Bidding strategically on eBay

A while ago I discovered that eBay makes the last three months of sold as well as completed listings available (just click on the little "Advanced" tab on the right of the search button). Learning about this feature hugely changed how I shopped on eBay. While you can do a search of the current listings to try to get a sense of your options, you can get a much more accurate picture of what the market is doing by looking at what people have historically paid. Here are a few ways I use the historical data to decide how to bid:

• If I see a "buy it now" item that is around the lowest price the auctions typically end at, I can simply use that option.
• I can figure out what the market rate is for the item and set my proxy bidding maximum at that amount. If I get outbid, I just try the same price on a similar auction.
• I can figure out how often the item is available via eBay and if I should try to find a good deal there versus looking elsewhere.

If you aren't familiar with this feature, I highly recommend giving it a try. Also, if you have any other ideas for how to use this tool, feel free to share them in the comments.

Logistical planning

As I learned when searching Airbnb for somewhere to stay during the INFORMS Annual Meeting, the pope is visiting Philly this year. He will be there September 26-27 for the "World Meeting of Families Congress," and there has been an incredible amount of logistical planning to both ensure security and allow for the large numbers of people they expect to attend the pope's events.

This link covers a lot of the changes that have been planned which include: limited or no driving and parking (some of which started today!), reduced subway / trolley / bus routes, and extra security to get close to downtown at all. They also have planned for a lot of extra services including porta-poties, free wifi, and even 500 "teenage athletes" to help push around people in wheelchairs. And that doesn't even get into the "logistical nightmare" that would arise if a thunderstorm rolls in.

Everything should be long back to normal by the time I get there... But I am happy to take advantage of the extra capacity on Airbnb as a result of the visit.

Second-order bias in models

You may have heard about the controversy surrounding the SAT over the years since people of color have always done worse on the test. The test-writers have attempted more and more to avoid racial bias in the results. It is clear that the test used to have a significant racial bias. It is less clear if that this is still the case today.

This kind of question is studied in the field of "disparate impact." Salon.com just published this article talking about that field and the risks of having disparate impact especially when you trust algorithms to make the decisions. I would call the old SAT an example of first-order bias, and the remaining issues in the test mostly second-order bias.

The problem is clearly not simple to solve. However, hopefully with time the very data analysis techniques that currently lead to biased decisions can ultimately be used to avoid bias in outcomes.

On "Managerial Insight"

Professor Chris Tang asked the operations research community to come together and provide a definition of "Insight." In our field, most of the top journals ask authors to consider the potential managerial insights available as a result of their paper. Ostensibly clearly stating the insights will save the reader some effort in figuring out how they can use the results in the paper, and perhaps will also ensure that the paper has real-world implications.

When a fellow PhD student first introduced me to the idea of insight, I understood it to simply be the practical implications of your work. Since then I have learned a lot about how OR is used in practice. It seems that occasionally our models are directly implemented. Most of the time though, there is some reason decision makers would not want to directly implement the output of the model. Maybe the optimization problem is missing some important piece that keeps it from being directly implementable. Maybe the model is far too complex to be worth solving exactly. Or maybe the whole goal of the model is simply to provide the decision maker with a collection of options to decide between.

Given this understanding, I now think of insights as the results that can help get a better understanding of the problem even without actually implementing the model. For illustrations of insight, physics provides some good examples:

• Heavier objects do not fall faster just because they have more mass.
• Doors open more easily when you push near the handle instead of near the hinge.
• Going uphill takes more energy than going downhill.

Behind each of these examples are equations which we may or may not care about in any particular situation. But the insight provided is accessible and useful whether or not we need to make a quantitative decision.

One additional point. While insights may come from the results of optimization models, sometimes simply formulating the model in a clever way can help provide insights. To use an OR example, Michael Trick recently posted on the topic of complete enumeration as an argument for complexity. He points out that just because complete enumeration is one way to find the optimal solution does not mean the underlying problem is hard. In the same way, clever formulations of hard problems can bypass a lot of unnecessary complexity.