2007 Practice Prize DVDs
WINNER: 07.01 “Pricing Digital Content Product Lines: A Model and Application for the National Academies Press”
by P K Kannan of the University of Maryland, Barbara Kline Pope of the National Academies Press and Sanjay Jain of Texas A&M University.This work involves a specialist publisher, the National Academies Press, that was provided an opportunity to distribute multiple formats of its content via the Internet. While digital copies such as pdf files are possible substitutes for printed books, there is complementarity in the form of some consumers buying bundles of both. The authors develop a pricing model for both product forms (separately and together), allowing for both substitution and complementarity effects. The model is then calibrated using an on-line experiment testing different product and bundle prices. The results of this calibration are then validated using actual sales data after the model was implemented. The work both demonstates how to model the bundling problem and makes a substantive contribution in an important substantive area, addressing the distribution and pricing of digital and hard copy products, an increasingly important problem facing content providers.
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07.02 “Marketing Mix Recommendations to Maximize Value Growth at P&G Asia-Pacific.”
by V Kumar, Jia Fan (University of Connecticut), Rohit Gulati, and P Venkat (P&G Asia Pacific)
The team worked with Proctor and Gamble in India to optimize its marketing mix for higher profits in the Indian heavy-duty detergent market. One of the biggest challenges in executing this study was to come up with a modeling framework that would not only accommodate the complexity in the data structure but also capture the uniqueness of how each SKU would respond to the marketing-mix elements over time. By understanding both the market structure (in terms of the different pricing tiers in the market) and the effect of pricing on distribution, the study provided key strategic guidelines so that Proctor and Gamble was able to increase the price and distribution of certain SKUs. Consequently, significant gains in profits were realized in this market.
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07.03 “PIN Optimal Auction Vehicle Distribution (ODAV) System: Applying Price Forecasting, Elasticity Estimation, and Genetic Algorithm to Used Vehicle Distribution”
by Jie Du, Lili Xie, and Stephan Schroeder (J. D. Power and Associates)
Automotive manufacturers and their captive channels need to remarket their rental fleet return vehicles and lease return vehicles at auctions throughout the US Realized prices depend on a number of characteristics related to the car (make, model, features and condition), the mix of consumers in each geographic area, and local dynamics of supply and demand. Many of these factors are changing quite rapidly. J. D. Power’s model generates a vehicle distribution plan to maximize the auction net profit by considering the auction price arbitrage across the country, costs associated with the vehicle shipping, and business constraints simultaneously. A number of automotive manufacturers and their captives use the system each day to allocate their incoming return vehicles and realize substantial savings over the previously implemented system.
