Voice-Led Urges: Voice Assistants Shape Spontaneous Decisions in Voice Commerce

Authors

  • V. Swathi S.E.A College of Science Commerce and Arts, Bangalore, India Author
  • C. Nagadeepa Kristu Jayanti College Autonomous, Bengaluru, India Author
  • Jaheer Mukthar KP Kristu Jayanti College Autonomous, Bengaluru, India Author
  • Allam Hamdan Ahlia University, Manama, Bahrain , University of Business & Technology, Jeddah, Saudi Arabia Author

DOI:

https://doi.org/10.51325/ejbti.v3i1.187

Keywords:

Voice Assistant, Personalized Online Shopping, Impulse Buying Behavior, Seamless ‎Interaction, Voice Commerce.

Abstract

Growth of technology and innovation is inevitable. Using natural language processing along with machine learning, this technology allows voice assistants to detect user preferences. Voice assistants would suggest products that are suited to the user, smoothen the buying process, and show a user interface that is in tune with the user's way of shopping behavior. The innovation copes with the challenges of limited visual comparison by adding context-aware suggestions that improve the engagement of users and enhance their confidence in the purchase decisions made through voice interactions. Our study is multifaceted in its blend of survey and interview approaches, investigating the psychology and behavior of consumer interactions. The study emphasizes impulsive purchase behavior influenced by this personalized technology. The SEM methodology was used for data analysis and hypothesis testing in connection with the voice assistant's features and online consumer decision-making process. This research offers several useful insights regarding the still-evolving voice commerce and its implications for businesses to enhance user engagement and satisfaction with personalized online shopping. The study presents both an innovative framework for voice-assisted e-commerce and discusses the rich dynamics between technological development and consumer behavior in the digital marketplace.

Author Biographies

  • V. Swathi, S.E.A College of Science Commerce and Arts, Bangalore, India

    S.E.A College of Science Commerce and Arts, Bangalore, India

  • C. Nagadeepa, Kristu Jayanti College Autonomous, Bengaluru, India

    Kristu Jayanti College Autonomous, Bengaluru, India

  • Jaheer Mukthar KP, Kristu Jayanti College Autonomous, Bengaluru, India

    Kristu Jayanti College Autonomous, Bengaluru, India ‎

  • Allam Hamdan, Ahlia University, Manama, Bahrain, University of Business & Technology, Jeddah, Saudi Arabia

    Ahlia University, Manama, Bahrain / University of Business & Technology, Jeddah, Saudi Arabia

References

Buhalis, D., & Moldavska, I. (2022). Voice assistants in hospitality: Using ‎artificial intelligence for customer service. Journal of Hospitality and ‎Tourism Technology, 13(3), 386–403. https://doi.org/10.1108/JHTT-03-‎‎2021-0104‎ DOI: https://doi.org/10.1108/JHTT-03-2021-0104

Burke, R. R. (2002). Technology and the customer interface: What consumers ‎want in the physical and virtual store. Journal of the Academy of ‎Marketing Science, 30(4), 411–432. ‎https://doi.org/10.1177/009207002236914‎ DOI: https://doi.org/10.1177/009207002236914

Chung, A. E., Griffin, A. C., Selezneva, D., & Gotz, D. (2018). Health and fitness ‎apps for hands-free voice-activated assistants: Content analysis. JMIR ‎mHealth and uHealth, 6(9), e9705. ‎https://doi.org/10.2196/mhealth.9705‎ DOI: https://doi.org/10.2196/mhealth.9705

Dellarocas, C., Zhang, X., & Awad, N. F. (2013). Exploring the value of online ‎product reviews in forecasting sales: The case of motion pictures. Journal ‎of Interactive Marketing, 27(4), 183–197.‎

Dholakia, U. M., Zhao, M., Dholakia, R. R., & Roggeveen, A. L. (2004). Coping ‎with the coping construct: A critical review and future directions. ‎Academy of Marketing Science Review, 2004(4).‎

Huang, Z., Benyoucef, M., & Kassab, M. (2018). A systematic review of the ‎factors influencing the adoption of mHealth solutions for underserved ‎populations. Journal of Organizational and End User Computing, 30(2), ‎‎1–25.‎

Kazim, S., Jaheer Mukthar, K. P., Jamanca-Anaya, R., Cayotopa-Ylatoma, C., ‎Mory-Guarnizo, S., & Silva-Gonzales, L. (2022, March). A study on ‎cosmetics and women consumers: Government protective measures and ‎exploitative practices. In International Conference on Business and ‎Technology (pp. 718–732). Cham: Springer International Publishing. ‎https://doi.org/10.1007/978-3-031-26953-0_66‎ DOI: https://doi.org/10.1007/978-3-031-26953-0_66

Kowatsch, T., Maass, W., & Wiesner, M. (2019). Personalization via extended ‎UTAUT: The role of individual differences, user-interface tailoring and ‎moderating effects. In Proceedings of the 52nd Hawaii International ‎Conference on System Sciences.‎

Lamba, S. S. (2021). FOMO: Marketing to millennials. Notion Press.‎

Liang, T. P., & Lai, H. J. (2000). Effect of store design on consumer purchases: ‎An empirical study of online bookstores. Information & Management, ‎‎37(5), 241–251.‎

Limayem, M., Hirt, S. G., & Cheung, C. M. (2014). How habit limits the ‎predictive power of intention: The case of information systems ‎continuance. MIS Quarterly, 38(1), 177–196.‎

Longo, F., Nicoletti, L., & Padovano, A. (2017). Smart operators in industry ‎‎4.0: A human-centered approach to enhance operators' capabilities and ‎competencies within the new smart factory context. Computers & ‎Industrial Engineering, 113, 144–159. ‎https://doi.org/10.1016/j.cie.2017.09.016‎ DOI: https://doi.org/10.1016/j.cie.2017.09.016

Malodia, S., Islam, N., Kaur, P., & Dhir, A. (2021). Why do people use artificial ‎intelligence (AI)-enabled voice assistants? IEEE Transactions on ‎Engineering Management.‎

Nagadeepa, C., Mohan, R., & Kumarathas, P. (2022). Acceptance of voice ‎assistants using technology acceptance model (TAM). Kristu Jayanti ‎Journal of Management Sciences (KJMS), 9–17. ‎https://doi.org/10.59176/kjms.v1i2.2277‎ DOI: https://doi.org/10.59176/kjms.v1i2.2277

Nagadeepa, C., Pushpa, A., Mukthar, K. J., Rurush-Asencio, R., Sifuentes-‎Stratti, J., & Rodriguez-Kong, J. (2024). User’s continuance intention ‎towards banker’s chatbot service: A technology acceptance using SUS and ‎TTF model. In Digital Technology and Changing Roles in Managerial ‎and Financial Accounting: Theoretical Knowledge and Practical ‎Application (pp. 65–77). Emerald Publishing Limited.‎ DOI: https://doi.org/10.1108/S1479-351220240000036006

Pushpa, A., Jaheer Mukthar, K. P., Ramya, U., Asis, E. H. R., & Martinez, W. R. ‎D. (2023). Adoption of fintech: A paradigm shift among millennials as a ‎next normal behaviour. In Fintech and Cryptocurrency (pp. 59–89). ‎Wiley. https://doi.org/10.1002/9781119905028.ch4‎ DOI: https://doi.org/10.1002/9781119905028.ch4

Roslan, F. A. B. M., & Ahmad, N. B. (2023). The rise of AI-powered voice ‎assistants: Analyzing their transformative impact on modern customer ‎service paradigms and consumer expectations. Quarterly Journal of ‎Emerging Technologies and Innovations, 8(3), 33–64.‎

Setyani, V., Zhu, Y. Q., Hidayanto, A. N., Sandhyaduhita, P. I., & Hsiao, B. ‎‎(2019). Exploring the psychological mechanisms from personalized ‎advertisements to urge to buy impulsively on social media. International ‎Journal of Information Management, 48, 96–107. ‎https://doi.org/10.1016/j.ijinfomgt.2019.01.007‎ DOI: https://doi.org/10.1016/j.ijinfomgt.2019.01.007

Suh, K. S., & Chang, S. (2006). User interfaces and consumer perceptions of ‎online stores: The role of telepresence. Behaviour & Information ‎Technology, 25(2), 99–113. ‎https://doi.org/10.1080/01449290500330398‎ DOI: https://doi.org/10.1080/01449290500330398

Tversky, A., & Simonson, I. (1993). Context-dependent preferences. ‎Management Science, 39(10), 1179–1189. ‎https://doi.org/10.1287/mnsc.39.10.1179‎ DOI: https://doi.org/10.1287/mnsc.39.10.1179

West, E. (2022). Buy now: How Amazon branded convenience and normalized ‎monopoly. MIT Press. https://doi.org/10.7551/mitpress/12464.001.0001‎ DOI: https://doi.org/10.7551/mitpress/12464.001.0001

Xiao, S. H., & Nicholson, M. (2013). A multidisciplinary cognitive behavioural ‎framework of impulse buying: A systematic review of the literature. ‎International Journal of Management Reviews, 15(3), 333–356. ‎https://doi.org/10.1111/j.1468-2370.2012.00345.x DOI: https://doi.org/10.1111/j.1468-2370.2012.00345.x

Downloads

Published

2024-01-31

How to Cite

Swathi, V., Nagadeepa, C., KP, J. M., & Hamdan, A. (2024). Voice-Led Urges: Voice Assistants Shape Spontaneous Decisions in Voice Commerce. EuroMid Journal of Business and Tech-Innovation (EJBTI), 3(1), 1-11. https://doi.org/10.51325/ejbti.v3i1.187

Similar Articles

1-10 of 29

You may also start an advanced similarity search for this article.

Most read articles by the same author(s)