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Participants’ Behavior And Platform’s Operation Analysis In The Reward Based Crowdfunding Market

Posted on:2017-05-31Degree:DoctorType:Dissertation
Country:ChinaCandidate:S S XiaoFull Text:PDF
GTID:1489305906959819Subject:Information management
Abstract/Summary:PDF Full Text Request
Crowdfunding,which is a typifier of Internet financial and has the characteristics of high efficiency,convenient and personalization when matching the capital supply and demand,is helping numerous organizations and individuals all over the world to realize their innovation dreams and to start new business.To some extent,it also accelerates China’s financial transformation,upgradesthe Chinese financial services industry and enriches the construction ofmultiple capital markets in China.However,as a new product of the fusion of highly developed information technologies and traditional finance agencies,the essence of crowdfunding and its operation mechanisms are still not well known by many practitioners and theoretical researchers.In this dissertation,we take the reward based crowdfunding as our research object and choose some key research questions,which are most related to the three kinds of participators in the crowdfunding market as our research content.Specifically,we separately and deeply discuss four management issues in the crowdfunding market(i.e.,Investors’ project choosing behavior in the crowdfunding market;Project founders’ optimal reward scheme design;Product improvement based on product reviews in the crowdfunding community;Investors’ reputationmanagement on the online crowdfunding platform).The detailed research content and findings can be concluded as follows:(1)Constructa complete and dynamic project choosing model for the investors on the crowdfunding platform based on the Social Cognitive Theory.The proposed model is well supported by using a real dataset from a famous crowdfunding platform in the word(the dataset is collected by using a self-designed Web Crawler).The author found that the description information of each crowdfunding project,the detailed information about reward scheme design and the characteristics of investors and lenders are the key factors which can influence investors’ project selection behavior.Specifically,the completeness and quality of project description can directly reduce the information asymmetry between investors and lenders and finally affects investors’ project selection;Project creators’ social network information,as well as their responses to investors’ questions can also reduce the information asymmetry.Furthermore,the rewards scheme design strategies used by project creators can be detected by the invertors and have positive effect on the project’s crowdfunding performance.(2)Complying with the special characteristics of crowdfunding mechanism,a basic reward scheme design model is built based on investor’s utility function.After some theoretical derivation of the basic model,the author has proved the existence of optimal reward scheme for each project on the crowdfunding platform.Furthermore,in the optimal reward scheme,the optimal price of each reward satisfies a specific equality constraint and the whole reward scheme design problem can be solved by searching a fixed point in a single variable equation.In addition,the project founders’ reward updating behavior,investors’ investment loss proportions,investors’ altruism and expectations of project success rate will influence the optimal reward prices and finally have impact on founders’ crowdfunding revenue.(3)Synthetically using text mining,sentiment analysis and other machine learning technology,the author successfully extract product features and investors’ sentiments from product reviews in the crowdfunding community.In order to help project founder improve his/her crowdfunding product,a new econometric model is used to measure investors’ aggregated preference on product feature and a modified Kano model is employed to visually display themeasurement results.(4)A reputation manage model and system are constructed from the starting point of managers on the crowdfunding platform.It will help to alleviate the information asymmetry between the project creators and investors,and to improve the operation efficiency of the whole crowdfunding platform.The dissertation has made some notable contributions to the extant literature and they can also be concluded as follows:First,the authorpioneereda complete and dynamic model to trace and interpreter investors’ real project choosing behavior in the crowdfunding market based the Social Cognitive Theory.The proposed model is supported by a real empiricalstudy on a famous crowdfunding platform.As a result,this study develops and enriches extant crowdfunding and internet finance research by transforming its research focus from searching factors which will affect projects’ crowdfunding performance to interpreting investors’ behavior on the crowdfunding platform.Second,the author sets up a new and basic reward scheme design model based on investors’ utility function and solves the model by transforming it into searching a fix point in an equation with single variable.Considering the behavior of investors and founder on the crowdfunding platform,the proposed basic model can also be extended to allow founders’ reward updating behavior,investors’ heterogeneity,and investors’ altruism effects.This study contributes to the extant crowdfunding literature and product design literature no matter from the perspective of methodology or research design.Third,this study also contributes to the existence preference measurement and management literature by establishing a new preference measurement and expression model based on a new type of social media data(i.e.,online project reviews in the crowdfunding community).The proposed method performances better when compared with extant preference measurement methods.Finally,considering the characteristics of founders in the crowdfunding market,the author constructs a Hidden Semi-Markov Model and information system to manage the founders’ reputation on the crowdfunding platform.The proposed model achieves better performance when compared with existed HMM based reputationmanagement model.This study enriches existence reputation management studies and alleviates the information asymmetry between investors and creators.The wholestructure of this dissertation is organized as follows: The first chapter shows an overall framework for the entire study and explains our research objects,contents,and methods.As a literature review part,the second chapter introduces some basic concepts of crowdfunding and summarizes the theoretical context for our study.In the third chapter,we begin to discuss investors’ project choosing behavior in the crowdfunding market based on a real dataset and rigid theories.According tothe insights derived from chapter three,we established the reward scheme design model for project founders in chapter four.In the fifth chapter,we discuss how to help founders improve their crowdfunding product by using investors’ preference information in the product reviews.We begin to talk about the founders’ reputation management issue from the perspective of platform managers.Finally,the author concludes the whole studyand shows the prospects of future research.
Keywords/Search Tags:Internet Finance, Reward based Crowdfunding, Investment Behavior, Product Reviews, Reputaton Management
PDF Full Text Request
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