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Identifying and predicting economic regimes in supply chains using sales and procurement information

Published: 12 August 2009 Publication History

Abstract

We investigate the effects of adding procurement information (component offer prices) to a sales-based economic regime model, which is used for strategic, tactical, and operational decision making in dynamic supply chains. The performance of the regime model is evaluated through experiments with the MinneTAC trading agent, which competes in the TAC SCM game. We find that the new regime model has a similar overall predictive performance as the existing model. Regime switches are predicted more accurately, whereas the prediction accuracy of dominant regimes is slightly worse. However, by adding procurement information, we have enriched the model and we have further opportunities for applications in the procurement market, such as procurement reserve pricing.

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  1. Identifying and predicting economic regimes in supply chains using sales and procurement information

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      cover image ACM Other conferences
      ICEC '09: Proceedings of the 11th International Conference on Electronic Commerce
      August 2009
      407 pages
      ISBN:9781605585864
      DOI:10.1145/1593254
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Sponsors

      • School of Business, The University of Hong Kong, Hong Kong
      • Sayling Wen Cultural & Educational Foundation
      • Ministry of Education, Taiwan
      • College of Information Science and Technology, Drexel University, USA
      • Weatherhead School of Management, Case Western Reserve University, USA
      • College of Technology Management, National Tsing Hua University, Taiwan
      • National Science Council, Taiwan
      • Chinese Enterprise Resource Planning Society, Taiwan
      • International Center for Electronic Commerce, Korea Advanced Institute of Science & Technology, Korea

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 12 August 2009

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      Author Tags

      1. TAC SCM
      2. economic regimes
      3. machine learning
      4. supply chain management
      5. trading agent

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      ICEC '09
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      ICEC '09: International Conference on E-Commerce
      August 12 - 15, 2009
      Taipei, Taiwan

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