Journal of Management Information Systems

Volume 39 Number 1 2022 pp. 159-186

Platform Policies and Sellers’ Competition in Agency Selling in the Presence of Online Quality Misrepresentation

Pu, Jingchuan, Nian, Tingting, Qiu, Liangfei, and Cheng, Hsing Kenneth


On e-commerce platforms, consumers rely heavily on online reviews, sales volume, and social media discussions to infer product quality. As a result, the past decade has witnessed an explosive growth of seller-initiated misrepresentation of quality through fake reviews, fake sales, and fake posts. We develop an analytical model to investigate sellers’ competition in quality misrepresentation in agency pricing and the platform’s policies. The platform can discourage sellers’ quality misrepresentations by increasing the cost of misrepresentation or implementing a more lenient product return policy. We find that while a stricter anti-misrepresentation policy deters the misrepresentation of the high-quality seller, such a strategy may unintendedly incentivize the low-quality seller to misrepresent the quality more. Furthermore, increasing return leniency deters low-quality seller’s misrepresentation in a wider range of market conditions than increasing the misrepresentation cost. We show sellers’ online quality misrepresentation behaviors in a competitive setting, and our results have practical implications for platform policies.

Key words and phrases: E-commerce platforms, quality misrepresentation, agency selling, product returns, online reviews, platform policies, analytical modeling, online platforms