This book aims at providing an empirical understanding of the main drivers affecting investors’ preferences in financing new ventures through equity crowdfunding (ECF) and determining fundraising campaign success. ECF is increasing in prominence as a route for new ventures in obtaining external financial resources. To raise capital, entrepreneurs are required to convey quality signals of their proposals with real-time information and knowledge sharing.
This book advances knowledge in entrepreneurial finance by investigating the factors that affect individuals’ decisions to participate in ECF. The authors adopt a data mining approach to extract publicly available information from a multitude of crowdfunding platforms across different countries, producing a unique dataset.
The book uses an innovative hybrid analysis to generate knowledge patterns creating data-driven models on one hand, and on the other test research hypotheses adopting statistical models to investigate empirical evidence in line, or in contrast, with the extant literature. The book also integrates organizational theories to examine the extent to which ECF platform managers follow a strategy of isomorphism in their choice of information disclosure. The final part of the book discusses how signals are interpreted by investors, how these affect financing preferences, and ultimately the successful completion of a fundraising campaign. The book will be of interest to academics and practitioners in entrepreneurial finance, FinTech, and investment behaviour.
Author(s): Francesco James Mazzocchini, Caterina Lucarelli
Publisher: Palgrave Pivot
Year: 2023
Language: English
Pages: 155
City: Cham
Acknowledgements
Contents
About the Authors
List of Figures
List of Tables
1 Introduction: What Is Equity Crowdfunding and How Can the Decision-Making Process of Retail Investors Be Outlined?
References
2 About Entrepreneurial Finance and Factors Affecting Crowd-Investor Preferences
2.1 Entrepreneurial Finance
2.2 FinTech and Equity Crowdfunding
2.3 Information Asymmetry and Signalling Theory
2.4 The Actors in the Process
2.5 Platforms’ Isomorphism
2.6 Drivers for the Crowd-Investors’ Action and Preferences
2.6.1 Entrepreneur Financial, Human and Social Capital (K1)
2.6.2 Venture Characteristics (K2)
2.6.3 Campaign Characteristics (K3)
2.6.4 Investors’ Behaviour (K4/Y)
2.7 Research Questions and Research Hypotheses
References
3 Definition and Description of the Analytical Process: A Data Mining Approach
3.1 The Knowledge Discovery in Databases (KDD)
3.2 Data Scraping
3.3 Data Consolidation and Wrangling
3.4 Data Pre-processing
3.5 Cleaning Procedures in Practice
3.6 Data Analysis
References
4 Sample Selection and Platform Characteristics
4.1 Platform Description
4.2 Variables Description
4.2.1 Dependent Variables
4.2.2 Independent Variables
4.3 Information Dissemination
4.3.1 Data Available Per Platform
References
5 Data Analysis and Econometric Models
5.1 Review of the Main Findings from Literature
5.2 Methodology of Estimation
References
6 Empirical Results
6.1 Description of the Sample
6.2 Exploratory Analysis
6.3 Determinants of ECF Success
6.3.1 Country-Level Analysis
6.3.2 Platform-Level Analysis
6.4 Discussion of Findings
6.4.1 Isomorphism Among ECF Platforms
6.4.1.1 First Piece of Evidence: Typologies of Public Information
6.4.1.2 Second Piece of Evidence: Trade-Off Between Breadth and Depth of Data
6.4.1.3 Third Piece of Evidence: Heterogeneous Projects Screening Procedures
6.4.1.4 Fourth Piece of Evidence: Heterogeneous Presence of Professional Investors
6.4.2 Investors’ Preferences in Financing New Ventures Through Equity Crowdfunding
References
7 Conclusions and Contributions to Theory and Practice
7.1 Limitations of the Study
7.2 Theoretical and Practical Implications
Appendix: Analytical Results of Estimations
Country-Level Estimates
Platform-Level Estimates
Index
