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The value of backers’ word-of-mouth in crowdfunding projects filtering: an empirical investigation

  • Haichao Zheng
  • , Zihao Qi
  • , Xin Luo
  • , Liting Li
  • , Bo Xu

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Abstract

The current study aims to investigate whether backers’ electronic word-of-mouth (eWOM) is a valuable input when it comes to generating collective intelligence for projects filtering in crowdfunding. Based on theories of collective intelligence and WOM, we developed a research model and conducted an empirical study using a cross-section dataset with 845 crowdfunding projects and a panel dataset of the funding dynamics of those projects. The results indicated that backers’ negative WOM rather than positive WOM can effectively predict project implementation performance. Besides, for entrepreneurs with a high reputation, negative WOM has stronger predictive power for the complaints of product quality. We also found that projects with more accumulated negative WOM tend to attract fewer subsequent backers. Compared with positive WOM, negative WOM has a stronger effect on subsequent investments in a crowdfunding project. Finally, positive WOM can reduce the diffusion of responsibility effect in crowdfunding, that is, a backer is less likely to take responsibility for investing in a project when others have already backed it. Based on these findings, we conclude that backers’ WOM, especially the negative WOM, contributes to projects filtering in crowdfunding.

Original languageEnglish
Pages (from-to)757-782
Number of pages26
JournalElectronic Commerce Research
Volume20
Issue number4
DOIs
Publication statusPublished - 1 Dec 2020
Externally publishedYes

Keywords

  • Collective intelligence
  • Crowd-based filtering
  • Projects filtering
  • Reward-based crowdfunding
  • Word-of-mouth

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