Wolf Ketter's Publications

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Strategic Sales Management Guided By Economic Regimes

Wolfgang Ketter, John Collins, Maria Gini, Alok Gupta, and Paul Schrater. Strategic Sales Management Guided By Economic Regimes. In Peter Vervest, Eric van Heck, Kenneth Preiss, and Louis-Francois Pau, editors, Edited Volume of the 2nd Smart Business Network Initiative Discovery Event, Springer Verlag, 2007.

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Abstract

We present methods to predict future market conditions and price trends from historical data, and we describe how these predictions can be used by an autonomous agent to make strategic and tactical sales decisions. The methods are based on learning dominant market conditions, such as over-supply or scarcity, from historical data and using this knowledge, together with real-time observable information, to identify the current market conditions. We use a Gaussian Mixture Model to represent the price density and a Markov process to forecast market changes and to predict price density over a planning horizon. We validate our methods by presenting experimental results in predicting price trends in the customer market for the Trading Agent Competition for Supply Chain Management.

@InCollection{KetterW_SBNi06,
  author =   "Wolfgang Ketter and John Collins and Maria Gini and Alok Gupta and Paul Schrater",
  title =    "Strategic Sales Management Guided By Economic Regimes",
    editor =     "Peter Vervest and Eric van Heck and Kenneth Preiss and Louis-Francois Pau",
  booktitle =    "Edited Volume of the 2nd Smart Business Network Initiative Discovery Event",
abstract = {We present methods to predict future market conditions
and price trends from historical data, and we describe how these
predictions can be used by an autonomous agent to make strategic and
tactical sales decisions.  The methods are based on learning dominant
market conditions, such as over-supply or scarcity, from historical data
and using this knowledge, together with real-time observable
information, to identify the current market conditions. We use a
Gaussian Mixture Model to represent the price density
and a Markov process to forecast market changes and to predict
price density over a planning horizon.  We validate our
methods by presenting experimental results in predicting
price trends in the customer market for the Trading
Agent Competition for Supply Chain Management.},
  publisher =    "Springer Verlag",
  year =      2007,
  bib2html_pubtype = {Book Chapter},
  bib2html_rescat = {Trading Agents: Supply-Chain Management},
}

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