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Tuesday, February 16, 2010

Agent-Based Consumer Market Modeling

A number of my former colleagues at Procter & Gamble have co-authored a paper with some smart people I met at Argonne National Labs. Abstract below. Fascinating application of agents to markets. With very interesting details. To appear in Complexity Magazine. Congrats for its publication to everyone.

Multiscale agent-based consumer market modeling
Michael J. North 1 , Charles M. Macal 1, James St. Aubin 2, Prakash Thimmapuram 3, Mark Bragen 2, June Hahn 4, James Karr 4, Nancy Brigham 4, Mark E. Lacy 4, Delaine Hampton 4
1Center for Complex Adaptive Agent Systems Simulation, Argonne, Illinois 60439
2Modeling, Simulation, and Visualization Group, Argonne, Illinois 60439
3Center for Energy, Environmental, and Economic Systems Analysis, Argonne National Laboratory, Argonne, Illinois 60439
4The Procter & Gamble Company, Cincinnati, Ohio 45202

Consumer markets have been studied in great depth, and many techniques have been used to represent them. These have included regression-based models, logit models, and theoretical market-level models, such as the NBD-Dirichlet approach. Although many important contributions and insights have resulted from studies that relied on these models, there is still a need for a model that could more holistically represent the interdependencies of the decisions made by consumers, retailers, and manufacturers. When the need is for a model that could be used repeatedly over time to support decisions in an industrial setting, it is particularly critical. Although some existing methods can, in principle, represent such complex interdependencies, their capabilities might be outstripped if they had to be used for industrial applications, because of the details this type of modeling requires. However, a complementary method - agent-based modeling - shows promise for addressing these issues. Agent-based models use business-driven rules for individuals (e.g., individual consumer rules for buying items, individual retailer rules for stocking items, or individual firm rules for advertizing items) to determine holistic, system-level outcomes (e.g., to determine if brand X's market share is increasing). We applied agent-based modeling to develop a multi-scale consumer market model. We then conducted calibration, verification, and validation tests of this model. The model was successfully applied by Procter & Gamble to several challenging business problems. In these situations, it directly influenced managerial decision making and produced substantial cost savings.

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