<p><span style="font-weight: 400;">The display of personal information in crowdfunding campaigns is vital for facilitating trust; however, this information often communicates the racial identity of the fundraiser. We study the relationship between racial cues and crowdfunding success. Using data from more than 100,000 projects gathered from Kickstarter.com, we categorized racial cues as creator-based versus product-based. For each category, we derived racial cues in two different mediums: photo vs. textual. We used propensity score matching to estimate the effects of racial identity across racial groups, categories, and mediums. We found that the category of racial cues is associated with crowdfunding success. Projects with either creator-based or product-based cues of African American identity had lower success rates. In contrast, creator-based cues of Asian identity were associated with lower levels of success whereas product-based cues were associated with increased success. Furthermore, when product-based cues and creator-based cues were misaligned, we found that the outcomes more closely followed those associated with product-based cues, suggesting that backers are more attuned to product attributes. Our results also suggest that racial anonymity correlates with higher success rates, as compared to African American and Asian racial cues. Our study contributes to the understanding of racial identity on digital platforms across multiple contexts, mediums, and racial groups.</span></p>
Who Are You and What Are You Selling? Creator-Based and Product-Based Racial Cues in Crowdfunding
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SKU
46.4.13
Publication History
Received: October 11, 2017
Revised: June 27, 2018; February 6, 2020; August 12, 2021; February 17, 2022
Accepted: March 13, 2022
Published Online as Articles in Advance: November 23, 2022
Published in Issue: December 1, 2022
Abstract
Additional Details
Author | Lauren Rhue and Jessica Clark |
Year | 2022 |
Volume | 46 |
Issue | 4 |
Keywords | Crowdfunding, empirical analysis, diversity, text mining, matched sample, econometrics, sharing economy, racial bias |
Page Numbers | 2229-2260 |