As cross-border electronic commerce(CBEC)has become a new path to serve the Belt and Road(B&R)Initiative,it is imperative to develop an efficient,convenient and simple online dispute resolution(ODR)mechanism to fa...As cross-border electronic commerce(CBEC)has become a new path to serve the Belt and Road(B&R)Initiative,it is imperative to develop an efficient,convenient and simple online dispute resolution(ODR)mechanism to facilitate the CBEC among the B&R countries.This study examines the legislative practice of the European Union(EU),the United Nations Commission on International Trade Law(UNCITRAL),and the Organization of American States(OAS)in the ODR mechanisms for CBEC.The findings provide reference and inspiration for China’s essential role in developing an ODR mechanism for CBEC among the B&R countries.Legally,ODR for CBEC between the B&R countries is essentially an innovative combination of rule by technology and rule by private law.In light of related principles(e.g.,special consumer protection,procedural fairness,and consumers’personal information and data protection),China should develop an ODR mechanism(involving compromise,mediation,online arbitration,and online court)for CBEC among the B&R countries based on China’s experience in the ODR for CBEC.展开更多
China has decided not to subject firsttime cross-border e-commerce(CBEC) Imports to licensing, registration or record-filing requirements, signaling easier times ahead for foreign cosmetics companies. According to the...China has decided not to subject firsttime cross-border e-commerce(CBEC) Imports to licensing, registration or record-filing requirements, signaling easier times ahead for foreign cosmetics companies. According to the statement from the State Council, China plans to "expand and improve" the existing CBEC policies in order to "unlock the potential of consumption" in China.展开更多
Numerous previous literature has attempted to apply machine learning techniques to analyze relationships between energy variables in energy consumption.However,most machine learning methods are primarily used for pred...Numerous previous literature has attempted to apply machine learning techniques to analyze relationships between energy variables in energy consumption.However,most machine learning methods are primarily used for prediction through complicated learning processes at the expense of interpretability.Those methods have difficulties in evaluating the effect of energy variables on energy consumption and especially capturing their heterogeneous relationship.Therefore,to identify the energy consumption of the heterogeneous relationships in actual buildings,this study applies the MOdel-Based recursive partitioning(MOB)algorithm to the 2012 CBECS survey data,which would offer representative information about actual commercial building characteristics and energy consumption.With resultant tree-structured subgroups,the MOB tree reveals the heterogeneous effect of energy variables and mutual influences on building energy consumptions.The results of this study would provide insights for architects and engineers to develop energy conservative design and retrofit in U.S.office buildings.展开更多
In recent years,with the support of national policies,Cross Border E-Commerce(CBEC)has developed rapidly.This business model not only brings significant benefits to the national economy,but also has many unique challe...In recent years,with the support of national policies,Cross Border E-Commerce(CBEC)has developed rapidly.This business model not only brings significant benefits to the national economy,but also has many unique challenges,especially at the level of supply chain management.Therefore,to enable CBEC enterprises to develop sustainable supply chain,this study discusses the performance evaluation model of supply chain and proposes a CBEC Supply Chain Performance Evaluation Model(CBECSC-EM)based on the Levenberg–Marquardt Backpropagation(LMBP)algorithm.This experiment constructs performance evaluation indicators for the supply chain of CBEC enterprises.On this basis,the LMBP algorithm is introduced,and improved in the experiment to make the overall performance of the evaluation model more scientific and reasonable.In the verification set,the maximum F1 values of LMBP,DEA,SBM,and BP are 98.46%,93.78%,87.29%,and 78.95%,respectively.The MAPE value of LMBP model is 0.102%,which is lower than the other three methods(0.282%,0.343%,and 0.385%)selected in the experiment.The maximum standard deviation rates of importance and operability of the evaluation indexes are 0.1346 and 0.1405,respectively,and there is a significant consistency between the expert scores.Therefore,the LMBP algorithm has broad application prospects in supply chain performance evaluation of CBEC enterprises.展开更多
基金funded by a soft science research project of Sichuan titled“Study of Legal Regulation of ODR for CBEC between the B&R Countries”(2020JDR0304).
文摘As cross-border electronic commerce(CBEC)has become a new path to serve the Belt and Road(B&R)Initiative,it is imperative to develop an efficient,convenient and simple online dispute resolution(ODR)mechanism to facilitate the CBEC among the B&R countries.This study examines the legislative practice of the European Union(EU),the United Nations Commission on International Trade Law(UNCITRAL),and the Organization of American States(OAS)in the ODR mechanisms for CBEC.The findings provide reference and inspiration for China’s essential role in developing an ODR mechanism for CBEC among the B&R countries.Legally,ODR for CBEC between the B&R countries is essentially an innovative combination of rule by technology and rule by private law.In light of related principles(e.g.,special consumer protection,procedural fairness,and consumers’personal information and data protection),China should develop an ODR mechanism(involving compromise,mediation,online arbitration,and online court)for CBEC among the B&R countries based on China’s experience in the ODR for CBEC.
文摘China has decided not to subject firsttime cross-border e-commerce(CBEC) Imports to licensing, registration or record-filing requirements, signaling easier times ahead for foreign cosmetics companies. According to the statement from the State Council, China plans to "expand and improve" the existing CBEC policies in order to "unlock the potential of consumption" in China.
文摘Numerous previous literature has attempted to apply machine learning techniques to analyze relationships between energy variables in energy consumption.However,most machine learning methods are primarily used for prediction through complicated learning processes at the expense of interpretability.Those methods have difficulties in evaluating the effect of energy variables on energy consumption and especially capturing their heterogeneous relationship.Therefore,to identify the energy consumption of the heterogeneous relationships in actual buildings,this study applies the MOdel-Based recursive partitioning(MOB)algorithm to the 2012 CBECS survey data,which would offer representative information about actual commercial building characteristics and energy consumption.With resultant tree-structured subgroups,the MOB tree reveals the heterogeneous effect of energy variables and mutual influences on building energy consumptions.The results of this study would provide insights for architects and engineers to develop energy conservative design and retrofit in U.S.office buildings.
文摘In recent years,with the support of national policies,Cross Border E-Commerce(CBEC)has developed rapidly.This business model not only brings significant benefits to the national economy,but also has many unique challenges,especially at the level of supply chain management.Therefore,to enable CBEC enterprises to develop sustainable supply chain,this study discusses the performance evaluation model of supply chain and proposes a CBEC Supply Chain Performance Evaluation Model(CBECSC-EM)based on the Levenberg–Marquardt Backpropagation(LMBP)algorithm.This experiment constructs performance evaluation indicators for the supply chain of CBEC enterprises.On this basis,the LMBP algorithm is introduced,and improved in the experiment to make the overall performance of the evaluation model more scientific and reasonable.In the verification set,the maximum F1 values of LMBP,DEA,SBM,and BP are 98.46%,93.78%,87.29%,and 78.95%,respectively.The MAPE value of LMBP model is 0.102%,which is lower than the other three methods(0.282%,0.343%,and 0.385%)selected in the experiment.The maximum standard deviation rates of importance and operability of the evaluation indexes are 0.1346 and 0.1405,respectively,and there is a significant consistency between the expert scores.Therefore,the LMBP algorithm has broad application prospects in supply chain performance evaluation of CBEC enterprises.
