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How can machine learning aid behavioral marketing research?

Author

Listed:
  • Linda Hagen

    (University of Southern California)

  • Kosuke Uetake

    (Yale University)

  • Nathan Yang

    (Cornell University)

  • Bryan Bollinger

    (New York University)

  • Allison J. B. Chaney

    (Duke University)

  • Daria Dzyabura

    (New Economic School)

  • Jordan Etkin

    (Duke University)

  • Avi Goldfarb

    (University of Toronto)

  • Liu Liu

    (University of Colorado Boulder)

  • K. Sudhir

    (Yale University)

  • Yanwen Wang

    (University of British Columbia)

  • James R. Wright

    (University of Alberta)

  • Ying Zhu

    (University of California San Diego)

Abstract

Behavioral science and machine learning have rapidly progressed in recent years. As there is growing interest among behavioral scholars to leverage machine learning, we present strategies for how these methods that can be of value to behavioral scientists using examples centered on behavioral research.

Suggested Citation

  • Linda Hagen & Kosuke Uetake & Nathan Yang & Bryan Bollinger & Allison J. B. Chaney & Daria Dzyabura & Jordan Etkin & Avi Goldfarb & Liu Liu & K. Sudhir & Yanwen Wang & James R. Wright & Ying Zhu, 2020. "How can machine learning aid behavioral marketing research?," Marketing Letters, Springer, vol. 31(4), pages 361-370, December.
    • Handle: RePEc:kap:mktlet:v:31:y:2020:i:4:d:10.1007_s11002-020-09535-7
    DOI: 10.1007/s11002-020-09535-7
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