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Voice analytics in business research: Conceptual foundations, acoustic feature extraction, and applications

Author

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  • Hildebrand, Christian
  • Efthymiou, Fotis
  • Busquet, Francesc
  • Hampton, William H.
  • Hoffman, Donna L.
  • Novak, Thomas P.

Abstract

Recent advances in artificial intelligence and natural language processing are gradually transforming how humans search, shop, and express their preferences. Leveraging the new affordances and modalities of human–machine interaction through voice-controlled interfaces will require a nuanced understanding of the physics and psychology of speech formation as well as the systematic extraction and analysis of vocal features from the human voice. In this paper, we first develop a conceptual framework linking vocal features in the human voice to experiential outcomes and emotional states. We then illustrate the effective processing, editing, analysis, and visualization of voice data based on an Amazon Alexa user interaction, utilizing state-of-the-art signal-processing packages in R. Finally, we offer novel insight into the ways in which business research might employ voice and sound analytics moving forward, including a discussion of the ethical implications of building multi-modal databases for business and society.

Suggested Citation

  • Hildebrand, Christian & Efthymiou, Fotis & Busquet, Francesc & Hampton, William H. & Hoffman, Donna L. & Novak, Thomas P., 2020. "Voice analytics in business research: Conceptual foundations, acoustic feature extraction, and applications," Journal of Business Research, Elsevier, vol. 121(C), pages 364-374.
    • Handle: RePEc:eee:jbrese:v:121:y:2020:i:c:p:364-374
    DOI: 10.1016/j.jbusres.2020.09.020
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    References listed on IDEAS

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    1. Donna L Hoffman & Thomas P Novak & Eileen FischerEditor & Robert KozinetsAssociate Editor, 2018. "Consumer and Object Experience in the Internet of Things: An Assemblage Theory Approach," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(6), pages 1178-1204.
    2. Shiri Melumad & Rhonda Hadi & Christian Hildebrand & Adrian F. Ward, 2020. "Technology-Augmented Choice: How Digital Innovations Are Transforming Consumer Decision Processes," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 7(3), pages 90-101, October.
    3. Thomas P. Novak & Donna L. Hoffman, 2019. "Relationship journeys in the internet of things: a new framework for understanding interactions between consumers and smart objects," Journal of the Academy of Marketing Science, Springer, vol. 47(2), pages 216-237, March.
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    Cited by:

    1. Naim Zierau & Christian Hildebrand & Anouk Bergner & Francesc Busquet & Anuschka Schmitt & Jan Marco Leimeister, 2023. "Voice bots on the frontline: Voice-based interfaces enhance flow-like consumer experiences & boost service outcomes," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 823-842, July.
    2. Haenlein, Michael & Kaplan, Andreas, 2021. "Artificial intelligence and robotics: Shaking up the business world and society at large," Journal of Business Research, Elsevier, vol. 124(C), pages 405-407.
    3. Hye-jin Kim & Yi Wang & Min Ding, 2021. "Brand Voiceprint," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 8(4), pages 123-136, December.
    4. Schwenzow, Jasper & Hartmann, Jochen & Schikowsky, Amos & Heitmann, Mark, 2021. "Understanding videos at scale: How to extract insights for business research," Journal of Business Research, Elsevier, vol. 123(C), pages 367-379.
    5. Volkmar, Gioia & Fischer, Peter M. & Reinecke, Sven, 2022. "Artificial Intelligence and Machine Learning: Exploring drivers, barriers, and future developments in marketing management," Journal of Business Research, Elsevier, vol. 149(C), pages 599-614.
    6. Christian Hildebrand & Anouk Bergner, 2021. "Conversational robo advisors as surrogates of trust: onboarding experience, firm perception, and consumer financial decision making," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 659-676, July.
    7. Beeler, Lisa & Zablah, Alex R. & Rapp, Adam, 2022. "Ability is in the eye of the beholder: How context and individual factors shape consumer perceptions of digital assistant ability," Journal of Business Research, Elsevier, vol. 148(C), pages 33-46.
    8. Ngai, Eric W.T. & Wu, Yuanyuan, 2022. "Machine learning in marketing: A literature review, conceptual framework, and research agenda," Journal of Business Research, Elsevier, vol. 145(C), pages 35-48.
    9. Allison, Thomas H. & Warnick, Benjamin J. & Davis, Blakley C. & Cardon, Melissa S., 2022. "Can you hear me now? Engendering passion and preparedness perceptions with vocal expressions in crowdfunding pitches," Journal of Business Venturing, Elsevier, vol. 37(3).
    10. Shiri Melumad & Rhonda Hadi & Christian Hildebrand & Adrian F. Ward, 2020. "Technology-Augmented Choice: How Digital Innovations Are Transforming Consumer Decision Processes," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 7(3), pages 90-101, October.
    11. Grewal, Dhruv & Herhausen, Dennis & Ludwig, Stephan & Villarroel Ordenes, Francisco, 2022. "The Future of Digital Communication Research: Considering Dynamics and Multimodality," Journal of Retailing, Elsevier, vol. 98(2), pages 224-240.
    12. Shiri Melumad & Rhonda Hadi & Christian Hildebrand & Adrian F. Ward, 2021. "Technology-Augmented Choice: How Digital Innovations Are Transforming Consumer Decision Processes," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 7(3), pages 90-101, October.

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