of this study is to propose an integrated model consisting of two models:Fuzzy Analytics Network Process(Fuzzy-ANP)model and Weighted Aggregated Sum Product Assessment(WASPAS)to solve the problem above.The Fuzzy-ANP model was developed to evaluate the weightings of the supplier selection criteria,and the WASPAS Model was used to rank the suppliers.An example of supplier selection in the coffee industry in Vietnam was studied to validate the model,namely 5 main criteria,with 16 sub-criteria,and 7 suppliers.The model test results show that the Fuzzy ANP and WASPAS integration model was suitable.In future,these developing models can apply to other industries or integrate with other models.展开更多
The two main approaches that countries are using to ease the strain on healthcare infrastructure is building temporary hospitals that are specialized in treating COVID-19 patients and promoting preventive measures.As ...The two main approaches that countries are using to ease the strain on healthcare infrastructure is building temporary hospitals that are specialized in treating COVID-19 patients and promoting preventive measures.As such,the selection of the optimal location for a temporary hospital and the calculation of the prioritization of preventive measures are two of the most critical decisions during the pandemic,especially in densely populated areas where the risk of transmission of the virus is highest.If the location selection process or the prioritization of measures is poor,healthcare workers and patients can be harmed,and unnecessary costs may come into play.In this study,a decision support framework using a fuzzy analytic hierarchy process(FAHP)and a weighted aggregated sum product assessment model are proposed for selecting the location of a temporary hospital,and a FAHP model is proposed for calculating the prioritization of preventive measures against COVID-19.A case study is performed for Ho Chi Minh City using the proposed decision-making framework.The contribution of this work is to propose a multiple criteria decision-making model in a fuzzy environment for ranking potential locations for building temporary hospitals during the COVID-19 pandemic.The results of the study can be used to assist decisionmakers,such as government authorities and infectious disease experts,in dealing with the current pandemic as well as other diseases in the future.With the entire world facing the global pandemic of COVID-19,many scientists have applied research achievements in practice to help decision-makers make accurate decisions to prevent the pandemic.As the number of cases increases exponentially,it is crucial that government authorities and infectious disease experts make optimal decisions while considering multiple quantitative and qualitative criteria.As such,the proposed approach can also be applied to support complex decision-making processes in a fuzzy environment in different countries.展开更多
Regulatory authorities create a lot of legislation that must be followed.These create complex compliance requirements and time-consuming processes to find regulatory non-compliance.While the regulations establish rule...Regulatory authorities create a lot of legislation that must be followed.These create complex compliance requirements and time-consuming processes to find regulatory non-compliance.While the regulations establish rules in the relevant areas,recommendations and best practices for compliance are not generally mentioned.Best practices are often used to find a solution to this problem.There are numerous governance,management,and security frameworks in Information Technology(IT)area to guide businesses to run their processes at a much more mature level.Best practice maps can used to map another best practice,and users can adapt themselves by the help of this relation maps.These maps are created generally by an expert judgment or topdown relationship analysis.These methods are subjective and easily creates inconsistencies.In order to have an objective and statistical relationships map,we propose a Latent Semantic Analysis(LSA)based modal to generate a specific relatedness correlation map.We created a relatedness map of a banking regulation to a best practice.We analyzed 224 statements of this regulation in relation to Control Objectives for Information Technologies(Cobit)2019’s 1202 activities.Furthermore,we support our LSA results with MCDM analysis methods;Fuzzy Analytics Hierarchy Process(FAHP)to prioritize our criteria and,WASPAS(Weighted Aggregated Sum Product Assessment Method)to compare similarity results of regulation and Cobit activity pairs.Instead of the subjective methods for mapping best practices and regulations,this study suggests creating relatedness maps supported by the objectivity of LSA.展开更多
Healthcare supply chains are under pressure to drive down costs because of digital business,shifting customer needs and new competition.Medical waste generated from medical facilities includes medical activities and d...Healthcare supply chains are under pressure to drive down costs because of digital business,shifting customer needs and new competition.Medical waste generated from medical facilities includes medical activities and daily-life activities of patients and their family members.According to statistics of the Department of Health EnvironmentalManagement,Vietnam currently has more than 13,500 medical facilities,including hospitals from central to provincial and district levels and private hospitals and medical facilities.Preventive medicine generates about 590 tons of medical waste/day and is estimated to be about 800 tons/day.Medical waste includes ordinary medical waste and hazardous medical waste;in which ordinary medical waste accounts for about 80%–90%,only about 10%–20%is hazardous medical waste including infectious waste and non-infectious hazardous waste.This is an environmental and occupational health issue that needs attention in developing countries like Vietnam.Handling large amounts of medical waste to ensure environmental and personal hygiene,doing so inefficiently creates potential hazards to the environment and increases operating costs.However,hospitals lack objective criteria and methods to evaluate and select the most optimal infectious medical waste,relying instead on their own subjective assessment and prior experience.Therefore,the author proposed a fuzzy multicriteria decision making(MCDM)model including Fuzzy Analytic hierarchy process(FAHP)and the Weighted Aggregated Sum-Product Assessment(WASPAS)for infectious medical waste contractors’selection in this research.The proposed Fuzzy MCDM method is in-tended to provide a more efficient,accurate method in the selection of infectious medical waste contractors than subjective assessment methods,thus reduce potential risks to hospitals.The results of this study can be applied to evaluate and select contractors in other industries.展开更多
In South Asia,Pakistan has a long and deadly history of floods that cause losses to various infrastructures,lives,and industries.This study aims to identify the most appropriate flood risk mitigation strategies that t...In South Asia,Pakistan has a long and deadly history of floods that cause losses to various infrastructures,lives,and industries.This study aims to identify the most appropriate flood risk mitigation strategies that the government of Pakistan should adopt.The assessment of flood risk mitigation strategies in this study is based on certain criteria,which are analyzed using the fuzzy full consistency method.Moreover,flood risk mitigation strategies are evaluated by using the fuzzy weighted aggregated sum product assessment(WASPAS)method,considering previously prioritized criteria.According to the results,lack of governance,lack of funding and resources,and lack of flood control infrastructure are the most significant flood intensifying factors and act as major criteria for assessing flood risk mitigation strategies in Pakistan.Adopting hard engineering strategies(e.g.,dams,reservoirs,river straightening and dredging,embankments,and flood relief channels),maintaining existing infrastructure,and adopting soft engineering strategies(flood plain zoning,comprehensive flood risk assessment,and sophisticated flood modeling)are identified as the top three flood risk mitigation strategies by the fuzzy WASPAS method.The highest weight(0.98)was assigned to the adoption of hard engineering strategies to mitigate flood risks.The study introduces a novel dimension by analyzing the real-time impact of the unprecedented 2022 floods,during which approximately one-third of the nation was submerged.This focus on a recent and highly significant event enhances the study’s relevance and contributes a unique perspective to the existing literature on flood risk management.The study recommends that the government of Pakistan should prioritize hard engineering strategies for effective flood risk mitigation.It also recommends that the government should incorporate these strategies in the national policy framework to reduce flood losses in the future.展开更多
文摘In international trade,exporters prefer to receive payments as quickly as possible,and importers want to make payments as late as possible.In this respect,the payment field,an essential condition for trade transactions,also represents the positions of exporters and importers conflict.In addition,there are many cases in which various variables must be considered rather than only one specific variable representatively affecting payment,particularly in the case of import-export Small and Medium-Sized Enterprises(SMEs)from emerging countries.A selection of proper payment methods can be categorized as a Multi-Criteria Decision-Making(MCDM)issue.Therefore,this study aims to propose a novel and efficient Spherical Fuzzy Weighted Aggregated Sum Product Assessment based Entropy Objective Weighting method(SF-EW and WASPAS-SF)to evaluate international payment methods with uncertain information.First,SF-EW model is applied to determine the relative weights of critical factors.Second,international payment method alternatives are prioritized by the WASPAS-SF approach.Five essential factors for four international payment methods are proposed based on experts’opinions and the existing literature.A real-world case study from Vietnamese import-export SMEs is presented to validate the applicability of the proposed framework.The results indicated that“Characteristics of payment method(PA)”had the most significant impact on international payment method selection.In comparison,“Letters of Credit(L/C)”was the most reliable payment method with the highest ranking available to international traders.Furthermore,a sensitivity analysis was performed to examine the validity and robustness of the proposed decision support model.Consequently,this study could contribute to international payment services and in the context of globalization and international trade.
文摘Purpose-This research focuses on a very important research question of determining the appropriate feature selection methods for software defect prediction.The study is centered on the creation of a new method that would enable the identification of both positive and negative selection criteria and the handling of ambiguous information in the decision-making process.Design/methodology/approach-To do so,we develop an improved method by extending the WASPAS assessment in the context of bipolar complex fuzzy sets,which leads to the bipolar complex fuzzy WASPAS method.The approach also uses Einstein operators to increase the accuracy of aggregation and manage complicated decision-making parameters.The methodology is designed for the processing of multi-criteria decision-making problems where criteria have positive and negative polarities as well as other ambiguous information.Findings-It is also shown that the proposed methodology outperforms the traditional weighted sum or product models when assessing feature selection methods.The incorporation of bipolar complex fuzzy sets with WASPAS improves the assessment of selection criteria by taking into account both positive and negative aspects of the criteria,which contributes to more accurate feature selection for software defect prediction.We investigate a case study related to the identification of feature selection techniques for software defect prediction by using the bipolar complex fuzzy WASPAS methodology.We compare the proposed methodology with certain prevailing ones to reveal the supremacy and the requirements of the proposed theory.Originality/value-This research offers the first integrated framework for handling bipolarity and uncertainty in feature selection for software defect prediction.The combination of Einstein operators with bipolar complex fuzzy sets improves the DM process,which will be useful for software engineers and help them select the best feature selection techniques.This work also helps to enhance the overall performance of software defect prediction systems.
文摘With the rapid growth of urbanization,smart city development has become a strategic priority worldwide,requiring complex and uncertain decision-making processes.In this context,advanced decision-support tools are essential to evaluate and prioritize competing initiatives effectively.To support effective prioritization of smart city initiatives under uncertainty,this study introduces a robust decision-making framework based on the t-arbicular fuzzy(t-AF)set—a recent extension of the t-spherical fuzzy set that incorporates an additional parameter,the radius r,to enhance the representation of uncertainty.Dombi-based operational laws are formulated within this context,leading to the development of four power aggregation operators that integrate a support degree to reflect inter-attribute relationships.The structural and theoretical foundations of the operators are rigorously demonstrated.Further,the proposed operators are embedded into an extended weighted aggregated sum product assessment(WASPAS)method to create a comprehensive multi-criteria decision-making model.The practical utility of the proposed approach is demonstrated through a case study involving the evaluation of seven smart city initiatives against eight critical criteria.Comparative analysis against establishedmodels reveals that the proposed approach offers superior ranking consistency,enhanced discrimination power among alternatives,and improved handling of uncertainty—ultimately supporting more reliable and interpretable decision-making outcomes.
基金supported by Van Lang University,Vietnam and National Kaohsiung University of Science and Technology,Taiwan.
文摘Supplier selection is a vital part of the supply chain and is also a current issue that concerns businesses today as supplier quality directly affects the operations of the organization.Choosing the right supplier can help businesses increase productivity,competitiveness in the market,and profits without having to lower the quality of the products.However,choosing a supplier is not a simple matter,it requires businesses to consider many aspects about their suppliers.Therefore,the goal of this study is to propose an integrated model consisting of two models:Fuzzy Analytics Network Process(Fuzzy-ANP)model and Weighted Aggregated Sum Product Assessment(WASPAS)to solve the problem above.The Fuzzy-ANP model was developed to evaluate the weightings of the supplier selection criteria,and the WASPAS Model was used to rank the suppliers.An example of supplier selection in the coffee industry in Vietnam was studied to validate the model,namely 5 main criteria,with 16 sub-criteria,and 7 suppliers.The model test results show that the Fuzzy ANP and WASPAS integration model was suitable.In future,these developing models can apply to other industries or integrate with other models.
文摘The two main approaches that countries are using to ease the strain on healthcare infrastructure is building temporary hospitals that are specialized in treating COVID-19 patients and promoting preventive measures.As such,the selection of the optimal location for a temporary hospital and the calculation of the prioritization of preventive measures are two of the most critical decisions during the pandemic,especially in densely populated areas where the risk of transmission of the virus is highest.If the location selection process or the prioritization of measures is poor,healthcare workers and patients can be harmed,and unnecessary costs may come into play.In this study,a decision support framework using a fuzzy analytic hierarchy process(FAHP)and a weighted aggregated sum product assessment model are proposed for selecting the location of a temporary hospital,and a FAHP model is proposed for calculating the prioritization of preventive measures against COVID-19.A case study is performed for Ho Chi Minh City using the proposed decision-making framework.The contribution of this work is to propose a multiple criteria decision-making model in a fuzzy environment for ranking potential locations for building temporary hospitals during the COVID-19 pandemic.The results of the study can be used to assist decisionmakers,such as government authorities and infectious disease experts,in dealing with the current pandemic as well as other diseases in the future.With the entire world facing the global pandemic of COVID-19,many scientists have applied research achievements in practice to help decision-makers make accurate decisions to prevent the pandemic.As the number of cases increases exponentially,it is crucial that government authorities and infectious disease experts make optimal decisions while considering multiple quantitative and qualitative criteria.As such,the proposed approach can also be applied to support complex decision-making processes in a fuzzy environment in different countries.
文摘Regulatory authorities create a lot of legislation that must be followed.These create complex compliance requirements and time-consuming processes to find regulatory non-compliance.While the regulations establish rules in the relevant areas,recommendations and best practices for compliance are not generally mentioned.Best practices are often used to find a solution to this problem.There are numerous governance,management,and security frameworks in Information Technology(IT)area to guide businesses to run their processes at a much more mature level.Best practice maps can used to map another best practice,and users can adapt themselves by the help of this relation maps.These maps are created generally by an expert judgment or topdown relationship analysis.These methods are subjective and easily creates inconsistencies.In order to have an objective and statistical relationships map,we propose a Latent Semantic Analysis(LSA)based modal to generate a specific relatedness correlation map.We created a relatedness map of a banking regulation to a best practice.We analyzed 224 statements of this regulation in relation to Control Objectives for Information Technologies(Cobit)2019’s 1202 activities.Furthermore,we support our LSA results with MCDM analysis methods;Fuzzy Analytics Hierarchy Process(FAHP)to prioritize our criteria and,WASPAS(Weighted Aggregated Sum Product Assessment Method)to compare similarity results of regulation and Cobit activity pairs.Instead of the subjective methods for mapping best practices and regulations,this study suggests creating relatedness maps supported by the objectivity of LSA.
文摘Healthcare supply chains are under pressure to drive down costs because of digital business,shifting customer needs and new competition.Medical waste generated from medical facilities includes medical activities and daily-life activities of patients and their family members.According to statistics of the Department of Health EnvironmentalManagement,Vietnam currently has more than 13,500 medical facilities,including hospitals from central to provincial and district levels and private hospitals and medical facilities.Preventive medicine generates about 590 tons of medical waste/day and is estimated to be about 800 tons/day.Medical waste includes ordinary medical waste and hazardous medical waste;in which ordinary medical waste accounts for about 80%–90%,only about 10%–20%is hazardous medical waste including infectious waste and non-infectious hazardous waste.This is an environmental and occupational health issue that needs attention in developing countries like Vietnam.Handling large amounts of medical waste to ensure environmental and personal hygiene,doing so inefficiently creates potential hazards to the environment and increases operating costs.However,hospitals lack objective criteria and methods to evaluate and select the most optimal infectious medical waste,relying instead on their own subjective assessment and prior experience.Therefore,the author proposed a fuzzy multicriteria decision making(MCDM)model including Fuzzy Analytic hierarchy process(FAHP)and the Weighted Aggregated Sum-Product Assessment(WASPAS)for infectious medical waste contractors’selection in this research.The proposed Fuzzy MCDM method is in-tended to provide a more efficient,accurate method in the selection of infectious medical waste contractors than subjective assessment methods,thus reduce potential risks to hospitals.The results of this study can be applied to evaluate and select contractors in other industries.
文摘In South Asia,Pakistan has a long and deadly history of floods that cause losses to various infrastructures,lives,and industries.This study aims to identify the most appropriate flood risk mitigation strategies that the government of Pakistan should adopt.The assessment of flood risk mitigation strategies in this study is based on certain criteria,which are analyzed using the fuzzy full consistency method.Moreover,flood risk mitigation strategies are evaluated by using the fuzzy weighted aggregated sum product assessment(WASPAS)method,considering previously prioritized criteria.According to the results,lack of governance,lack of funding and resources,and lack of flood control infrastructure are the most significant flood intensifying factors and act as major criteria for assessing flood risk mitigation strategies in Pakistan.Adopting hard engineering strategies(e.g.,dams,reservoirs,river straightening and dredging,embankments,and flood relief channels),maintaining existing infrastructure,and adopting soft engineering strategies(flood plain zoning,comprehensive flood risk assessment,and sophisticated flood modeling)are identified as the top three flood risk mitigation strategies by the fuzzy WASPAS method.The highest weight(0.98)was assigned to the adoption of hard engineering strategies to mitigate flood risks.The study introduces a novel dimension by analyzing the real-time impact of the unprecedented 2022 floods,during which approximately one-third of the nation was submerged.This focus on a recent and highly significant event enhances the study’s relevance and contributes a unique perspective to the existing literature on flood risk management.The study recommends that the government of Pakistan should prioritize hard engineering strategies for effective flood risk mitigation.It also recommends that the government should incorporate these strategies in the national policy framework to reduce flood losses in the future.
