Understanding fraud with respect to Internet auctions is especially important because the oft-cited
“network externality” in which having large numbers
of buyers leads to large numbers of sellers, which leads
to even more buyers, and so on. It is based upon the
knowledge that the winner of the auction will receive
what he or she was expecting. If more than a handful
of buyers perceive that the system does not work in a
fair and neutral manner, the entire network effect
may start unraveling.
If the claim of such a low level of fraud were true,
an auction site could encourage a higher level of buyer
activity (and prices bid) by charging a minimal surcharge on the final winning bid to provide automatic
insurance to buyers. Analyzing one auction site, we
found that a one-dollar increase in the final winning
bid translates into over $700 million in annual dollar
volume. A surcharge of one promille per dollar of the
final price above the additional transaction costs such
as bookkeeping, investigation of claims, and issuing
of compensation should be enough to provide insurance and to leave ample additional profit for the auction site operator. The fact that insurers do not offer
such policies calls into question industry’s estimates of
This procedure is not as simple as it sounds, as having automatic insurance would have an effect on the
behavior of both buyers and sellers. Buyers will be
willing to tolerate a higher level of risk and bid higher
even for unknown sellers, or sellers with lower levels
of reputation. Another complication is that it creates
incentives for crooked sellers and buyers to form
coalitions in which they swindle the auction operator
or the insurance entity. The advantage of an auction
site operator compared to the occasional buyer or
seller is that the operator has the resources and experience to develop methodologies that detect and
reduce such swindling operations to a minimal level.
By providing automatic insurance, the auction site
operator would benefit from the higher level of volume in bidding activity.
We concentrate on buyers being swindled. In our
study we discovered that sellers face a similar problem
of cheating; however, auction houses have devoted
extensive resources toward protecting sellers, but have
invested limited effort into protecting buyers. Why?
We contend that if sellers do not put items up for auction, the site cannot survive, while bidders/buyers on
their own do not justify the existence of an auction
Another factor involves the fact that most sellers
use the auction site multiple times (in many cases,
thousands of times). As a result they develop experience and methods that protect them. Bidders, on the
other hand, have limited experience with the auction
process and do not have the expertise to protect themselves. 1 For example, in most auction sites, sellers do
not ship a product to the buyer until the buyer has
paid for the product.
We employed a variety of methods to undertake an
exploratory investigation of Internet auction fraud.
We performed a literature review of prior empirical
studies on Internet fraud and auction fraud. This led
to a preliminary and exploratory survey conducted
in 2003. Our survey results also helped guide our
participant-observation exploration: We bought and
sold on major auction sites from 2003–2005 to better understand how swindlers work and what actions
might be taken by the auction houses and by buyers.
We also interviewed bidders and sellers that contacted us through our own buying and selling.
In our exploratory pilot study (see [ 5]), we surveyed 1,298 winners of Internet auctions at a major
auction site to see whether they received what they
were expecting. The respondents came from 14 different item categories and a full range of prices. We
asked primarily two questions and collected other
information from the auction site itself.
1. Did you receive any item after you won the auction in question?
2. If you did receive an item, was it what you were
We interviewed willing respondents to our survey. It
was difficult to gather the data using automatic
means, so we did everything manually. Generally
speaking, auction houses put many obstacles to prevent automatic data gathering for such a research
investigation. They limit the number of interactions
one can have with other members per day. Thus, it
is not obvious how to do such a study.
Staying within the rules set up by the auction
houses, we were prevented from using mechanical
methods such as Web crawlers; otherwise, it would
have been much easier to contact a large number of
auction winners. Further, the auction houses are willing to give researchers information, but what they
offer is mostly meaningless for such a study. For
example, looking simply at feedback does not convey
much information. It carries a value of 0, neutral, or
1, so there is no magnitude. For example, a “winner”
in Athens, Greece, whom we talked to lost close to
This can be ascertained by observing the distribution of the number of transactions
or the number of feedback ratings for sellers and buyers.