Configurational paths to sponsor satisfaction in crowdfunding

Bo Xu, Haichao Zheng, Yun Xu and Tao Wang

Journal of Business Research, 2016, vol. 69, issue 2, 915-927

Abstract: Crowdfunding is a new financing channel for small- and medium-sized enterprises and individual entrepreneurs to raise funds for innovation projects online. Different from business research based upon the conventional symmetric thinking, this paper investigates sponsor satisfaction in crowdfunding using asymmetric analytics. Cross-tabular and qualitative comparative analysis (QCA) were conducted for the antecedent factors, including delivery timeliness, product quality, project novelty, sponsor participation and entrepreneur activeness, and sponsor demographics. The results show that cases contrary to their main effects occur, and configurational models with high predictive validity are sufficient for predicting sponsor satisfaction or dissatisfaction in crowdfunding projects. This paper supports the complexity theory and deepens crowdfunding research by providing insights into sponsor satisfaction from asymmetrical perspective. It also makes practical implications for crowdfunding platforms and entrepreneurs.

Keywords: Crowdfunding; Sponsor satisfaction; Asymmetric analysis; QCA; Complexity theory (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (40)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0148296315002714
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:69:y:2016:i:2:p:915-927

DOI: 10.1016/j.jbusres.2015.06.040

Access Statistics for this article

Journal of Business Research is currently edited by A. G. Woodside

More articles in Journal of Business Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().