Scarcity Strategy in Crowdfunding: An Empirical Exploration

Lusi Yang, Zhiyi Wang, Jungpil Hahn

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Scarcity-based marketing strategy has been increasingly adopted in reward-based crowdfunding in the form of reward limits, whereby project creators are able to restrict the quantity of contributors in each reward tier. This study uncovers the effect of reward limits in eventual and concurrent funding performance. Specifically, we performed campaign and campaign-day level analysis. At the campaign level, we find that setting reward limit at the beginning of a campaign is beneficial for final funding outcomes across four different performance measures. The number of limited reward tiers is shown to have an inverted U-shaped relationship with fundraising performance. Potential endogeneity issues are addressed with propensity score matching and the Heckman selection model. At the campaign-day level, we find incorporating new limited reward tiers is helpful for attracting new backers, but having reward tiers being “sold out� will demotivate subsequent backers to contribute thus lead to lower funding speed in subsequent days.

Original languageEnglish (US)
Title of host publicationICIS 2017
Subtitle of host publicationTransforming Society with Digital Innovation
PublisherAssociation for Information Systems
ISBN (Print)9780996683159
StatePublished - 2018
Externally publishedYes
Event38th International Conference on Information Systems: Transforming Society with Digital Innovation, ICIS 2017 - Seoul, Korea, Republic of
Duration: Dec 10 2017Dec 13 2017

Publication series

NameICIS 2017: Transforming Society with Digital Innovation

Other

Other38th International Conference on Information Systems: Transforming Society with Digital Innovation, ICIS 2017
Country/TerritoryKorea, Republic of
CitySeoul
Period12/10/1712/13/17

Keywords

  • Crowdfunding
  • Empirical study
  • Exclusivity
  • Reward limit
  • Scarcity strategy

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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