Projects per year
Given the positive bias toward attractive people in society, online sellers are justifiably apprehensive about perceptions of their profile pictures. Although the existing literature emphasizes the “beauty premium” and the “ugliness penalty,” the current studies of seller profile pictures on customer-to-customer e-commerce platforms find a U-shaped relationship between facial attractiveness and product sales (i.e., both beauty and ugliness premiums and, thus, a “plainness penalty”). By analyzing two large data sets, the authors find that both attractive and unattractive people sell significantly more than plain-looking people. Two online experiments reveal that attractive sellers enjoy greater source credibility due to perceived sociability and competence, whereas unattractive sellers are considered more believable on the basis of their perceived competence. While a beauty premium is apparent for appearance-relevant products, an ugliness premium is more pronounced for expertise-relevant products and for female consumers evaluating male sellers. These findings highlight the influence of facial appearance as a key vehicle for impression formation in online platforms and its complex effects in e-commerce and marketing.
Bibliographical noteThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors acknowledge the financial support of Lingnan University, Hong Kong for this research (FRG 102016/DB18B1).
Ling Peng, Geng Cui, and Yuho Chung share equal authorship.
- beauty premium
- social selling
- ugliness premium
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- 1 Finished
A Machine Learning Approach to Assessing Facial Attractiveness of Profile Pictures and Its Impact in Online Platforms
1/07/18 → 31/12/19
Project: Grant Research
1 item of Media coverage
Press/Media: Research / Knowledge Transfer