Value Add Pricing – Dynamic Price Descrimination

Key Concepts:

1. Dynamic Price Discrimination with Price Commitment
2. Interruptible Sales (Low Priority Sales)

Conclusions:

1. Efficiency requires a positive probability of empty seats. Pricing to sell out is inefficient.
2. The interruptible good problem breaks up into two separate maximization problems, one for the low

quality good, and one for the difference of the low quality good and the high quality good. In the airline

context, an interruptible good is one that provides the airline greater flexibility with respect to the time of

flight. The cost of delivering a seat reserving greater airline flexibility is automatically lower, and thus is

part of both profit maximization and efficient provision of services.

1. dynamic price discrimination only matters significantly on the last twenty or so sales.
2. Dynamic price discrimination is primarily driven by customer dynamics rather than price discrimination over an existing set of customers.

Ideas:

1. DPDwPC – Dynamic Price Descrimination with Price commitment
   1. Barclays promises us $500,000 a month and we promise them up to 3TB of processing per month (hosting not included)
   2. PWAN – Price with advance notice (3 months of notice or 3 month before we have to start).
      1. We can make a pricing model that gives customers an excellent discount if they are able to commit to us the volume with enough lead time to escape prod/pm capacity constraints.
      2. Interruptible transmission rights –
         1. It is quite common in pipeline transport where it goes by the name of interruptible transmission rights, as opposed to firm (guaranteed) rights Priceline.com sold a kind of interruptible service, where they sold the ticket well in advance but didn’t specify the time of the flight until a day or so in advance.

What is Dynamic Pricing?

Dynamic pricing, which is also known as yield management or revenue management, is a set of pricing

strategies aimed at increasing profits. The techniques are most useful when two product characteristics

co-exist. First, the product expires at a point in time, like hotel rooms, airline flights, generated

electricity, or time-dated (“sell before”) products. Second, capacity is fixed well in advance and can be

augmented only at a relatively high marginal cost. These characteristics create the potential for very large

swings in the opportunity cost of sale, because the opportunity cost of sale is a potential foregone

subsequent sale. The value of a unit in a shortage situation is the highest value of an unserved customer.

Forecasting this value given current sales and available capacity represents dynamic pricing.

What is covered in this paper:

This paper contributes to our understanding of yield management in five ways. First, it provides an extensive survey

of yield management research in operations research journals. Second, we explore an existing model of

Gallego and van Ryzin (1994) that has a number of desirable properties, including closed form solutions

and sharp predictions, to address dynamic pricing considerations. Third, most of the literature assumes

demand takes a convenient but unlikely form. We consider the implications of constant elasticity of

demand and demonstrate some new inequalities concerning this more standard case. We examine this

case in the context of an efficient allocation, rather than the profit-maximizing allocation, and show that

many of the conclusions attributed to profit-maximization are actually consequences of the dynamic

efficiency. Fourth, we take a new look at dynamic pricing from the perspective of selling options. A

problem airlines face is that late arrivals may have significantly higher value than early arrivals,

suggesting the airline ought to sell two kinds of tickets: a guaranteed use ticket and a ticket that can be

delayed at the airline’s request. Fifth, we’ve collected airline pricing data and generated stylized facts

about the determinants of pricing, facilitating the evaluation of models.

Yield Management VS. Made-To-Order (I think we are made-to-order)

Sridharan (1998) describes the use of yield management in manufacturing situations with higher demand than capacity, discussing three methods of increasing efficiency and revenue: capacity rationing based on price classes, increased coordination between marketing and manufacturing, and subcontracting.

Yield management applications in the made-to-order (MTO) manufacturing industry include Harris and

Pinder (1995), Sridharan (1998), and Barut and Sridharan (2004). Both MTO firms and service providers

such as airlines face the problem of effectively utilizing a fixed capacity under uncertain or high demand

in order to maximize revenue, and thus many yield management results are applicable to the MTO

manufacturing industry. However, MTO manufacturing is different on the key points of finite time

horizon and unchanging capacity. The horizon is infinite, since the factory never stops all operations at a

specific time or sets a common deadline for all activity, and the capacity is not fixed, in that as orders are

completed, capacity is replenished. Thus, the MTO problem is more of a “stock out” problem than a

yield management problem. Harris and Pinder (1995) discuss the applicability of traditional yield

management to MTO manufacturing and its managerial implications and develop a relevant theoretical

framework using price classes based on unit-capacity rates.

Link:

http://vita.mcafee.cc/PDF/DynamicPriceDiscrimination.pdf