Research On The Influence Of Home Bias On Online Crowdfunding Project Investment Behavior And Financing Effect

Home bias is a common phenomenon in offline trading scenarios,which refers to the geographic convergence of user behavior,rather than spreading to a wide range of distances.In other words,it is difficult for user behavior to break the geographic restrictions.More and more scholars believe that the home bias characteristics of user behavior should be taken into account in market structure analysis,policy formulation and social welfare provision.home bias for trade are considered one of the six mysteries of international macroeconomics.In crowdfunding platform,all funds flow is realized through online transfer,not involving geographical gap;at the same time,information flow is equally visible to all users,and there is no geographical difference.The online crowdfunding model,which breaks the geographical limitations,has shown significant home bias in a small number of existing studies.Therefore,even in online financial markets,home bias may be the typical behavior pattern of investors,and home bias of investment behavior are the important factors affecting financing performance.This study introduces data mining and measurement model to build a bridge between investors' home bias behavior and the financing effect of crowdfunding projects.In recent years,data mining and social relationship analysis have opened up new ideas to solve the above problems.Data mining method can be used to analyze data in groups,layers and face-to-face,and get multi-level home bias behavior model of investors.Using data from Kickstarter,the world's largest revenue-based crowdfunding platform,136,234 crowdfunding projects and their geographic location data were collected using crawler technology.In addition,the reptiles also collected the location information of all investors.In order to compare the differences in home bias between Chinese and American investors horizontally,we also collected 347 Chinese crowdfunding projects from Demohour and its detailed investment data.Through data mining and empirical analysis,this paper draws the following key conclusions:1)The online crowdfunding model,which breaks the geographical limitations,has shown significant home bias.In the online financial market,home bias is a typical behavior pattern of investors,that is,investors tend to invest in crowdfunding projects that are close to themselves,rather than investing in crowdfunding projects that are far away.2)It is confirmed that the home bias of users in different project categories show different trends.In the existing research,the user behavior patterns are analyzed as a whole,without subdividing the home bias objects.This paper subdivides projects into categories,and proves that investors' behavior shows different home bias in different types of projects.In some project categories,home bias significantly exists and affect financing performance;in others,they do not.3)The existence of home bias in crowdfunding investment behavior is hierarchical,and dynamic diffusion and play an important impact on financing performance.The data used in this paper has a time variable,which is convenient for examining the changes in home bias from a dynamic perspective,which is helpful for a deep understanding of the changes in investor behavior patterns.In the initial stage of financing,the distance between investors and financiers was relatively close.As the financing progressed,the average distance between the investment and financing sides gradually increased from 3,605 kilometers to 4,229 kilometers.The diffusion of home bias shows a completely different trend in different project categories.Through the prediction model,it is found that the prediction accuracy of project financing results has increased from 63% to more than 70% considering the diffusion of home bias.4)We compared the trends of home bias between Chinese investors and American investors,the actual investment data shows that US investors are more open and they invest more in foreign projects;while Chinese investors' home bias are more intense,that is,Chinese investors invest more domestic projects.From the internal perspective of China and the US,they all show different levels of home bias and show certain regional differences.This paper enriches our understanding of user behavior patterns,improves the management and marketing channels of Internet finance,and provides theoretical basis and practical reference for the healthy development of Internet finance.This study would help to design a new generation of Internet crowdfunding model under the guidance of home bias behavior model: according to the characteristics of user behavior model,guide the design of a new generation of Internet crowdfunding model,fully consider the investment preference and investment characteristics of investors,improve the financing ability and friendliness of Internet finance.