July 20, 2009
Fines: cosmetic incentives?
The State of New York announced settlement of a lawsuit it filed against LifeStyle Lift for "astroturfing" (paying its employees to "flood" the net with false positive reviews). The company will pay a $300,000 fine, plus an undisclosed amount of New York's legal costs.
Lifestyle Lift is a facial cosmetic surgery procedure that purports to be quicker and safer than traditional facelift procedures, with shorter recovery time and cost.
According to the NY State Attorney General's office, employees published anonymous reviews to the web to trick potential customers. They did this on legitimate review sites, and they also created standalone web sites that purported to be independent, where they created all of the "reviews" or edited reviews by third parties to skew the discussion.
See also this New York Times story.
Laws that impose possible fines or other punishments (such as jail time) are an incentives-based approach to shape behavior. A simplified version of the idea is that if the expected cost of the punishment, times the likelihood that the agent will be caught and punished (discounted to present value), is greater than the expected benefit from the improper behavior, it will not be in the agent's self-interest to engage in the behavior.
One concern about using legal punishment incentives is that they involve multiple sources of uncertainty (about punishment size and likelihood of being caught and punished), and that seemingly large ex post punishments may not be that much of an ex ante deterrent.
Lifestyle Lift was fined $300,000 plus legal costs. Suppose that it had known with certainty that it would have to pay this fine several years after earning money as a result of publishing false reviews. Would it have chosen to be honest? That depends, of course, on how many consumers it falsely induced to get the procedure, and the profit on the procedure. According to current customer comments on one review site that claims to have been abused (RealSelf.com), the procedure costs on the order of $5000, only some portion of which will be profit. Suppose that the profit rate is 10% (about $500): then of the "nearly 100,000" customers it claims to have served, Lifestyle Lift would have had to falsely induced at least 600 of them. If many more than 600 had been tricked, then even knowing the fine would occur may not have been sufficient deterrent. Multiply that by the uncertainty and the number of customers they had to successfully trick might have been less (there were also uncertainties about the benefits of lying that would have to be taken into account).
There is at least one reason the incentive might be greater: harm to Lifestyle Lift's reputation. For example, this settlement was reported in the New York Times, and the story is starting to circulate through blogs and other information sources.
On RealSelf.com, where presumably the false reviews have now been removed, 65% say that the procedure is not worth it. Meanwhile, Lifestyle Lift now posts a badge and promised "Internet Code of Conduct" on its own web site, stating that it "is proud to take a leadership role in establishing new standards of Internet conduct and communications." I don't know when that "code" first appeared, but it seems likely that this is an example of trying to turn lemons into lemonade.
July 17, 2006
ICD to establish trust for transactions
Huberman, Wu and Zhang just published an article in Netnomics called "Ensuring trust in one-time exchanges: the QoS problem". (Folks at UM can access through the library's "Electronic Journals" access page.) They are interested specifically in the problem of purchasing from an IT service provider who does not have a verifiable reputation; this is a generic problem in transactions, but their modeling makes specific assumptions for this particular situation.
Summary from the paper:
In our model, a quality of service contract describes the likelihood that the service provider delivers the promised service. We have designed a mechanism that forces the provider to reveal his true assessment of the probability that he will be delivering a given service in a single interaction with a user/customer. We also solved the complementary truthtelling reservation problem of obtaining from the user his assessment of the true probability that a given level of resources will be required at the time of their delivery. In both cases, our mechanisms use a contingent contract to elicit true revelation of both QoS and likelihood of use through a pricing structure that forces the parties to make accurate assessments of their ability to do what they commit to.
They also apply the problem to situations in which service providers might overbook.