Afraid of Niche, Tired of Mass: Atypical Idea Combination on Crowdfunding Platform

37 Pages Posted: 9 Aug 2022 Last revised: 28 Mar 2023

See all articles by Yu Kan

Yu Kan

University of Washington - Department of Information Systems and Operations Management

Yifan Yu

The University of Texas at Austin; Amazon

Yang Jiang

Nanjing University - School of Business

Yong Tan

University of Washington - Michael G. Foster School of Business

Date Written: August 3, 2022

Abstract

A new idea usually follows a stream of similar ideas yet simultaneously combines atypical elements from ideas outside this stream. A successful business idea usually balances between familiarity and atypicality. To investigate the relationship between atypicality innovation and crowdfunding project performance, we analyzed 1,826 crowdfunding projects with 1,062,182 donors, 1,087 organizers and 281,763 comments on one of the largest crowdfunding platforms in China. By text mining approach, we build a similarity network of crowdfunding projects to measure the degree of atypicality innovation for these projects. Using a double machine learning model, we find that there exists an optimal pattern of idea combination that balances between familiarity and atypicality. The atypical combination of mainstream and niche ideas has a significant positive effect on the individual project’s funding. This type of projects is likely to gain unexpected success, i.e., receives funding that is five times more successful than other projects on average. We also find the potential reasons that cause the poor performance of niche and mainstream projects. Donors are more conservative due to the high risk of niche projects and driven away by the monotonous repetition of mainstream projects. Our work provides key insights on how to generate successful business ideas with atypicality innovation.

Keywords: atypical, double machine learning, crowdfunding, creativity

Suggested Citation

Kan, Yu and Yu, Yifan and Jiang, Yang and Tan, Yong, Afraid of Niche, Tired of Mass: Atypical Idea Combination on Crowdfunding Platform (August 3, 2022). Available at SSRN: https://ssrn.com/abstract=4180052 or http://dx.doi.org/10.2139/ssrn.4180052

Yu Kan (Contact Author)

University of Washington - Department of Information Systems and Operations Management ( email )

Box 353200
Seattle, WA 98195-3200
United States

Yifan Yu

The University of Texas at Austin ( email )

2317 Speedway
Austin, TX Texas 78712
United States

Amazon ( email )

Yang Jiang

Nanjing University - School of Business ( email )

Nanjing, Jiangsu 210093
China

Yong Tan

University of Washington - Michael G. Foster School of Business ( email )

Box 353226
Seattle, WA 98195-3226
United States

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