five

Descriptive statistics.

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Descriptive_statistics_/26744988
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Reward-based crowdfunding is a typical two-sided platform (fundraiser side and backer side) with high information asymmetry. While existing research indicates that signals from fundraisers and backers can impact crowdfunding performance, the interplay among these signals warrants further investigation. Drawing on signaling theory, this study adopts a configurational perspective and utilizes the fsQCA method and linear regression to investigate the combined effects of fundraiser engagement (update and fundraiser comment), third-party endorsement (backer comment and Facebook sharing), and project preparedness (video, image, and description) on crowdfunding performance. Drawing data from the reward-based crowdfunding platform Indiegogo, this research pointed out that these signals cannot generate better crowdfunding performance alone and examined substitution and complementary effects among different signals. Based on the linear regression and fsQCA results, configurations that lead to high crowdfunding performance are identified. We found that project preparedness must work with other signals to produce high crowdfunding performance. Besides, we summarized these configurations into two patterns that may lead to high crowdfunding performance: a fundraiser engagement-driven pattern and a third-party endorsement-driven pattern. This study contributes a configurational perspective and valuable insights into how signals can work together to mitigate information asymmetry in crowdfunding.
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2024-08-15
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