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Effective strategies to attract crowdfunding investment based on the novelty of business ideas

Authors
Jung, EunjunLee, ChangjunHwang, Junseok
Issue Date
May-2022
Publisher
Elsevier BV
Keywords
Entrepreneurial finance; Crowdfunding; Investor attraction; Deep learning; Investor persuasion; Startup success factor
Citation
Technological Forecasting and Social Change, v.178, pp 1 - 16
Pages
16
Indexed
SSCI
SCOPUS
Journal Title
Technological Forecasting and Social Change
Volume
178
Start Page
1
End Page
16
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/111510
DOI
10.1016/j.techfore.2022.121558
ISSN
0040-1625
Abstract
Whether the novelty of an idea is a factor that directly influences crowdfunding success remains an area of ambiguity. We hypothesize that target funder diversification is effective with incremental ideas. However, focused business proposals are better suited to assert radical ideas. We also hypothesize the impact of two different strategic actions that founders can take during fundraising campaigns, agile information update and communication, on crowdfunding success. A deep-learning-based novelty detection model combined with statistical analysis is used to empirically test 7406 crowdfunding projects crawled from online platform. Our results support our hypotheses and reveal that information updates from startup founders show non-linear quadratic relationships with fundraising performance, whereas two-sided communication helps stimulate investors. We also revealed that novelty level can influence strategic choice, indicating that a project with a higher novelty should have a focused target. Our finding suggests a solution to the conflicting conclusions in previous studies on the direct impact of novelty level and target diversification, by explaining the process of novelty-dependent behavioral strategies based on signaling theory.
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