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Hierarchisch bayesianische Methoden bei der Conjointanalyse

In: Conjointanalyse

Author

Listed:
  • Bernhard Baumgartner

    (Universität Osnabrück)

  • Winfried J. Steiner

    (Technische Universität Clausthal)

Abstract

Zusammenfassung Im Laufe der letzten beiden Dekaden wurden in der Marketingforschung zunehmend hierarchisch bayesianische Ansätze zur Modellierung von Konsumentenheterogenität eingesetzt. Allenby et al. (1995), Allenby und Ginter (1995) sowie Lenk et al. (1996) wendeten diese Verfahren erstmals an, um individuelle Nutzenbeiträge basierend auf Daten aus Conjointanalysen zu schätzen. In diesem Kapitel werden Grundlagen und die Vorgehensweise einführend diskutiert. So wird zunächst der Grundgedanke der bayesianischen Statistik und das häufig verwendete, so genannte „Normalmodell“ zur Schätzung individueller Koeffizienten sowie Modellerweiterungen behandelt. Ausführungen zur Modellselektion und eine empirische Anwendung schließen das Kapitel mit einer kurzen Zusammenfassung ab.

Suggested Citation

  • Bernhard Baumgartner & Winfried J. Steiner, 2021. "Hierarchisch bayesianische Methoden bei der Conjointanalyse," Springer Books, in: Daniel Baier & Michael Brusch (ed.), Conjointanalyse, edition 2, chapter 0, pages 257-272, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-63364-9_11
    DOI: 10.1007/978-3-662-63364-9_11
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