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An Online An Online Consumer-to-Consumer Consumer-to-Consumer

Trading CommunityTrading CommunityPresentation is based on Melnik research:

“Does a Seller’s eCommerce Reputation Really Matter? Evidence from eBay Auctions” (with James Alm). Journal of Industrial Economics, September 2002. “Reputation, Information Signals, and Willingness to Pay for Heterogeneous Goods in Online Auctions”, (with James Alm). Southern Economic Journal, October 2005.

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eBay: A True Success StoryeBay: A True Success StoryFrom a simple website in 1995 to beingsynonymous with online auctions! 1.9 billion listings in 2005 4.552 billion in revenues 71.8 million active users 96.2 million accounts listed with PayPal*

But what about the economics.....* All information is taken from QIV05 eBay Financial Results report

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Asymmetry of Information Asymmetry of Information Akerlof, 1970 Asymmetry of Information on eBay

Buyer’s problem Uncertainty about delivery of the item (general compliance with the

terms of transaction) Uncertainty about the accuracy in the description of the item

Seller’s problem Payment/return

Past Reputation as a Signal of Current and Future Behavior Theoretical support

Klein and Leffler, 1981; Shapiro, 1983; Allen, 1984; Houser and Wooders, 2000

Experimental support Miller and Plott, 1985; DeJong, Forsythe, and Lundholm, 1985;

Camerer and Weigelt, 1988; Holt and Sherman, 1990

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Reputational Mechanism on eBayReputational Mechanism on eBay

Structure of the mechanism Quantitative

Positive, negative, neutral rating choices only Difficult to manipulate through collusive behavior

Rating left by unique registered eBay users Feedback score = unique positives – unique negatives

Informative Overall eBay experience of the seller Past complain history

Does the reputational measure help overcome asymmetries of information? Is it valued by members of the community? Is it valued by competing communities?

SIMPLE * MEASURABLE * DIFFICULT TO MANIPULATESIMPLE * MEASURABLE * DIFFICULT TO MANIPULATE

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Choice of DataChoice of Data 2002: Homogeneous good study

US $5 1999 Gold Coin in Mint Condition Possibility of encountering a fraudulent seller

2005: Heterogeneous good study US Morgan Dollars in Almost Uncirculated

Condition Accuracy in the description of item-specific

characteristics Possibility of encountering a fraudulent seller

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Modeling ReputationModeling Reputation

P = f (seller’s reputation, X) X – a set of auction specific variables

Transaction costs (shipping, insurance) Time exposure, closing (duration, closing

time/date, day of the week) Supply characteristics (number of available

items) Payment methods

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Empirical formulationEmpirical formulation

Censored observations and the use of Tobit model Fixed price auctions and no-bid auctions

iii XP *

*00 if iiii PPPP * if i

bi

bii PPPP

otherwise *ii PP

• 105 price distributions: Huber-White estimation of robust standard errors

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Estimation ResultsEstimation ResultsCertified Non-certified Non-certified, no scans

rating stat insig $ 0.029 (0.05%) $0.05 (0.084%)negative (1 point) $-3.450 (1.1%) stat insig. -$0.89 (1.5%)rating stat insig $21.848 (37.6%) $36.69 (63.2%)negative $-95.055 (29.0%) stat insig. -$15.76 (27%)rating stat insig $2.009 (3.5%) $3.37 (5.8%)negative $-27.477 (8.4%) stat insig. -$5.25 (9.05%)

1% increase at the mean

increase from 0 to mean

increase from 0 to 1

Mean prices: Certified: $327.50; Non-certified: $58.08

1. Seller’s reputation impacts buyer’s willingness to pay2. In heterogeneous goods: A reduction in available

information increases the premium to positive reputation and the penalty to negative reputation.

3. Negative feedback effect increases with the value of the item

4. Substantial penalty is imposed on new sellers in non-certified coins auctions

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Some Previous FindingsSome Previous Findings

- Lucking-Reiley et al. (1999): 1% increase in rating -> 0.03% increase in willingness to pay

- Houser and Wooders (2002): 10% increase in rating -> 0.17% increase in willingness to pay

- Melnik and Alm (2002): Doubling in rating -> 0.55% increase in willingness to pay

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Conclusions

Non-transferable across communities reputational mechanism in online consumer to consumer communities acts as a club good• Valued by buyers and sellers• Enables a community to overcome

asymmetries of information problem• Establishes a barrier to entry for a competing

community