IDEAS home Printed from https://ideas.repec.org/a/eee/jouret/v100y2024i2p293-315.html
   My bibliography  Save this article

Facilitating retail customers’ use of AI-based virtual assistants: A meta-analysis

Author

Listed:
  • Blut, Markus
  • Wünderlich, Nancy V.
  • Brock, Christian

Abstract

Retailers rely on virtual assistants (VAs), such as Amazon's Alexa and chatbots, to deliver 24/7 customer service at low costs, as well as novel shopping opportunities. Despite improved VA capabilities due to artificial intelligence (AI), many retailers still struggle to convince customers to become repeat users of VAs. Therefore, to establish recommendations for how to facilitate VA use, this meta-analysis extracts 2,766 correlations from 244 independent samples of customers interacting with VAs. The results suggest that customer-, VA-, and shopping occasion–related factors all influence technology use. Price value is the strongest driver, followed by support, social influence, and anthropomorphism. Performance risk, competence, and trust matter to lesser extents. These factors exert strong indirect effects by triggering two customer responses: cognitive and emotional. Negative emotions emerge as a particularly important mediator. Finally, several VA types enhance or weaken the noted effects, including whether they are intelligent/less intelligent, commercial/noncommercial, voice-/text-based, and avatar-/non-avatar-based. The results suggest no one-size-fits-all approach applies for VAs, because their performance varies across customer responses. The current meta-analysis provides in-depth guidance for retailers seeking to select appealing VAs.

Suggested Citation

  • Blut, Markus & Wünderlich, Nancy V. & Brock, Christian, 2024. "Facilitating retail customers’ use of AI-based virtual assistants: A meta-analysis," Journal of Retailing, Elsevier, vol. 100(2), pages 293-315.
    • Handle: RePEc:eee:jouret:v:100:y:2024:i:2:p:293-315
    DOI: 10.1016/j.jretai.2024.04.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0022435924000174
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jretai.2024.04.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    3. Marcus Phipps & Julie L. Ozanne, 2017. "Routines Disrupted: Reestablishing Security through Practice Alignment," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(2), pages 361-380.
    4. Johnson, Devon & Grayson, Kent, 2005. "Cognitive and affective trust in service relationships," Journal of Business Research, Elsevier, vol. 58(4), pages 500-507, April.
    5. Weiyin Hong & Frank K. Y. Chan & James Y. L. Thong & Lewis C. Chasalow & Gurpreet Dhillon, 2014. "A Framework and Guidelines for Context-Specific Theorizing in Information Systems Research," Information Systems Research, INFORMS, vol. 25(1), pages 111-136, March.
    6. Shimp, Terence A & Bearden, William O, 1982. "Warranty and Other Extrinsic Cue Effects on Consumers' Risk Perceptions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(1), pages 38-46, June.
    7. Guha, Abhijit & Grewal, Dhruv & Kopalle, Praveen K. & Haenlein, Michael & Schneider, Matthew J. & Jung, Hyunseok & Moustafa, Rida & Hegde, Dinesh R. & Hawkins, Gary, 2021. "How artificial intelligence will affect the future of retailing," Journal of Retailing, Elsevier, vol. 97(1), pages 28-41.
    8. Huang, Ming-Hui & Rust, Roland T., 2022. "A Framework for Collaborative Artificial Intelligence in Marketing," Journal of Retailing, Elsevier, vol. 98(2), pages 209-223.
    9. Davis, Lizhu & Hodges, Nancy, 2012. "Consumer shopping value: An investigation of shopping trip value, in-store shopping value and retail format," Journal of Retailing and Consumer Services, Elsevier, vol. 19(2), pages 229-239.
    10. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    11. Joshua J. Clarkson & Chris Janiszewski & Melissa D. Cinelli, 2013. "The Desire for Consumption Knowledge," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 39(6), pages 1313-1329.
    12. Gelbrich, Katja & Hagel, Julia & Orsingher, Chiara, 2021. "Emotional support from a digital assistant in technology-mediated services: Effects on customer satisfaction and behavioral persistence," International Journal of Research in Marketing, Elsevier, vol. 38(1), pages 176-193.
    13. Dhruv Grewal & Nancy Puccinelli & Kent B. Monroe, 2018. "Meta-analysis: integrating accumulated knowledge," Journal of the Academy of Marketing Science, Springer, vol. 46(1), pages 9-30, January.
    14. Li, Jian & Huang, Jin-Song, 2020. "Dimensions of artificial intelligence anxiety based on the integrated fear acquisition theory," Technology in Society, Elsevier, vol. 63(C).
    15. Jian Mou & Dong-Hee Shin & Jason Cohen, 2017. "Understanding trust and perceived usefulness in the consumer acceptance of an e-service: a longitudinal investigation," Behaviour and Information Technology, Taylor & Francis Journals, vol. 36(2), pages 125-139, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mauricio S. Featherman & Nick Hajli, 2016. "Self-Service Technologies and e-Services Risks in Social Commerce Era," Journal of Business Ethics, Springer, vol. 139(2), pages 251-269, December.
    2. Mariani, Marcello M. & Ek Styven, Maria & Teulon, Fréderic, 2021. "Explaining the intention to use digital personal data stores: An empirical study," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    3. Mütterlein, Joschka & Kunz, Reinhard E. & Baier, Daniel, 2019. "Effects of lead-usership on the acceptance of media innovations: A mobile augmented reality case," Technological Forecasting and Social Change, Elsevier, vol. 145(C), pages 113-124.
    4. Capestro, Mauro & Rizzo, Cristian & Kliestik, Tomas & Peluso, Alessandro M. & Pino, Giovanni, 2024. "Enabling digital technologies adoption in industrial districts: The key role of trust and knowledge sharing," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    5. Erik Hermann & Gizem Yalcin Williams & Stefano Puntoni, 2024. "Deploying artificial intelligence in services to AID vulnerable consumers," Journal of the Academy of Marketing Science, Springer, vol. 52(5), pages 1431-1451, October.
    6. İbrahim Aydın & Zübeyir Çelik & Kaan Yiğenoğlu & Ayhan Cesur, 2024. "Consumers' foresight for the digital Turkish lira: an empirical study," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 29(2), pages 214-228, June.
    7. Mou, Jian & Benyoucef, Morad, 2021. "Consumer behavior in social commerce: Results from a meta-analysis," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    8. Francesca Bonetti & Matteo Montecchi & Kirk Plangger & Hope Jensen Schau, 2023. "Practice co-evolution: Collaboratively embedding artificial intelligence in retail practices," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 867-888, July.
    9. Riccardo Reith & Maximilian Fischer & Bettina Lis, 2020. "Explaining the intention to use social trading platforms: an empirical investigation," Journal of Business Economics, Springer, vol. 90(3), pages 427-460, April.
    10. Philippe Cohard, 2020. "Information Systems Values: A Study of the Intranet in Three French Higher Education Institutions," Post-Print hal-02987225, HAL.
    11. Melih Engin & Fatih Gürses, 2019. "Adoption of Hospital Information Systems in Public Hospitals in Turkey: An Analysis with the Unified Theory of Acceptance and Use of Technology Model," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(06), pages 1-19, October.
    12. Morosan, Cristian, 2016. "An empirical examination of U.S. travelers’ intentions to use biometric e-gates in airports," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 120-128.
    13. Tsung Teng Chen, 2012. "The development and empirical study of a literature review aiding system," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(1), pages 105-116, July.
    14. Abdesamad Zouine & Pierre Fenies, 2014. "The Critical Success Factors Of The ERP System Project: A Meta-Analysis Methodology," Post-Print hal-01419785, HAL.
    15. Debora Bettiga & Lucio Lamberti & Emanuele Lettieri, 2020. "Individuals’ adoption of smart technologies for preventive health care: a structural equation modeling approach," Health Care Management Science, Springer, vol. 23(2), pages 203-214, June.
    16. Chen-Yuan Chen & Bih-Yaw Shih & Shih-Hsien Yu, 2012. "Disaster prevention and reduction for exploring teachers’ technology acceptance using a virtual reality system and partial least squares techniques," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 62(3), pages 1217-1231, July.
    17. Paul Juinn Bing Tan, 2013. "Applying the UTAUT to Understand Factors Affecting the Use of English E-Learning Websites in Taiwan," SAGE Open, , vol. 3(4), pages 21582440135, October.
    18. Mäntymäki, Matti & Salo, Jari, 2013. "Purchasing behavior in social virtual worlds: An examination of Habbo Hotel," International Journal of Information Management, Elsevier, vol. 33(2), pages 282-290.
    19. Cristopher Siegfried Kopplin, 2021. "Two heads are better than one: matchmaking tools in coworking spaces," Review of Managerial Science, Springer, vol. 15(4), pages 1045-1069, May.
    20. Ofir Turel & Catherine E. Connelly, 2012. "Team Spirit: The Influence of Psychological Collectivism on the Usage of E-Collaboration Tools," Group Decision and Negotiation, Springer, vol. 21(5), pages 703-725, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jouret:v:100:y:2024:i:2:p:293-315. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-retailing .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.