Skip navigation
Please use this identifier to cite or link to this item: http://hdl.handle.net/2451/27747
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

Files in This Item:
File Description SizeFormat 
CPP-03-07.pdf384.78 kBAdobe PDFView/Open


Items in FDA are protected by copyright, with all rights reserved, unless otherwise indicated.