Name
Abstract | ||
|---|---|---|
Deciding who should receive a mail-order catalog is among the most important decisions that mail-order-catalog firms must address. In practice, the current approach to the problem is invariably myopic: firms send catalogs to customers who they think are most likely to order from that catalog. In doing so, the firms overlook the long-run implications of these decisions. For example, it may be profitable to mail to customers who are unlikely to order immediately if sending the current catalog increases the probability of a future order. We propose a model that allows firms to optimize mailing decisions by addressing the dynamic implications of their decisions. The model is conceptually simple and straightforward to implement. We apply the model to a large sample of historical data provided by a catalog firm and then evaluate its performance in a large-scale field test. The findings offer support for the proposed model but also identify opportunities for further improvement. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1287/mnsc.1050.0504 | Management Science |
Keywords | Field | DocType |
markov decision process,findings offer support,dynamic catalog,future order,important decision,catalog mailing,current catalog,current approach,historical data,dynamic implication,dynamic optimization,field test,mail-order catalog,catalog firm,profitability | Dynamic programming,Economics,Markov process,Microeconomics,Markov decision process,Operations research,Marketing | Journal |
Volume | Issue | ISSN |
52 | 5 | 0025-1909 |
Citations | PageRank | References |
24 | 2.88 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Duncan I. Simester | 1 | 260 | 20.45 |
| Peng Sun | 2 | 420 | 26.68 |
| John N. Tsitsiklis | 3 | 5300 | 621.34 |