Fr. 69.00

Investors' Preferences in Financing New Ventures - A Data Mining Approach to Equity

English · Hardback

Shipping usually within 2 to 3 weeks (title will be printed to order)

Description

Read more

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 adoptingstatistical 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.

List of contents

Chapter 1. Introduction: what is equity crowdfunding and how can the decision-making process of retail investors be outlined?.- Chapter 2. About entrepreneurial finance and factors affecting crowd-investor preferences.- Chapter 3. Definition and description of the analytical process: a data mining approach.- Chapter 4. Sample selection and platform characteristics.- Chapter 5. Data analysis and econometric models.- Chapter 6. Empirical results.- Chapter 7. Conclusions and contributions to theory and practice.

About the author










Francesco James Mazzocchini, Ph.D., is postdoctoral research fellow in Banking and Financial Markets at the Department of Management, Marche Polytechnic University - Italy. His scientific interests are in the fields of behavioural finance, decision-making under risk, FinTech, innovative financing, and entrepreneurial finance.

 

Caterina Lucarelli is Full Professor of Banking and Financial Markets at the Department of Management, Marche Polytechnic University - Italy. Her scientific interests are in the fields of market microstructure, investors' behaviour, decision-making under risk, gender diversity, entrepreneurship and sustainable finance. Since 2007, as National Coordinator of a Research Project supported by the Italian Ministry of University and Research, she has cooperated with psychologist and neuroscientists to study individual risk tolerance.



Product details

Authors Caterina Lucarelli, Francesco James Mazzocchini
Publisher Springer, Berlin
 
Languages English
Product format Hardback
Released 01.06.2023
 
EAN 9783031300578
ISBN 978-3-0-3130057-8
No. of pages 147
Dimensions 148 mm x 12 mm x 210 mm
Illustrations XIV, 147 p. 26 illus., 11 illus. in color.
Subject Social sciences, law, business > Business > Business administration

Customer reviews

No reviews have been written for this item yet. Write the first review and be helpful to other users when they decide on a purchase.

Write a review

Thumbs up or thumbs down? Write your own review.

For messages to CeDe.ch please use the contact form.

The input fields marked * are obligatory

By submitting this form you agree to our data privacy statement.