A mixed methods approach to understanding funder trust and due diligence processes in online crowdfunding investment
Jones, Helen S. and Moncur, Wendy (2020) A mixed methods approach to understanding funder trust and due diligence processes in online crowdfunding investment. ACM Transactions on Social Computing, 3 (1). 3. ISSN 2469-7826 (https://doi.org/10.1145/3373148)
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Abstract
We report on two studies undertaken to establish the factors that affect funders’ trust and likelihood to invest in crowdfunding campaigns online. Findings from an initial small-scale qualitative study are reported and subsequently triangulated in a larger quantitative survey. Across these studies, we demonstrate the importance of social information within the peer economy, with a strong reliance on other users across the course of the investment decision-making process. Decision-making on whether to invest is informed not only by the content of the crowdfunding campaign page, but also by social influence factors that are present (e.g. liking of the campaigner, reciprocity). It is further shaped by due diligence checks focused on the progression of the prototype for which funding is sought, and by assurances from outside the campaign page – namely on social media. Such assurances center around the importance of social proof, garnered through opinions of previous customers or other funders. The risk here is that much of this information is content that can be faked, and as such a reliance on this may leave potential funders vulnerable. Meanwhile, a genuine lack of prior experience and customer base means that some legitimate campaigners struggle to gain trust from potential investors who are reliant on such social information. Our findings present an empirical grounding to develop future security solutions that (i) protect existing funders and (ii) increase potential funders’ level of trust, to encourage their engagement with legitimate crowdfunding campaigns.
ORCID iDs
Jones, Helen S. and Moncur, Wendy ORCID: https://orcid.org/0000-0002-1485-4723;-
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Item type: Article ID code: 73900 Dates: DateEvent29 February 2020Published30 November 2019AcceptedSubjects: Science > Mathematics > Electronic computers. Computer science Department: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 17 Sep 2020 10:50 Last modified: 16 Dec 2024 02:17 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/73900