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A Two-Step Hierarchical Product Configurator Design Methodology

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Foundations of Intelligent Systems (ISMIS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7661))

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Abstract

Product configurators are widely used to elicit custmer requirements in the form of tangible product specification in product design. However customers are heterogeneous in terms of preferences and needs. To meet the diversified customer needs, companies have provided a wider variety of product variants. In this situation, there may be too many choices for customers to specify during configuration process. The huge number of choices may lead to mass confusion among customers, and less customer satisfaction. To handle this issue, we propose a hierarchical product configuration design method which operates in a from-coarse-to-fine manner. K-means method is used to classify the whole product attribute sets into several interested clusters. The coarse configuration process will be used to identify customers’ preferences cluster. The fine configuration stage will be conducted within each cluster to fine tune the product configuration. Thus the confusion caused by the large number of choices can be mitigated.

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References

  1. Sabin, D., Weigel, R.: Product Configuration Frameworks - A Survey. IEEE Intelligent Systems, 42–49 (July/August 1998)

    Google Scholar 

  2. Wang, Y., Tseng, M.M.: Adaptive attribute selection for configurator design via Shapley value. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 25(1), 185–195 (2011)

    Article  MATH  Google Scholar 

  3. Wang, Y., Tseng, M.M.: Customized products recommendation based on Probabilistic relevance model. Journal of Intelligent Manufacturing (accepted, 2012), doi:10.1007/s10845-012-0644-7

    Google Scholar 

  4. Kurniawan, S.H., Tseng, M.M., So, R.H.Y.: Modeling consumer behavior in the customization process. In: Piller, F., Tseng, M. (eds.) The Customer Centric Enterprise, pp. 267–282. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  5. Bayus, B.L., Putsis Jr., W.P.: Product proliferation: An empirical analysis of product line determinants and market outcomes. Marketing Science 18(2), 137–153 (1999)

    Article  Google Scholar 

  6. Huffman, C., Kahn, B.E.: Variety for sale: Mass customization or mass confusion? Journal of Retailing 74(4), 491–513 (1998)

    Article  Google Scholar 

  7. Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification. John Wiley & Sons, New York (2001)

    MATH  Google Scholar 

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© 2012 Springer-Verlag Berlin Heidelberg

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Wang, Y., Tseng, M.M. (2012). A Two-Step Hierarchical Product Configurator Design Methodology. In: Chen, L., Felfernig, A., Liu, J., RaĹ›, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2012. Lecture Notes in Computer Science(), vol 7661. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34624-8_39

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  • DOI: https://doi.org/10.1007/978-3-642-34624-8_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34623-1

  • Online ISBN: 978-3-642-34624-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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