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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/27747
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| Title: | Internet Exchanges for Used Goods: An Empirical Analysis of Trade
Patterns and Adverse Selection |
| Authors: | Ghose, Anindya |
| Keywords: | Information uncertainty
adverse selection
user generated content
text analysis
seller reputation
product quality
used goods
electronic markets
information asymmetry
trade patterns |
| Issue Date: | 6-Nov-2008 |
| Series/Report no.: | CeDER-PP-2007-03 |
| Abstract: | 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 productbased 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. |
| URI: | http://hdl.handle.net/2451/27747 |
| Appears in Collections: | CeDER Published Papers
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