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.
