Consumer surplus in eBay

A paper that we wrote on “Consumer surplus in online auctions” was recently accepted to the leading journal Information Systems Research. Reuters interviewed us about the paper (Study shows eBay buyers save billions of dollars), which is of special interest these days due to the change in CEO at eBay. Although the economic implications of the paper are interesting and important, the neat methodology is a highlight in itself. So here’s what we did: Consumer surplus is the difference between what a consumer pays and what s/he was willing to pay for an item. eBay can measure the consumer surplus … Continue reading Consumer surplus in eBay

New “predictive tools” from Fair Issac

An interesting piece in the Star Tribune: Fair Isaac hopes its new tools lessen lenders’ risk of defaults was sent to me by former student Erik Anderson. Fair Issac is apparently updating their method for computing FICO scores for 2008. According to the article “in the next few weeks [Fair Issac] will roll out a suite of tools designed to predict future default risk”. The emphasis is on predicting. In other words, given a database of past credit reports, a model is developed for predicting default risk. I would be surprised if this is a new methodology. Trying to decipher … Continue reading New “predictive tools” from Fair Issac

Data Mining goes to Broadway!

Data mining is all about being creative. At one of the recent data mining conferences I recall receiving a T-shirt from one of the vendors with the print “Data Mining Rocks!” Maybe data mining does have the groove: A data mining class at U Fullerton (undergrad business students) instructed by Ofir Turel, has created “Data Mining – The Musical“. Check it out for some wild lyrics. Continue reading Data Mining goes to Broadway!

Cycle plots for time series

In his most recent newsletter, Stephen Few from PerceptualEdge presents a short and interesting article on Cycle Plots (by Naomi Robbins). These are plots for visualizing time series, which enhance both cyclical and trend components of the series. Cycle plots were invented by Cleveland, Dunn, and Terpenning in 1978, and seem quite useful. I have not seen them integrated into any visualization tool, although they definitely are useful and easy to interpret. The closest implementation that I’ve seen (aside from creating them yourself or using one of the macros suggested in the article) is Spotfire DXP‘s hierarchies. A hierarchy enables … Continue reading Cycle plots for time series