The Investment Behavior Of Investors In Debt-based Crowdfunding

Debt-based crowdfunding is one form of financial technology boosted by the modern information technology.Such lending activity focuses on the need of small and diverse borrowers.These lending platforms act as information intermediaries.Lenders transact with borrowers directly based on the information and services provided by the lending platforms.Although debt-based lending has spread around the world,it has yet to receive great attention from information system research.Investors are the key participants of such lending activity.Their decisions directly affect whether the borrowers’ need is fulfilled,how the lending platforms operate,and the development of lending market.Therefore,understanding how investors making decisions become urgent.The purpose of this paper is to study investors’ decision-making behavior and to explore the underlying mechanism in debt-based crowdfunding activities.This work will help researchers gain insights into individual decision making in debt-based crowdfunding market and have managerial implications for investors,borrowers,lending platforms and policy makers.Specifically,this paper investigates the following questions.First,this work focuses on the investors’ herding behavior when choosing which platform to invest.By using transacting data from multiple lending platforms,this research finds that subsequent investors are more likely to choose platforms that have already attracted a large number of investors,herding behavior exists.The results also show that investors’ herding behaviors are moderated by platform features related to public awareness,capital condition,participant composition,as well as information disclosure regulations.This research contributes to the crowdfunding literature by providing empirical evidence of investors’ herding behavior at the platform level.Existing work mainly explores investors’ herding behavior at the listing level;thus,this paper provides a new perspective.This study is among the few that empirically looks into the relationship between government regulations and investors’ behavior in the debt-based crowdfunding.Second,this work investigates the matching between investors and borrowers.A two-sided structural matching model is established to capture the matching pattern.In estimation,a computational feasible maximum score estimator is introduced.This study finds that investor and borrower characteristics interact with each other to determine the matching.By investigating the impact of different information disclosure policies on match value at participant and market level,this study shows that the matching under a uniform disclosure policy is close to the assignment under current disclosure policy.Existing research provides evidence on investor decision making base on one-sided market framework.They cannot fully capture the endogenous lending process.The study contributes to the crowdfunding literature by using a two-sided matching framework to investigate the decisions of investors.Third,this work explores the moderating role of identity-disclosure in peer influence among investors.By leveraging usernames,a simple and direct form of identity-descriptive information,this work examines how the level of anonymity or identifiability of the precedent investors affect herding magnitude exhibited by subsequent investors.To capture the data structure,this work introduces both finite mixture model and cross-classified multilevel model.The results show that subsequent investors demonstrate the strongest herding magnitude toward prior investors using anonymous usernames,followed by those with pseudonyms and real-sounding names.Extant studies have found evidence that the observable actions of earlier investors have significant impacts on subsequent ones,but they largely ignore online identity the investors.The novelty of this work is that it reveals how the identity-disclosure moderates herding behavior and proves heterogeneity in herding behavior.This work also examines how investor value collateral information and the extent to which various constraints may affect their responses in a housing secured lending market.By using matched sample constructed from propensity score matching,this work establishes survival model and amount model to examine the investors’ response towards collateral type.The results show that lenders tend to decrease their investment pace and allocate less money when facing loan projects that use a mortgage as collateral rather than loan projects that use a self-owned house as collateral.Factors such as investment experience,peer influence,housing price and stock market fluctuation moderate lenders’ interpretation of collateral information in different ways.Existing studies largely focuses on credit based online lending;the secured lending receives less attention.This work contributes to the literature by linking the micro investor decision and macro factors such housing price and stock market through the lens of secured lending.