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Investors' preferences in financing new venturesa data mining approach to equity /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Investors' preferences in financing new venturesby Francesco James Mazzocchini, Caterina Lucarelli.
其他題名:	a data mining approach to equity /
作者:	Mazzocchini, Francesco James.
其他作者:	Lucarelli, Caterina.
出版者:	Cham :Springer Nature Switzerland :2023.
面頁冊數:	xiv, 147 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Investments.
電子資源:	https://doi.org/10.1007/978-3-031-30058-5
ISBN:	9783031300585$q(electronic bk.)

Investors' preferences in financing new venturesa data mining approach to equity /
Mazzocchini, Francesco James.

Investors' preferences in financing new venturesa data mining approach to equity /[electronic resource] :by Francesco James Mazzocchini, Caterina Lucarelli. - Cham :Springer Nature Switzerland :2023. - xiv, 147 p. :ill. (some col.), digital ;24 cm.

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.

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. 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.

ISBN: 9783031300585$q(electronic bk.)

Standard No.: 10.1007/978-3-031-30058-5doiSubjects--Topical Terms:

187451
Investments.

LC Class. No.: HG4521 / .M39 2023

Dewey Class. No.: 332.6

Investors' preferences in financing new venturesa data mining approach to equity /
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