With the development of central-private enterprises integration,selecting suitable key suppliers are able to provide core components for smart complex equipment.We consider selecting suitable key suppliers from matchi...With the development of central-private enterprises integration,selecting suitable key suppliers are able to provide core components for smart complex equipment.We consider selecting suitable key suppliers from matching perspective,for it not only satisfies natural development of smart complex equipment,it is also a good implementation of equipment project in central-private enterprises integration context.In in this paper,we carry out two parts of research,one is evaluation attributes based on comprehensive analysis,and the other is matching process between key suppliers and core components based on the matching attribute.In practical analysis process,we employ comprehensive evaluated analysis methods to acquire relevant attributes for the matching process that follows.In the analysis process,we adopt entropy-maximum deviation method(MDM)-decision-making trial and evaluation laboratory(DEMATEL)-technique for order preference by similarity to an ideal solution(TOPSIS)to obtain a comprehensive analysis.The entropy-MDM is applied to get weight value,DEMATEL is utilized to obtain internal relations,and TOPSIS is adopted to get ideal evaluated solution.We consider aggregating two types of evaluation information according to similarities of smart complex equipment based on the combination between geometric mean and arithmetic mean.Moreover,based on the aforementioned attributes and generalized power Heronian mean operator,we aggregate preference information to acquire relevant satisfaction degree,then combine the constructed matching model to get suitable key supplier.Through comprehensive analysis of selecting suitable suppliers,we know that two-sided matching and information aggregation can provide more research perspectives for smart complex equipment.Through analysis for relevant factors,we find that leading role and service level are also significant for the smart complex equipment development process.展开更多
Decision Making Trial and Evaluation Laboratory(DEMATEL)method is a powerful tool for understanding and visualizing the causal relationships among factors in complex decision-making problems.The method uses diagrams a...Decision Making Trial and Evaluation Laboratory(DEMATEL)method is a powerful tool for understanding and visualizing the causal relationships among factors in complex decision-making problems.The method uses diagrams and matrixes to map out the causal relationships and interdependencies among factors,allowing decision-makers to identify key drivers and potential solutions to the problem.DEMATEL has a wide range of application areas,including supply chain management,environmental planning,healthcare,finance,and engineering,among others.The DEMATEL method is a valuable tool for decision-makers who need to understand the complex causal relationships among factors in order to make informed decisions.The method provides a structured approach for analyzing and prioritizing factors and for identifying potential solutions to complex problems.This paper describes the main features of this method,its application areas as well as the main process steps in the DEMATEL method.展开更多
Land suitability assessment (LSA) is an essential step in the process of determining environmental limits for sustainable crop production. Up to date, studies on LSA for crop production in Cameroon have been based on ...Land suitability assessment (LSA) is an essential step in the process of determining environmental limits for sustainable crop production. Up to date, studies on LSA for crop production in Cameroon have been based on empirical methods which are limited as they consider similar singnificance levels for all evaluation criteria and do not consider the interrelationships of criteria in the best-fit models. In the present study a qualitative land suitability evaluation by an integrated multi-criteria decision-making (MCDM) approach and geographic information system (GIS) was tested to assess and map suitable land units for maize (Zea mays L) production in Cameroon Western highland. Eight environmental criteria identified as the most relevant for maize production in the area of interest (AOI) saw their thematic maps prepared using ArcGIS 10.8. The relationship between criteria was considered by the DEMATEL method. The criteria were weighted using the ANP method. Thereafter, the land suitability map was obtained using the weighted overlay analysis (WOA) in ArcGIS. The results obtained indicated that slope has the highest specific weight and consequently the greatest influence on land suitability for maize production in the locality. The land suitability map generated showed that Foumbot’s agricultural land suitability for maize production varies from very high to marginally suitable (99% of the surface area). Specifically, 11% (8056 ha) is very highly suitable, 29% (21,119 ha) is highly suitable, 38% (27,405 ha) are moderately suitable and 20% (14,422 ha) are marginally suitable. The remaining 1% that falls under non suitable class represents 606 ha and is located on the steep slopes around the Mount Mbappit. The kappa analysis reveals a total overall accuracy of 78.67% and a kappa value of 0.7256 with an asymptotic error of 0.058 which is good. Then the model used in this research is highly recommended for future land evaluation works in Cameroon and similar ecosystems around the world.展开更多
The large number of environmental problems faced by society in recent years has driven researchers to collect and study massive amounts of data in order to understand the complex relations that exist between people an...The large number of environmental problems faced by society in recent years has driven researchers to collect and study massive amounts of data in order to understand the complex relations that exist between people and the environment in which we live.Such datasets are often high dimensional and heterogeneous in nature,with complex geospatial relations.Analysing such data can be challenging,especially when there is a need to maintain spatial awareness as the non-spatial attributes are studied.Geo-Coordinated Parallel Coordinates(GCPC)is a geovisual analytics approach designed to support exploration and analysis within complex geospatial environmental data.Parallel coordinates are tightly coupled with a geospatial representation and an investigative scatterplot,all of which can be used to show,reorganize,filter,and highlight the high dimensional,heterogeneous,and geospatial aspects of the data.Two sets of field trials were conducted with expert data analysts to validate the real-world benefits of the approach for studying environmental data.The results of these evaluations were positive,providing real-world evidence and new insights regarding the value of using GCPC to explore among environmental datasets when there is a need to remain aware of the geospatial aspects of the data as the non-spatial elements are studied.展开更多
ldentifying risks and prioritizing is important for payment service provider(PSP)companies to get banking projects and gain more market share.However,studies regarding the identification of risks and causal relationsh...ldentifying risks and prioritizing is important for payment service provider(PSP)companies to get banking projects and gain more market share.However,studies regarding the identification of risks and causal relationships are insufficient in the lranian PSP industry and the industry is unique because of its characteristics.In this study,30 experts involved with PSP companies are employed as the research sample.Eleven key risks and 46 sub-risks are also ientified.Subsequently,the fuzzy decision-making trial and evaluation laboratory technique is applied to determine the effective and affected risks and the severity of their effects on each other.Finally,all risks are ranked.Due to the interal interrelationships of the main risks,the weight of each risk is calculated via the fuzy analytic network process.As the second-level risks have no significant interrelationships,they are ranked via the fuzzy analytical hierarchy process.Moreover,the best-worst method is used to ensure that the obtained rankings are reliable.This study identifies the risks affecting the loss of banking projects and determines the impacts of these risks on each.A sensitivity analysis is then conducted on the weights of the criteria,and the results are compared.展开更多
文摘With the development of central-private enterprises integration,selecting suitable key suppliers are able to provide core components for smart complex equipment.We consider selecting suitable key suppliers from matching perspective,for it not only satisfies natural development of smart complex equipment,it is also a good implementation of equipment project in central-private enterprises integration context.In in this paper,we carry out two parts of research,one is evaluation attributes based on comprehensive analysis,and the other is matching process between key suppliers and core components based on the matching attribute.In practical analysis process,we employ comprehensive evaluated analysis methods to acquire relevant attributes for the matching process that follows.In the analysis process,we adopt entropy-maximum deviation method(MDM)-decision-making trial and evaluation laboratory(DEMATEL)-technique for order preference by similarity to an ideal solution(TOPSIS)to obtain a comprehensive analysis.The entropy-MDM is applied to get weight value,DEMATEL is utilized to obtain internal relations,and TOPSIS is adopted to get ideal evaluated solution.We consider aggregating two types of evaluation information according to similarities of smart complex equipment based on the combination between geometric mean and arithmetic mean.Moreover,based on the aforementioned attributes and generalized power Heronian mean operator,we aggregate preference information to acquire relevant satisfaction degree,then combine the constructed matching model to get suitable key supplier.Through comprehensive analysis of selecting suitable suppliers,we know that two-sided matching and information aggregation can provide more research perspectives for smart complex equipment.Through analysis for relevant factors,we find that leading role and service level are also significant for the smart complex equipment development process.
文摘Decision Making Trial and Evaluation Laboratory(DEMATEL)method is a powerful tool for understanding and visualizing the causal relationships among factors in complex decision-making problems.The method uses diagrams and matrixes to map out the causal relationships and interdependencies among factors,allowing decision-makers to identify key drivers and potential solutions to the problem.DEMATEL has a wide range of application areas,including supply chain management,environmental planning,healthcare,finance,and engineering,among others.The DEMATEL method is a valuable tool for decision-makers who need to understand the complex causal relationships among factors in order to make informed decisions.The method provides a structured approach for analyzing and prioritizing factors and for identifying potential solutions to complex problems.This paper describes the main features of this method,its application areas as well as the main process steps in the DEMATEL method.
文摘Land suitability assessment (LSA) is an essential step in the process of determining environmental limits for sustainable crop production. Up to date, studies on LSA for crop production in Cameroon have been based on empirical methods which are limited as they consider similar singnificance levels for all evaluation criteria and do not consider the interrelationships of criteria in the best-fit models. In the present study a qualitative land suitability evaluation by an integrated multi-criteria decision-making (MCDM) approach and geographic information system (GIS) was tested to assess and map suitable land units for maize (Zea mays L) production in Cameroon Western highland. Eight environmental criteria identified as the most relevant for maize production in the area of interest (AOI) saw their thematic maps prepared using ArcGIS 10.8. The relationship between criteria was considered by the DEMATEL method. The criteria were weighted using the ANP method. Thereafter, the land suitability map was obtained using the weighted overlay analysis (WOA) in ArcGIS. The results obtained indicated that slope has the highest specific weight and consequently the greatest influence on land suitability for maize production in the locality. The land suitability map generated showed that Foumbot’s agricultural land suitability for maize production varies from very high to marginally suitable (99% of the surface area). Specifically, 11% (8056 ha) is very highly suitable, 29% (21,119 ha) is highly suitable, 38% (27,405 ha) are moderately suitable and 20% (14,422 ha) are marginally suitable. The remaining 1% that falls under non suitable class represents 606 ha and is located on the steep slopes around the Mount Mbappit. The kappa analysis reveals a total overall accuracy of 78.67% and a kappa value of 0.7256 with an asymptotic error of 0.058 which is good. Then the model used in this research is highly recommended for future land evaluation works in Cameroon and similar ecosystems around the world.
基金This work was supported in part by grant from Social Sciences and Humanities Research Council of Canada(SSHRC)(895-2011-1011)held by the second author.
文摘The large number of environmental problems faced by society in recent years has driven researchers to collect and study massive amounts of data in order to understand the complex relations that exist between people and the environment in which we live.Such datasets are often high dimensional and heterogeneous in nature,with complex geospatial relations.Analysing such data can be challenging,especially when there is a need to maintain spatial awareness as the non-spatial attributes are studied.Geo-Coordinated Parallel Coordinates(GCPC)is a geovisual analytics approach designed to support exploration and analysis within complex geospatial environmental data.Parallel coordinates are tightly coupled with a geospatial representation and an investigative scatterplot,all of which can be used to show,reorganize,filter,and highlight the high dimensional,heterogeneous,and geospatial aspects of the data.Two sets of field trials were conducted with expert data analysts to validate the real-world benefits of the approach for studying environmental data.The results of these evaluations were positive,providing real-world evidence and new insights regarding the value of using GCPC to explore among environmental datasets when there is a need to remain aware of the geospatial aspects of the data as the non-spatial elements are studied.
文摘ldentifying risks and prioritizing is important for payment service provider(PSP)companies to get banking projects and gain more market share.However,studies regarding the identification of risks and causal relationships are insufficient in the lranian PSP industry and the industry is unique because of its characteristics.In this study,30 experts involved with PSP companies are employed as the research sample.Eleven key risks and 46 sub-risks are also ientified.Subsequently,the fuzzy decision-making trial and evaluation laboratory technique is applied to determine the effective and affected risks and the severity of their effects on each other.Finally,all risks are ranked.Due to the interal interrelationships of the main risks,the weight of each risk is calculated via the fuzy analytic network process.As the second-level risks have no significant interrelationships,they are ranked via the fuzzy analytical hierarchy process.Moreover,the best-worst method is used to ensure that the obtained rankings are reliable.This study identifies the risks affecting the loss of banking projects and determines the impacts of these risks on each.A sensitivity analysis is then conducted on the weights of the criteria,and the results are compared.
