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A Constrained Clusterwise Regression Procedure for Benefit Segmentation

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Summary

A new procedure for benefit segmentation using clusterwise regression is presented. Constraints on the model parameters ensure that the derived benefit segments can be easily attached to single competing products under consideration. The new procedure is compared to other one-stage and two-stage procedures for benefit segmentation using data from the European air freight market.

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© 1998 Springer Japan

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Baier, D. (1998). A Constrained Clusterwise Regression Procedure for Benefit Segmentation. In: Hayashi, C., Yajima, K., Bock, HH., Ohsumi, N., Tanaka, Y., Baba, Y. (eds) Data Science, Classification, and Related Methods. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Tokyo. https://doi.org/10.1007/978-4-431-65950-1_74

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  • DOI: https://doi.org/10.1007/978-4-431-65950-1_74

  • Publisher Name: Springer, Tokyo

  • Print ISBN: 978-4-431-70208-5

  • Online ISBN: 978-4-431-65950-1

  • eBook Packages: Springer Book Archive

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