1. Employing and Evaluating Dynamic Pricing Strategies Joan Morris MS Thesis Proposal Research Hour, 11/30/00

2. 2 Question In a finite, fluctuating marketplace, where each seller has a finite number of days to sell a finite number of goods, and Sellers use agents to make dynamic pricing decisions, How does a seller develop and evaluate pricebot strategies?

3. 3 Answer Use market simulator as evaluation tool Use several specific market scenarios for evaluation Model real-world consumer behavior within the simulator Implement and evaluate agent strategies

4. 4 Why Dynamic Pricing? Consumers are willing to pay different prices In a fixed-price marketplace, seller is forced to choose price point Dynamic marketplaces capture demand elasticity

5. 5 Why Agents? Because agents can perform tasks for you! As markets move more rapidly, a seller will be unable to make timely pricing decisions for each individual transaction. Maybe agents can make better (more profitable) decisions than a human?

6. 6 Why Simulate? In order to provide practical information to sellers, we look at real-world scenarios. Simulations provide numerical results for specific situations. Theoretical analysis can solve for the optimal solution, but difficult to apply to real-world.

7. 7 Question & Answer (again) Q: How does a seller develop and evaluate pricebot strategies? A: Market Simulator Market Scenarios Consumer Behavior Agent Strategies

8. 8 Market Simulator Simulation Revenue results Market behavior Consumer behavior Market variables Seller strategies INPUTS OUTPUTS

9. 9 Market Scenarios Each market scenario has: Finite number goods Finite amount of time Changing value of goods: either increasing, decreasing, or fluctuating Many examples of markets that behave this way!

10. 10 Market Scenarios 1. Airline auctioning off airline tickets Auction, ascending value, monopoly, agent varies price and num of seats for auction 2. Theatre selling play tickets Posted-price, fluctuating value, monopoly, agent varies price 3. Grocer selling fruit Posted-price, descending value, competitive market, agent varies price and num of goods

11. 11 On a single day, a fixed demand curve Consumer demand modeled in a uniform distribution around average bid amt Every day, the demand curve will be different, either increased or decreased Consumer Behavior: basic

12. 12 Consumer Behavior: real-world Evidence that e-markets will not result in price wars, because of: Search costs of comparison shopping [K. Clay] Brand loyalty [E. Brynjolfsson] Flexible valuation [D. Ariely]

13. 13 Agent Strategies Derivative Following – examine own behavior Myopically Optimal – analyze entire market and make best response Game Theoretic – based on competitor behavior, make decision Reinforcement Learning? – over time, agent learns which strategy decisions are more profitable

14. 14 Research Goals With 3 market scenarios, 3 consumer behaviors, and 3 agent strategies => 3*3*3 matrix of possible situations. Goal: Make conclusions about the success of the strategies under different market conditions. Goal: Create an interface for allowing a “seller” to interact with the simulator to make his/her own conclusions.

15. 15 Related Work Agent strategy simulations: Greenwald, Kephart, Deck, Brooks Optimal market allocation with finite goods and time: Wellman Real-world application of automated pricing decisions (agents): airline industry, car rentals

16. 16 Questions? Comments?