Credit risk prediction for small and medium enterprises(SMEs)has long posed a complex research challenge.Traditional approaches have primarily focused on enterprise-specific variables,but these models often prove inad...Credit risk prediction for small and medium enterprises(SMEs)has long posed a complex research challenge.Traditional approaches have primarily focused on enterprise-specific variables,but these models often prove inadequate when applied to SMEs with incomplete data.In this innovative study,we push the theoretical boundaries by leveraging data from adjacent enterprises to address the issue of data deficiency.Our strategy involves constructing an intricate network that interconnects enterprises based on shared managerial teams and business interactions.Within this network,we propose a novel relational graph attention network(RGAT)algorithm capable of capturing the inherent complexity in its topological information.By doing so,our model enhances financial service providers'ability to predict credit risk even in the face of incomplete data from target SMEs.Empirical experiments conducted using China's SMEs highlight the predictive proficiency and potential economic benefits of our proposed model.Our approach offers a comprehensive and nuanced perspective on credit risk while demonstrating the advantages of incorporating network-wide data in credit risk prediction.展开更多
A high quality transportation system is necessary in a modem economy, and a road network is a common and significant, component of the system. Road systems have two major objectives： to enable the movement of passeng...A high quality transportation system is necessary in a modem economy, and a road network is a common and significant, component of the system. Road systems have two major objectives： to enable the movement of passenger vehicles and the movement of freight vehicles at reasonable speeds. An important part of the transportation system and an expensive investment, a functional road network must meet both objectives to main- tain an efficient economy. In Australia, the Department of Infrastructure and Regional Development reported that, in 2011/12, the total road length was approximately 900,000 kin, and the total road expenditure was approximately $19 billion. Good policy requires that infrastructure investments provide a return on investment, thus warranting judicious management to ensure that it is maintained in a cost effective manner. Recent studies in Queensland, Australia, have identified differences between financial and engi- neering professionals in their understanding of infrastructure depreciation, condition deterioration, and future funding needs. Furthermore, the Queensland Asset Sustainability Ratio （ASR） requires clearer definitions to ensure that infrastructure remains meaningful to all users. This study proposes a separate sustainability index for road pavements （SIR） unlike the ASR that combines all type of assets. The justification is our ability to assess road condition, the high value of road assets, relative value to other infrastructure, and advanced knowledge of deterioration relative to other infrastructure. The SIR involves community consultation to target an average pavement condition index （PCI）. This study also provides an alternative method to determine the optimal target PCI for a local展开更多
文摘Credit risk prediction for small and medium enterprises(SMEs)has long posed a complex research challenge.Traditional approaches have primarily focused on enterprise-specific variables,but these models often prove inadequate when applied to SMEs with incomplete data.In this innovative study,we push the theoretical boundaries by leveraging data from adjacent enterprises to address the issue of data deficiency.Our strategy involves constructing an intricate network that interconnects enterprises based on shared managerial teams and business interactions.Within this network,we propose a novel relational graph attention network(RGAT)algorithm capable of capturing the inherent complexity in its topological information.By doing so,our model enhances financial service providers'ability to predict credit risk even in the face of incomplete data from target SMEs.Empirical experiments conducted using China's SMEs highlight the predictive proficiency and potential economic benefits of our proposed model.Our approach offers a comprehensive and nuanced perspective on credit risk while demonstrating the advantages of incorporating network-wide data in credit risk prediction.
文摘A high quality transportation system is necessary in a modem economy, and a road network is a common and significant, component of the system. Road systems have two major objectives： to enable the movement of passenger vehicles and the movement of freight vehicles at reasonable speeds. An important part of the transportation system and an expensive investment, a functional road network must meet both objectives to main- tain an efficient economy. In Australia, the Department of Infrastructure and Regional Development reported that, in 2011/12, the total road length was approximately 900,000 kin, and the total road expenditure was approximately $19 billion. Good policy requires that infrastructure investments provide a return on investment, thus warranting judicious management to ensure that it is maintained in a cost effective manner. Recent studies in Queensland, Australia, have identified differences between financial and engi- neering professionals in their understanding of infrastructure depreciation, condition deterioration, and future funding needs. Furthermore, the Queensland Asset Sustainability Ratio （ASR） requires clearer definitions to ensure that infrastructure remains meaningful to all users. This study proposes a separate sustainability index for road pavements （SIR） unlike the ASR that combines all type of assets. The justification is our ability to assess road condition, the high value of road assets, relative value to other infrastructure, and advanced knowledge of deterioration relative to other infrastructure. The SIR involves community consultation to target an average pavement condition index （PCI）. This study also provides an alternative method to determine the optimal target PCI for a local
