The past few years have witnessed the increasing
ubiquity of user-generated content on seller reputation and product
condition in Internet based used-good markets. Recent theoretical
models of trading and sorting in used-good markets provide testable
predictions to use to examine the presence of adverse selection and
trade patterns in such dynamic markets. A key aspect of such
empirical analyses is to distinguish between product-level
uncertainty and seller-level uncertainty, an aspect the extant
literature has largely ignored. Based on a unique, 5-month panel
dataset of user-generated content on used good quality and seller
reputation feedback collected from Amazon, this paper examines trade
patterns in online used-good markets across four product categories
(PDAs, digital cameras, audio players, and laptops). Drawing on two
different empirical tests and using content analysis to mine the
textual feedback of seller reputations, the paper provides evidence
that adverse selection continues to exist in online markets. First,
it is shown that after controlling for price and other product and
seller-related factors, higher quality goods take a longer time to
sell compared to lower quality goods. Second, this result also holds
when the relationship between sellers’ reputation scores and time to
sell is examined. Third, it is shown that price declines are larger
for more unreliable products, and that products with higher levels
of intrinsic unreliability exhibit a more negative relationship
between price decline and volume of used good trade. Together, our
findings suggest that despite the presence of signaling mechanisms
such as reputation feedback and product condition disclosures, the
information asymmetry problem between buyers and sellers persists in
online markets due to both product-based and seller-based
information uncertainty. No consistent evidence of substitution or
complementarity effects between product-based and seller-level
uncertainty are found. Implications for research and practice are
discussed.
Keywords: Information uncertainty, adverse selection,
user-generated content, text analysis, seller reputation, product
quality, used goods, electronic markets, information asymmetry,
trade patterns