Analysis on Internet Financial Business and Construction of Credit System

Internet finance is a new emerging financial model,using the Internet as a platform,big data and cloud computing as the basis.Supply Chain Finance is the easiest way to enter Internet finance.The thirdparty companies or institutions can invest in Internet financial companies by integrating their industrial chain practices into designing the financial products to reduce credit costs and improve safety.At the same time,it will increase mobile Internet,big data and operational services.Also,it can make full use of the Internet financial platform to provide value-added services for higher and lower enterprise and consolidate the core status of the company in the industrial chain.However,an important issue that needs to be concerned during developing Supply Chain Finance is the construction of a system for credit evaluation.Due to the lack of a unified credit evaluation system,the development of the existing Supply Chain Financial companies suffers from difficulties.Many newly launched companies have difficulties operating due to the lack of a credit evaluation system.Therefore,proper and effective credit indicators are essential for the development of enterprises under Internet finance.From the micro perspective,it is conducive for enterprises to improve their credit under the constraints of indicators,and it can solve the problem of capital raising;from the macro perspective,it is conducive to the standardized development of China’s Internet finance and promotes the comprehensive economic development.Based on this,analyzing the model of Internet financial business and developing an enterprise’s credit index system is beneficial to the development of China’s Internet finance.

Digital Marketing and B2B Cross-Border E-Commerce: A Case Study of Alibaba International Station in China

The rapid development of the“Internet+”has ushered in a new era of global digital technology innovation.Concurrent with the deepening trends of economic globalization and integration,international trade is progressively undergoing extensive digitization,with cross-border e-commerce emerging as a significant manifestation of this transformation.Within this landscape,the cross-border e-commerce B2B platform is anticipated to become a pivotal driver for China’s cross-border trade growth,representing a strategic opportunity for trade transformation.This paper provides a comprehensive examination of the concepts,characteristics,and development status of cross-border e-commerce and B2B platforms,considering both global and Chinese perspectives.Focusing on a prominent case study,Alibaba International Station,a B2B cross-border e-commerce platform,the paper delves into its business model and core competencies,offering a thorough analysis of its role in the intricacies of international e-commerce and its contribution to the field.Drawing on insights gained,the paper concludes by presenting targeted recommendations from both the platform and government perspectives.These suggestions are informed by a nuanced understanding of the development opportunities and challenges facing China’s cross-border e-commerce B2B platforms.

Modelling User Needs:Students as Enterprise Analysts

We illustrate a case study,where students designed enterprise architectures,that were not only welcome but successfully implemented.The success key was threefold.First the analysis framework,that integrates all the aspects of the systems that are relevant to users,namely user interface,rules,and information.Second,the analysis approach,that guides,trough confirmatory sessions,to elicit real requirements from users.Third,the model-to-model transformation,that assures consistency from the highest aggregate abstraction down to an executable model.

An Estimated DSGE Model for Business Cycle Analysis in China

A small-scale, but highly-stylized dynamic stochastic general equilibrium model is estimated by the maximum likelihood method using Chinese quarterly data. Model specifications and parameter equalities between various competing model variants are addressed by formal statistical hypothesis tests, while implications for business cycle fluctuations are evaluated via a variance decomposition experiment, second-moments matching, and some out-of-sample forecast exercises. It is highlighted that the monetary authority takes an aggressive stance to the current inflation pressure （there is a significant lagged response）, while leaving less attention to changes in aggregate output. Variance decomposition reveals that large percentages of variations in real and nominal variables are explained by the highly volatile preference and potential output shock, respectively. When nominal and real frictions as well as additional shocks are included, overall our estimated model can successfully reproduce the stylized facts from actual data of Chinese business cycles and frequently can even outperform those forecasts from an unconstrained VAR.