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On ChatGPT and beyond: How generative artificial intelligence may affect research, teaching, and practice

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  • Peres, Renana
  • Schreier, Martin
  • Schweidel, David
  • Sorescu, Alina

Abstract

How does ChatGPT, and other forms of Generative Artificial Intelligence (GenAI) affect the way we have been conducting—and evaluating—academic research, teaching, and business practice? What are the implications for the theory and practice of marketing? What are the opportunities and threats, and what are some interesting avenues for future research? This editorial aims to kick off an initial discussion and stimulate research that will help us better understand how the marketing field can fully exploit the potential of GenAI and effectively cope with its challenges.

Suggested Citation

  • Peres, Renana & Schreier, Martin & Schweidel, David & Sorescu, Alina, 2023. "On ChatGPT and beyond: How generative artificial intelligence may affect research, teaching, and practice," International Journal of Research in Marketing, Elsevier, vol. 40(2), pages 269-275.
    • Handle: RePEc:eee:ijrema:v:40:y:2023:i:2:p:269-275
    DOI: 10.1016/j.ijresmar.2023.03.001
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    References listed on IDEAS

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    1. Nishikawa, Hidehiko & Schreier, Martin & Ogawa, Susumu, 2013. "User-generated versus designer-generated products: A performance assessment at Muji," International Journal of Research in Marketing, Elsevier, vol. 30(2), pages 160-167.
    2. Chris Stokel-Walker, 2023. "ChatGPT listed as author on research papers: many scientists disapprove," Nature, Nature, vol. 613(7945), pages 620-621, January.
    3. Holly Else, 2023. "Abstracts written by ChatGPT fool scientists," Nature, Nature, vol. 613(7944), pages 423-423, January.
    4. Eric von Hippel, 2006. "Democratizing Innovation," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262720477, December.
    5. Eva A. M. van Dis & Johan Bollen & Willem Zuidema & Robert van Rooij & Claudi L. Bockting, 2023. "ChatGPT: five priorities for research," Nature, Nature, vol. 614(7947), pages 224-226, February.
    6. Carlson, Keith & Kopalle, Praveen K. & Riddell, Allen & Rockmore, Daniel & Vana, Prasad, 2023. "Complementing human effort in online reviews: A deep learning approach to automatic content generation and review synthesis," International Journal of Research in Marketing, Elsevier, vol. 40(1), pages 54-74.
    7. Martin Reisenbichler & Thomas Reutterer & David A. Schweidel & Daniel Dan, 2022. "Frontiers: Supporting Content Marketing with Natural Language Generation," Marketing Science, INFORMS, vol. 41(3), pages 441-452, May.
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