Real-Time Tactical and Strategic Sales Management for Intelligent Agents Guided by Economic Regimes

36 Pages Posted: 18 May 2011

See all articles by Wolfgang Ketter

Wolfgang Ketter

University of Cologne - Faculty of Management, Economics and Social Sciences; Erasmus University Rotterdam (EUR) - Department of Technology and Operations Management; Erasmus Research Institute of Management (ERIM)

John Collins

University of Minnesota - Twin Cities

Maria Gini

University of Minnesota - Twin Cities - Computer Science and Engineering

Alok Gupta

University of Minnesota - Twin Cities - Carlson School of Management

Paul Schrater

University of Minnesota - Twin Cities

Date Written: May 16, 2011

Abstract

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 address 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 (TAC SCM), a supply chain environment characterized by competitive procurement and sales markets, and dynamic pricing. We show how regime models can be used to inform both short-term pricing decisions and longterm resource allocation decisions. Results show that our method outperforms more traditional shortand long-term predictive modeling approaches.

Keywords: dynamic pricing, trading agent competition, agent-mediated electronic commerce, dynamic markets, economic regimes, enabling technologies, price forecasting, supply-chain

JEL Classification: M, O32, L15

Suggested Citation

Ketter, Wolfgang and Collins, John and Gini, Maria L and Gupta, Alok and Schrater, Paul, Real-Time Tactical and Strategic Sales Management for Intelligent Agents Guided by Economic Regimes (May 16, 2011). ERIM Report Series Reference No. ERS-2011-012-LIS, Available at SSRN: https://ssrn.com/abstract=1845265

Wolfgang Ketter (Contact Author)

University of Cologne - Faculty of Management, Economics and Social Sciences ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

HOME PAGE: http://is3.uni-koeln.de

Erasmus University Rotterdam (EUR) - Department of Technology and Operations Management ( email )

RSM Erasmus University
PO Box 1738
3000 DR Rotterdam
Netherlands

Erasmus Research Institute of Management (ERIM) ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

HOME PAGE: http://www.rsm.nl/energy

John Collins

University of Minnesota - Twin Cities ( email )

420 Delaware St. SE
Minneapolis, MN 55455
United States

Maria L Gini

University of Minnesota - Twin Cities - Computer Science and Engineering ( email )

200 Union St SE, #4-192
Minneapolis, MN 55455
United States

HOME PAGE: http://www,cs,umn.edu/~gini

Alok Gupta

University of Minnesota - Twin Cities - Carlson School of Management ( email )

19th Avenue South
Minneapolis, MN 55455
United States

Paul Schrater

University of Minnesota - Twin Cities ( email )

420 Delaware St. SE
Minneapolis, MN 55455
United States