Look the Part? The Role of Profile Pictures in Online Labor Markets

Isamar Troncoso () and Lan Luo ()
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Isamar Troncoso: Department of Business Administration, Harvard Business School, Harvard University, Boston, Massachusetts 02163
Lan Luo: Department of Marketing, Marshall School of Business, University of Southern California, Los Angeles, California 90089

Marketing Science, 2023, vol. 42, issue 6, 1080-1100

Abstract: Profile pictures are a key component of many freelancing platforms, a design choice that can impact hiring and matching outcomes. In this paper, we examine how appearance-based perceptions of a freelancer’s fit for the job (i.e., whether a freelancer “looks the part” for the job), as inferred from profile pictures, can impact hiring outcomes on such platforms. Leveraging computer vision techniques and choice models, we analyze six-month data from Freelancer.com (63,014 completed jobs that received 2,042,198 applications from 160,014 freelancers) and find that, above and beyond demographics and beauty, freelancers who “look the part” are more likely to be hired. Interestingly, we do not find a strong correlation between “looking the part” and job performance. Supplementing our large-scale observational study with two choice experiments, we find that (i) the effect of perceived job fit is stronger when reputation systems are not sufficiently diagnostic to differentiate candidates and (ii) that by considering perceptions of job fit, participants are more likely to choose freelancers with fewer reviews, lower ratings, and/or without certifications. Last, we find that “platform recommendations” can only partially mitigate the unintended consequences of profile pictures, and recommending multiple freelancers can further increase the role of “looking the part.”

Keywords: freelancing platforms; profile pictures; reputation systems; platform recommendations; choice experiments; computer vision (search for similar items in EconPapers)
Date: 2023
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