Social information from friends and experts could help reduce uncertainty in crowdfunding campaigns
BINGHAMTON, NY – Social information gathered from friends and experts, depending on the complexity of the product, can decrease uncertainty in crowdfunding campaigns, according to research from Binghamton University, State University of New York.
Popular crowdfunding sites host many projects that are initiated by first-time entrepreneurs for a variety of creative products. In these projects, funders face a unique uncertainty: seller competence uncertainty. Unlike traditional e-commerce, where products are already finished and ready for shipment, in crowdfunded projects the product still needs to be produced. The seller competence uncertainty captures the uncertainty related to the project initiator’s ability to finish the product.
When people on crowdfunding sites are presented with an information overload and face ambiguity regarding a project, they tend to follow the decisions of others to differentiate the projects they find legitimate from those that they find illegitimate. Current literature postulates that funders make decisions by following the decisions of the crowd, and this herd behavior leads to less than optimal decisions. Having a mechanism that aids decision-making would be beneficial for the long-term success of crowdfunding sites.
The researchers write that crowdfunding sites can integrate social information from experts and friends to assist decision-making.
“The crowdfunding website can extract information from Facebook, and then your Facebook friends will be notified that you have funded a project,” said Surinder Singh Kahai, associate professor in Binghamton University’s School of Management, suggesting possible ways that this information could be leveraged. “Information can also be extracted from sources such as LinkedIn. That way, if you are an engineer funding a computer- or hardware-related project, the crowdfunding platform can give you expertise level.”
Binghamton University researchers Kahai and Ali Alper Yayla, along with Yu Lei from SUNY College at Old Westbury, recruited subjects through Amazon Mechanical Turk, a crowdsourcing internet marketplace, to examine the influence of different reference groups (experts, friends and family, the crowd) at different product complexities. The researchers conducted a controlled lab experiment, designing several webpages to mimic a crowdfunding environment and incorporate the influence of different reference groups. By proposing both implicit and explicit social information, they were able to identify which type of information each reference group provided during the decision-making process. The researchers found that under low product complexity, funders needed more implicit information, and they followed friends over experts and crowd to make pledging decisions. On the other hand, under high product complexity, people needed more explicit information, and they rationalized their pledging behaviors by following experts over crowd and friends.
“We have to look at external sources, specifically reference groups, which include our friends and family, or experts who have expertise in a certain area and the general population,” said Yayla. “When I have to make a decision about which mechanic to bring my car to, I should probably listen to the experts, but instead I listen to my friends or I use a website such as Yelp to read reviews.”
The paper, “Guiding the Herd: The Effect of Reference Groups in Crowdfunding Decision Making,” was presented at the 50th Hawaii International Conference on System Sciences.