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How artificiality and intelligence affect voice assistant evaluations

Author

Listed:
  • Abhijit Guha

    (University of South Carolina)

  • Timna Bressgott

    (Maastricht University)

  • Dhruv Grewal

    (Babson College
    University of Bath)

  • Dominik Mahr

    (Maastricht University)

  • Martin Wetzels

    (EDHEC Business School)

  • Elisa Schweiger

    (King’s College)

Abstract

Widespread, and growing, use of artificial intelligence (AI)–enabled voice assistants (VAs) creates a pressing need to understand what drives VA evaluations. This article proposes a new framework wherein perceptions of VA artificiality and VA intelligence are positioned as key drivers of VA evaluations. Building from work on signaling theory, AI, technology adoption, and voice technology, the authors conceptualize VA features as signals related to either artificiality or intelligence, which in turn affect VA evaluations. This study represents the first application of signaling theory when examining VA evaluations; also, it is the first work to position VA artificiality and intelligence (cf. other factors) as key drivers of VA evaluations. Further, the paper examines the role of several theory-driven and/ or practice-relevant moderators, relating to the effects of artificiality and intelligence on VA evaluations. The results of these investigations can help firms suitably design their VAs and suitably design segmentation strategies.

Suggested Citation

  • Abhijit Guha & Timna Bressgott & Dhruv Grewal & Dominik Mahr & Martin Wetzels & Elisa Schweiger, 2023. "How artificiality and intelligence affect voice assistant evaluations," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 843-866, July.
    • Handle: RePEc:spr:joamsc:v:51:y:2023:i:4:d:10.1007_s11747-022-00874-7
    DOI: 10.1007/s11747-022-00874-7
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    1. Yiu-Fai Yung & David Thissen & Lori McLeod, 1999. "On the relationship between the higher-order factor model and the hierarchical factor model," Psychometrika, Springer;The Psychometric Society, vol. 64(2), pages 113-128, June.
    2. Benedict G. C. Dellaert & Suzanne B. Shu & Theo A. Arentze & Tom Baker & Kristin Diehl & Bas Donkers & Nathanael J. Fast & Gerald Häubl & Heidi Johnson & Uma R. Karmarkar & Harmen Oppewal & Bernd H. S, 2020. "Consumer decisions with artificially intelligent voice assistants," Marketing Letters, Springer, vol. 31(4), pages 335-347, December.
    3. Hair, Joe F. & Howard, Matt C. & Nitzl, Christian, 2020. "Assessing measurement model quality in PLS-SEM using confirmatory composite analysis," Journal of Business Research, Elsevier, vol. 109(C), pages 101-110.
    4. Joseph F. Hair & G. Tomas M. Hult & Christian M. Ringle & Marko Sarstedt & Kai Oliver Thiele, 2017. "Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods," Journal of the Academy of Marketing Science, Springer, vol. 45(5), pages 616-632, September.
    5. Grewal, Dhruv & Guha, Abhijit & Satornino, Cinthia B. & Schweiger, Elisa B., 2021. "Artificial intelligence: The light and the darkness," Journal of Business Research, Elsevier, vol. 136(C), pages 229-236.
    6. Fuller, Christie M. & Simmering, Marcia J. & Atinc, Guclu & Atinc, Yasemin & Babin, Barry J., 2016. "Common methods variance detection in business research," Journal of Business Research, Elsevier, vol. 69(8), pages 3192-3198.
    7. Milne, George R. & Villarroel Ordenes, Francisco & Kaplan, Begum, 2020. "Mindful consumption: Three consumer segment views," Australasian marketing journal, Elsevier, vol. 28(1), pages 3-10.
    8. Seo Young Kim & Bernd H. Schmitt & Nadia M. Thalmann, 2019. "Eliza in the uncanny valley: anthropomorphizing consumer robots increases their perceived warmth but decreases liking," Marketing Letters, Springer, vol. 30(1), pages 1-12, March.
    9. John Hulland, 1999. "Use of partial least squares (PLS) in strategic management research: a review of four recent studies," Strategic Management Journal, Wiley Blackwell, vol. 20(2), pages 195-204, February.
    10. McLean, Graeme & Osei-Frimpong, Kofi & Barhorst, Jennifer, 2021. "Alexa, do voice assistants influence consumer brand engagement? – Examining the role of AI powered voice assistants in influencing consumer brand engagement," Journal of Business Research, Elsevier, vol. 124(C), pages 312-328.
    11. Villarroel Ordenes, Francisco & Silipo, Rosaria, 2021. "Machine learning for marketing on the KNIME Hub: The development of a live repository for marketing applications," Journal of Business Research, Elsevier, vol. 137(C), pages 393-410.
    12. Markus Blut & Cheng Wang & Nancy V. Wünderlich & Christian Brock, 2021. "Understanding anthropomorphism in service provision: a meta-analysis of physical robots, chatbots, and other AI," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 632-658, July.
    13. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    14. Rao, Akshay R & Monroe, Kent B, 1988. "The Moderating Effect of Prior Knowledge on Cue Utilization in Product Evaluations," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 15(2), pages 253-264, September.
    15. Fernandes, Teresa & Oliveira, Elisabete, 2021. "Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption," Journal of Business Research, Elsevier, vol. 122(C), pages 180-191.
    16. Michael Spence, 1973. "Job Market Signaling," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 87(3), pages 355-374.
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