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Lecture 7

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McGill University
Economics (Arts)
ECON 208
Paul Dickinson

Eco Lecture Great uses for price optimization software. 1.1.1. Avoiding overcrowding. One optimal use for IT pricing software systems is when there is an externality problem. A good example is road congestion pricing, where a city prices roads higher during peak hours to deter drivers from driving then. This is also the case for water parks, theme parks and so on. These are examples of goods that have a very high fixed capacity and highly variable demand, leading to congestion at certain times that they need to manage. 1.1.2. Avoiding spare capacity. The most expensive thing in a restaurant is an empty table Most firms want to operate at something close to full capacity whenever they can. By booking a hotel room, I am directly preventing another customer from taking that hotel room. This trade-off between pricing a room low and selling it now against waiting and potentially selling a room at the last minute for a higher price, has given rise to the practice of revenue management. Revenue can be improved by: • Identifying new pricing fences • Preventing arbitrage across existing pricing fences • Improving customer perceptions of pricing fairness Generally most success stories outside of industries with fixed capacities rest on a better understanding of price elasticities. Theoretically, optimization systems could optimize over cost schedules, but I have come across no software systems that do this very well primarily because managers simply do not know cost schedules. Some problems these systems have faced. (1) Used a price management rather than optimization tool. • Large departmentstore invested in expensive pricing optimization software. Merchandizing set key commands on override and used it predominantly to manage the prices that they set using their ‘super gut’. (2) Limitations to the use of optimization software created for selling airplane seats in industries that have no capacity constraints.. • Example of software that created artificial constraints in order to be able to say that it was optimizing. Case Study: Google Adwords Pricing A lot of these problems are caused because IT systems model people’s pricing behavior in the future as being like it was in the past. They also assume that people will not try and outsmart the pricing software. However, it makes a lot more sense if IT systems instead were focused on giving incentives so that people were actually willing to tell the firm what they were willing to pay. This is what Google has been able to do with its automated auctions for advertising search terms ‘Adwords’ system. By doing this, Google has transformed itself into the market leader in the provision of advertising. Adwords Pricing Process. First, a quick description of the Google search term auction mechanism: • Firms enroll in Adwords • They pick the particular s
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