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1. Introduction
2. Research objective
3. Literature review
4. Our integrated stochastic model approach
5. Fundamental kernel of our model: latent WTB
6. Data description
7. Empirical findings: number of bidders per auction
8. Empirical findings: number of bids per auction
9. Empirical findings: bid time distribution
10. Empirical findings: winning bid time
11. Empirical findings: bid amount
12. Empirical findings: "Buy-It-Now" (BIN) feature
13. Conceptual model development
14. Determining the latent competition set
15. Latent bidders
16. Latent bidders: data windowing approach
17. Model development: rates for bid speed
18. Model development: whether
19. Model development: who
20. Model development: when / who
21. Model development: how much
22. Empirical applications
23. Auction design effect on WTB
24. Seller reputation effect on WTB
25. Bidder characteristics effect on WTB
26. Bid characteristics effect on WTB
27. Bidder experience effect on WTB
28. Model results for bid speed
29. Model results for probability of bidding BIN
30. Number of latent competing bidders
31. Model fit: MAPE
32. Model fit: in-sample hit rate
33. Observed vs. fitted number of bidders
34. Observed vs. fitted bid time
35. Observed vs. fitted bid amount
36. Conclusions and future research

Topics Covered

• Our integrated stochastic model approach
• Data description
• Empirical findings
• Conceptual model development
• Latent bidders
• Model development
• Model results
• Model fit

Links

Series:

• Bayesian Analysis in Marketing

Categories:

• Marketing & Sales

Talk Citation

Publication History

• Published on January 27, 2010