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Indian Journal of Marketing

ISSN: 0973-8703 Frequency: Monthly Peer Review: Double-blind Published since: 1968 Language: English
A publication of AMCPL
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New Delhi, India
Indexed in: Scopus Q3 UGC-CARE Group II ABDC: C Google Scholar J-Gate NAAS NISCAIR Crossref

Original Article

Open Access Original Article

Shopping with Voice Assistant: Understanding Consumer Intention and the Mediating Role of Trust

Naveen Kumar1Vasundhra Singh2

1 Assistant Professor, School of Management, Gautam Buddha University, Gautam Buddha Nagar, Greater Noida - 201 308, Uttar Pradesh

2 Research Scholar , School of Management, Gautam Buddha University, Gautam Buddha Nagar, Greater Noida - 201 308, Uttar Pradesh.

Volume 52
Issue 8
Pages 51–65
Year 2022
Received: June 25, 2021 Accepted: May 15, 2022 Published: Aug. 1, 2022
Abstract

Voice assistants are a new smart tool in the market to assist and ease the shopping process for consumers. A voice assistant, along with its in-built artificial intelligence, makes consumer and device interaction more humanlike and personal. Despite a promising debut in the Indian market, there has been limited research on the Indian consumers’ intention to use VA for online shopping. Most of the studies are exploratory in nature and lack a clear theoretical framework. This study aimed to tap the growing trend of the use of voice assistants in the Indian market. The study focused on finding what factors determine consumer intention to shop online using a voice assistant. How does trust upon a voice assistant affect the relationship between these factors and intention? This is a cross-sectional quantitative study. A convenience sample of 121 respondents participated in the study using an online structured questionnaire. The hypotheses testing was done using AMOS SEM. The tests confirmed that information quality and system quality impacted intention only when mediated through trust. Interaction quality, however, only had a direct effect, and no mediation through trust was determined. The study explained how more sincere efforts by VA in information searching and delivering the right information to consumers lead to the development of trust in the VA.

Keywords Voice assistant intention interaction quality system quality information quality trust
How to Cite

Naveen Kumar, Vasundhra Singh (2022). Shopping with Voice Assistant: Understanding Consumer Intention and the Mediating Role of Trust. Indian Journal of Marketing, 52(8), 51–65. https://doi.org/10.17010/ijom/2022/v52/i8/171224

References
  1. Aeschlimann, S., Bleiker, M., Wechner, M., & Gampe, A. (2020). Communicative and social consequences of interactions with voice assistants. Computers in Human Behavior, 112, Article 106466. https://doi.org/10.1016/j.chb.2020.106466
  2. Al-dweeri, R. M., Obeidat, Z. M., Al-dwiry, M. A., Alshurideh, M. T., & Alhorani, A. M. (2017). The impact of e-service quality and e-loyalty on online shopping: Moderating effect of e-satisfaction and e-trust. International Journal of Marketing Studies, 9(2), 92–103. http://doi.org/10.5539/ijms.v9n2p92
  3. Alshibly, H. H. (2014). Evaluating E-HRM success: A validation of the information systems success model. International Journal of Human Resource Studies, 4(3), 107–124. http://doi.org/10.5296/ijhrs.v4i3.5929
  4. Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21(2), 230 – 258. https://doi.org/10.1177/0049124192021002005
  5. Bulsara, H. P., & Vaghela, P. S. (2020). Online shopping intention for consumer electronics products: A literature review and conceptual model. E-Commerce for Future & Trends, 7(1), 24–32. http://doi.org/10.37591%2Fecft.v7i1.2363
  6. Buteau, E., & Lee, J. (2021). Hey Alexa, why do we use voice assistants? The driving factors of voice assistant technology use. Communication Research Reports, 38(5), 336–345. https://doi.org/10.1080/08824096.2021.1980380
  7. Chatterjee, S., & Kundu, A. (2020). Sub-conscious decision mapping and network framework for retail market consumption. Indian Journal of Marketing, 50(2), 35–51. https://doi.org/10.17010/ijom/2020/v50/i2/150440
  8. Copeland, J. (1998). Artificial intelligence: A philosophical introduction. Blackwell Publishers.
  9. Cowan, B. R., Pantidi, N., Coyle, D., Morrissey, K., Clarke, P., Al-Shehri, S., Earley, D., & Bandeira, N. (2017). “What can I help you with?” : Infrequent users' experiences of intelligent personal assistants [Conference Session]. In, Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services (Mobile HCI'17) (Article 43, pp. 1–12). Association for Computing Machinery. https://doi.org/10.1145/3098279.3098539
  10. DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60–95. http://doi.org/10.1287/isre.3.1.60
  11. DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748
  12. Dey, T., & Sharma, L. S. (2019). Determinants of purchasing selected FMCG products in India: Evidence from Agartala city. Indian Journal of Marketing, 49(10), 42–57. https://doi.org/10.17010/ijom/2019/v49/i10/147564
  13. Dreheeb, A. E., Basir, N., & Fabil, N. (2016). Impact of system quality on users' satisfaction in continuation of the use of e-learning system. International Journal of e-Education, e-Business, e-Management and e-Learning, 6(1), 13–20. http://doi.org/10.17706/ijeeee.2016.6.1.13-20
  14. Ekinci, Y., & Dawes, P. L. (2009). Consumer perceptions of frontline service employee personality traits, interaction quality, and consumer satisfaction. The Service Industries Journal, 29(4), 503–521. http://doi.org/10.1080/02642060802283113
  15. Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382–388. https://doi.org/10.1177/002224378101800313
  16. Forsythe, S. M., Dai, B., & Kwon, W (2014). The impact of online shopping experience on risk perceptions and online purchase: Does product category matter? Journal of Electronic Commerce Research, 15(1), 13 – 24.
  17. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Inexperience and experience with online stores: The importance of TAM and trust. IEEE Transactions on Engineering Management, 50(3), 307–321. http://doi.org/10.1109/TEM.2003.817277
  18. Ghasemaghaei, M., & Hassanein, K. (2015). Online information quality and consumer satisfaction: The moderating roles of contextual factors – A meta-analysis. Information & Management, 52(8), 965–981. https://doi.org/10.1016/j.im.2015.07.001
  19. Goksel Canbek, N., & Mutlu, M. E. (2016). On the track of artificial intelligence: Learning with intelligent personal assistants. Journal of Human Sciences, 13(1), 592–601. http://doi.org/10.14687/IJHS.V13I1.3549
  20. Guru, S., Bhatt, N., & Agrawal, N. (2021). Prioritization of dimensions of online trust using analytical hierarchy approach. Indian Journal of Marketing, 51(5–7), 81–92. https://doi.org/10.17010/ijom/2021/v51/i5-7/163886
  21. Ha, N. T., Nguyen, T. L., Pham, T. V., & Nguyen, T. H. (2021). Factors influencing online shopping intention: An empirical study in Vietnam. The Journal of Asian Finance, Economics and Business, 8(3), 1257–1266. https://doi.org/10.13106/jafeb.2021.vol8.no3.1257
  22. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis. Prentice-Hall.
  23. Hoffman, D. L., & Novak, T. P. (2017). Consumer and object experience in the internet of things: An assemblage theory approach. Journal of Consumer Research, 44(6), 1178–1204. http://doi.org/10.1093/JCR/UCX105
  24. Hoy, M. B. (2018). Alexa, Siri, Cortana, and more: An introduction to voice assistants. Medical Reference Services Quarterly, 37(1), 81–88. https://doi.org/10.1080/02763869.2018.1404391
  25. Jain, K., Gautam, S., & Pasricha, D. (2018). The pleasure and the guilt-Impulse purchase and post purchase regret: A study of young Indian consumers. Indian Journal of Marketing, 48(3), 49 – 63. https://doi.org/ 10.17010/ijom/2018/v48/i3/121984
  26. Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). Trust and satisfaction, two stepping stones for successful e-commerce relationships: A longitudinal exploration. Information Systems Research, 20(2), 237–257. http://doi.org/10.1287/isre.1080.0188
  27. Klein, A. M., Hinderks, A., Schrepp, M., & Thomaschewski, J. (2020). Measuring user experience quality of voice assistants. In, 2020 15th Iberian Conference on Information Systems and Technologies (CISTI) (pp. 1–4). IEEE. http://doi.org/10.23919/CISTI49556.2020.9140966
  28. Kumar, R., & Kaushal, S. K. (2019). A study of factors affecting consumer behavior towards electronic durable goods. Indian Journal of Marketing, 49(7), 35–48. https://doi.org/10.17010/ijom/2019/v49/i7/145403
  29. Mari, A. (2019). Voice commerce: Understanding shopping-related voice assistants and their effect on brands [Conference Session]. IMMAA Annual Conference, Northwestern University, Qatar, Doha. https://doi.org/10.5167/uzh-197725
  30. Mayer, R. E., Sobko, K., & Mautone, P. D. (2003). Social cues in multimedia learning: Role of speaker's voice. Journal of Educational Psychology, 95(2), 419–425. https://doi.org/10.1037/0022-0663.95.2.419
  31. Nasirian, F., Ahmadian, M., & Lee, O.-K. (2017). AI-based voice assistant systems: Evaluating from the interaction and trust perspectives [Conference Session]. In, 23rd Americas Conference on Information Systems. Curran Associates, Inc. https://www.proceedings.com/38301.html
  32. Nattuvathuckal, B., Mekoth, N., & Sony, M. (2020). Role of consumption intent in service quality: Perceived benefit relationship. Indian Journal of Marketing, 50(3), 22–32. https://doi.org/10.17010/ijom/2020/v50/i3/151027
  33. Nunnally, J. C. (1994). Psychometric theory (3E). Tata McGraw-Hill Education.
  34. Ojo, A. I. (2017). Validation of the DeLone and McLean information systems success model. Healthcare Informatics Research, 23(1), 60 – 66. https://doi.org/10.4258/hir.2017.23.1.60
  35. Ponte, E. B., Carvajal-Trujillo, E., & Escobar-Rodríguez, T. (2015). Influence of trust and perceived value on the intention to purchase travel online: Integrating the effects of assurance on trust antecedents. Tourism Management, 47, 286–302. https://doi.org/10.1016/j.tourman.2014.10.009
  36. Poushneh, A. (2021). Humanizing voice assistant: The impact of voice assistant personality on consumers' attitudes and behaviors. Journal of Retailing and Consumer Services, 58, Article 102283. https://doi.org/10.1016/j.jretconser.2020.102283
  37. Ramos, D. (2018, April 16). Voice assistants: How artificial intelligence assistants are changing our lives every day. Smartsheet. https://www.smartsheet.com/voice-assistants-artificial-intelligence
  38. Rana, N. P., Dwivedi, Y. K., Williams, M. D., & Weerakkody, V. (2015). Investigating success of an e-government initiative: Validation of an integrated IS success model. Information Systems Frontiers, 17, 127–142. https://doi.org/10.1007/s10796-014-9504-7
  39. Rashid, A., & Rokade, V. (2021). Multi-criterion decision making approach to assess retail service quality: A market perspective from Iraq. Prabandhan: Indian Journal of Management, 14(3), 49–63. https://doi.org/10.17010/pijom/2021/v14i3/158156
  40. Schweitzer, F., Belk, R., Jordan, W., & Ortner, M. (2019). Servant, friend or master? The relationships users build with voice-controlled smart devices. Journal of Marketing Management, 35(7 – 8), 693–715. https://doi.org/10.1080/0267257X.2019.1596970
  41. Siddiqui, A., & Siddiqui, M. (2021). Buy my trust, before I buy your food – Consumers' insights for online food delivery platforms during the COVID-19 pandemic. Indian Journal of Marketing, 51(12), 26 – 40. https://doi.org/10.17010/ijom/2021/v51/i12/167218
  42. Singh, N., & Nigam, S. (2021). Value-based segmentation of generation Z women consumers of India: Replication and validation of model. Prabandhan: Indian Journal of Management, 14(10), 8–23. https://doi.org/10.17010/pijom/2021/v14i10/166641
  43. Song, Y. W. (2019). User acceptance of artificial intelligence (AI) virtual assistant: An extension of the technology acceptance model (Doctoral dissertation). The University of Texas at Austin. https://doi.org/10.26153/tsw/2132
  44. Tanwar, S. (2020, February 10). Indians are suspicious of voice assistants, but not enough to forgo their convenience. Quartz India. https://qz.com/india/1799767/indians-love-siri-alexa-google-assistant-for-their-convenience/
  45. Velev, D., & Zlateva, P. (2019). Analysis of v-commerce as the new online sales channel. International Journal of e-Education, e-Business, e-Management and e-Learning, 9(2), 131–137. https://doi.org/10.17706/ijeeee.2019.9.2.131-137
  46. Whang, C. (2018). Voice shopping: The effect of the consumer-voice assistant parasocial relationship on the consumer's perception and decision making (Doctoral dissertation). University of Minnesota, United States.
  47. Whang, C., & Im, H. (2018). Does recommendation matter for trusting beliefs and trusting intentions? Focused on different types of recommender system and sponsored recommendation. International Journal of Retail & Distribution Management, 46(10), 944–958. https://doi.org/10.1108/IJRDM-06-2017-0122
  48. Yang, H., & Lee, H. (2019). Understanding user behavior of virtual personal assistant devices. Information Systems and e-Business Management, 17, 65–87. https://doi.org/10.1007/s10257-018-0375-1
  49. Yi, C.-C., Liao, P. - W., Huang, C.-F., & Hwang, I.-H. (2009). Acceptance of mobile learning: A respecification and validation of information system success. International Journal of Educational and Pedagogical Sciences, 3(5), 475–479.
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