Artikel
Crowdinvesting in entrepreneurial projects: disentangling patterns of investor behavior
Crowdinvesting emerged recently as an alternative way of funding for start-up projects. Our dataset consists of 16,666 investments made at Companisto, one of the largest crowdinvesting platforms in Europe. Using cluster analysis based on individual investment decisions, we find that crowdinvestors differ in their investment strategies and motivations. We can distinguish three types of crowdinvestors: Casual Investors, Crowd Enthusiasts, and Sophisticated Investors. The types also vary in their response to project quality signals, project-related information reducing the degree of uncertainty, and social influence by fellow investors. We conclude that crowdinvestors are anything but a homogeneous group. Instead, they are motivated by different factors and respond to different signals when making investment decisions.
- Language
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Englisch
- Bibliographic citation
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Journal: Small Business Economics ; ISSN: 1573-0913 ; Volume: 57 ; Year: 2020 ; Issue: 2 ; Pages: 905-926 ; New York, NY: Springer US
- Classification
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Wirtschaft
Pension Funds; Non-bank Financial Institutions; Financial Instruments; Institutional Investors
Behavioral Finance: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets‡
Entrepreneurship
- Subject
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Crowdinvesting
Entrepreneurial finance
New ventures
Cluster analysis
Social influence
Signaling
- Event
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Geistige Schöpfung
- (who)
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Goethner, Maximilian
Luettig, Sebastian
Regner, Tobias
- Event
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Veröffentlichung
- (who)
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Springer US
- (where)
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New York, NY
- (when)
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2020
- DOI
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doi:10.1007/s11187-020-00332-0
- Last update
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10.03.2025, 11:44 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Goethner, Maximilian
- Luettig, Sebastian
- Regner, Tobias
- Springer US
Time of origin
- 2020
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