Greed by Algorithm

            The adage about the stock market applies to both human and machine greediness: Bulls make money and bears make money, but pigs get slaughtered.  I am not suggesting that corporations—or academic entrepreneurs—forego profit maximization, or charging what the market will bear.  But consider the following instances where algorithms overreach and in the process tick people off big time.

            In researching hotel accommodation for my daughter’s “White Coat” ceremony marking the start of her 4 year vet school adventure at Virginia Tech, I quickly identified peak demand conditions for Blacksburg and a 50 mile radius. OK I get this: high, inelastic demand equals high prices even for 2 star motels that usually fetch $50 off peak.  But does Marriott do anything but generate ill will with an algorithm triggering a $968-1069 nightly rate for a Residence Inn?

            Countless so-called behavioral economic experiments prove that we humans do not operate as utility maximizing, cost minimizing, rational actors.  We often forego gains so that cheaters do not share or exceed what rule compliant actors get.  I suspect that many people seeing this kind of price quote from Marriott think less of the company perhaps to the point of avoiding its offerings even when quoted rates are fair and competitive. 

            Way to go Marriott algorithm writers!

            Of course, Marriott does not have a monopoly on foolish algorithmic outcomes.  Amazon has an algorithm that occasionally prices an easily procured book at prices no one would pay.  See Amazon Algorithm Price War Leads to $23.6-Million-Dollar Book Listing, https://www.pcmag.com/article2/0,2817,2384102,00.asp.

            Most times, well-written algorithms manage to squeeze out every last dollar of consumer surplus in a transaction.  So-called surge pricing taught a student of mine how elasticity-based rates work far better than I ever could.  During Spring Break in Florida, an Uber ride to Miami Beach cost a quite reasonable $17.  At 2 a.m. the same ride was quoted in excess of $400       .  The student gutted it out until the rate dropped to $147.