Adapting Manufacturing to Customer Behavior

Lessons learned from trading goods on public market places
  • Stephan Kassel
  • Kay Grebenstein
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 207)


The globalization of competition urges manufacturers to reduce costs and simultaneously provide a better service to the customer. To achieve both goals, the prediction of customer behaviour plays a key role. This can be done by observation of the customers on public market places like eBay. These observations have to be combined with events influencing customer preferences. For this purpose, a decision support system for retailers was designed, combining an expert system with a data warehouse. The experiences of this project can be utilized for manufacturing companies as well.

Key words

event-driven customer behaviour demand prognosis knowledge management data warehouse public markets decision support customer-driven manufacturing 

4. References

  1. 1.
    An, C. Fromm, H., eds., (2005), Supply Chain Management on Demand, Springer, Berlin.Google Scholar
  2. 2.
    Becker, T., (2005), Prozesse in Produktion und Supply Chain optimieren, Springer, Berlin.Google Scholar
  3. 3.
    BüyüKözkan, G., Derelİ, T., and Baykasoğlu, A., (2004), A survey on the methods and tools of concurrent new product development and agile manufacturing, J. Int. Manuf. 15(6): 731–751.CrossRefGoogle Scholar
  4. 4.
    Dietrich, J., (2004), A Rule-Based System for eCommerce Applications, in: Proceedings of Knowledge-Based Intelligent Information and Engineering Systems: 8th International Conference, Springer LNCS 3213 / 2004, Heidelberg, 455–463.Google Scholar
  5. 5.
    Kamakura, W., Mela, C.F., Ansari, A., Bodapati, A., Fader, P., Iyengar, R., Naik, P., Neslin, S., Sun, B., Verhoef, P.C., Wedel, M., and Wilcox, R., (2005), Choice Models and Customer Relationship Management, Marketing Letters 16(3–4): 279–291.CrossRefGoogle Scholar
  6. 6.
    Kidd, P.T., (1994), Agile Manufacturing, Addison-Wesley, Reading.Google Scholar
  7. 7.
    Liker, J., (2004), The Toyota Way, McGraw-Hill, New York, New York.Google Scholar
  8. 8.
    Liu, B., Hsu, W., Han, H.-S., and Xia, Y., (2000), Mining Changes for Real-Life Applications, in: Data Warehousing and Knowledge Discovery: Second International Conference, DaWaK 2000, London, UK, September 2000. Proceedings, Y. Kambayashi, M. Mohania, A M. Tjoa, eds., LNCS 1874–2000, 337–346.Google Scholar
  9. 9.
    Salcedo, L., (2004), Market Forecast Report European Commerce, 2003–2009, JupiterResearch, Jupitermedia Corp.Google Scholar
  10. 10.
    Sol, H., (2002), Expert Systems and Artificial Inteligence in Decision Support Systems, Kluwer Academic Publishers.Google Scholar
  11. 11.
    Verhoef, P.C., Franses, P.H., and Donkers, B., (2002), Changing Perceptions and Changing Behavior in Customer Relationships, Marketing Letters 13(2): 121–134.CrossRefGoogle Scholar
  12. 12.
    Vitt, E., (2002), Business Intelligence: Making Better Decisions Faster, Microsoft Corporation, RedmondGoogle Scholar
  13. 13.
    Womack, J.P., and Jones, D.T., (1996), Lean Thinking, Simon & Schuster, New York, New York.Google Scholar

Copyright information

© International Federation for Information Processing 2006

Authors and Affiliations

  • Stephan Kassel
    • 1
  • Kay Grebenstein
    • 1
  1. 1.University of Applied SciencesZwickauGermany

Personalised recommendations