2012-12-01
Real-time Tactical and Strategic Sales Management for Intelligent Trading Agents Guided by Economic Regimes
Publication
Publication
Many enterprises that participate in dynamic markets need to make product pricing and inventory resource
utilization decisions in real time. We describe a family of statistical models that addresses these needs by
combining characterization of the economic environment with the ability to predict future economic conditions
to make tactical (short-term) decisions, such as product pricing, and strategic (long-term) decisions, such as
level of finished goods inventories. Our models characterize economic conditions, called economic regimes,
in the form of recurrent statistical patterns that have clear qualitative interpretations. We show how these
models can be used to predict prices, price trends, and the probability of receiving a customer order at a given
price.
These “regime” models are developed using statistical analysis of historical data and are used in real
time to characterize observed market conditions and predict the evolution of market conditions over multiple
time scales. We evaluate our models using a testbed derived from the Trading Agent Competition for Supply
Chain Management, a supply chain environment characterized by competitive procurement, sales markets, and
dynamic pricing. We show how regime models can be used to inform both short-term pricing decisions and
long-term resource allocation decisions. Results show that our method outperforms more traditional short- and
long-term predictive modeling approaches.
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hdl.handle.net/1765/115458 | |
Organisation | Department of Technology and Operations Management |
Ketter, W., Collins, J., Gini, M., Gupta, A., & Schrater, P. (2012). Real-time Tactical and Strategic Sales Management for Intelligent Trading Agents Guided by Economic Regimes. Retrieved from http://hdl.handle.net/1765/115458 |