Do AI-Based Voice Assistants Influence Brand Continuous Usage? The Mediating Role of AI-Driven Customer Experience
DOI:
https://doi.org/10.33423/jabe.v26i2.6973Keywords:
business, economics, artificial intelligence, AI-based voice assistants, customer experience, continuous usage, mobile phone brandAbstract
This study aimed to assess the influence of artificial intelligence (AI) voice assistant (VA) on customer experience, resulting in the continuous use of mobile brands. Specifically, this article assesses the role of hedonic, utilitarian, and social benefits provided by AIVA on customer experience and continuous usage of a mobile phone brand. Using a primary data collection instrument, the quantitative approach was adopted to examine the study’s variables. Data from 348 valid responses were used for the analysis based on structural equation modeling (SEM) with AMOS version 23. Three main factors were identified to influence customer experience, which results in continuous usage of a mobile phone brand. These factors are social benefits, hedonic benefits, and utilitarian benefits. In conclusion, a significant and positive relationship exists between AI-enabled customer experience and brand continuous usage. It recommended that mobile brands consider and research their prospects’ and customers’ social, hedonic, and utilitarian needs to provide them with desired products and experiences.
References
Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548.
Athwal, N., Istanbulluoglu, D., & McCormack, S.E. (2019). The allure of luxury brands’ social media activities: A uses and gratifications perspective. Information Technology & People, 32(3), 603–626.
Balakrishnan, J., & Dwivedi, Y.K. (2021). Role of cognitive absorption in building user trust and experience. Psychology & Marketing, 38(4), 643–668.
Balakrishnan, J., Dwivedi, Y.K., Hughes, L., & Boy, F. (2021). Enablers and inhibitors of AI-powered voice assistants: A dual-factor approach by integrating the status quo bias and technology acceptance model. Information Systems Frontiers, pp. 1–22.
Bilgihan, A., Kandampully, J., & Zhang, T. (2016). Towards a unified customer experience in online shopping environments: Antecedents and outcomes. International Journal of Quality and Service Sciences, 8(1), 102–119.
Camilleri, M.A., & Falzon, L. (2021). Understanding motivations to use online streaming services: Integrating the technology acceptance model (TAM) and the uses and gratifications theory (UGT). Spanish Journal of Marketing-ESIC, 25(2), 217–238.
Cerekovic, A., Aran, O., & Gatica-Perez, D. (2016). Rapport with virtual agents: What do human social cues and personality explain? IEEE Transactions on Affective Computing, 8(3), 382–395.
Chattaraman, V., Kwon, W.S., Gilbert, J.E., & Ross, K. (2019). Should AI-Based, conversational digital assistants employ social-or task-oriented interaction style? A task-competency and reciprocity perspective for older adults. Computers in Human Behavior, 90, 315–330.
Chau, P.Y., & Lai, V.S. (2003). An empirical investigation of the determinants of user acceptance of internet banking. Journal of Organizational Computing and Electronic Commerce, 13(2), 123–145.
Chen, J.S., Tsou, H.T., Chou, C.Y., & Ciou, C.H. (2020). Effect of multichannel service delivery quality on customers’ continued engagement intention: A customer experience perspective. Asia Pacific Journal of Marketing and Logistics, 32(2), 473–494.
Christino, J., Silva, T., Moura, L.R., & Fonseca, L.H. (2020). Antecedents and consequents of brand love in the smartphone market: An extended study of the impact of switching cost. Journal of Promotion Management, 26(3), 301–321.
Collier, J. (2020). Applied structural equation modeling using AMOS: Basic to advanced techniques. Routledge.
Cummins, J. (2021). Rethinking the education of multilingual learners: A critical analysis of theoretical concepts (Vol. 19). Multilingual Matters.
Dash, G., & Paul, J. (2021). CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting. Technological Forecasting and Social Change, 173, 121092.
Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, pp. 319–340.
Dhir, A., & Tsai, C.C. (2017). Understanding the relationship between intensity and gratifications of Facebook use among adolescents and young adults. Telematics and Informatics, 34(4), 350–364.
Diamantopoulos, A., & Siguaw, J.A. (2006). Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration. British Journal of Management, 17(4), 263–282.
Dobrota, M., Nikodijević, A., & Mihailović, D. (2012). Influence of the customer experience on satisfaction with mobile phones. Journal of Engineering Management and Competitiveness (JEMC), 2(2), 69–75.
Dou, W., Wang, G., & Zhou, N. (2006). Generational and regional differences in media consumption patterns of Chinese generation X consumers. Journal of Advertising, 35(2), 101–110.
Fernandes, T., & Oliveira, E. (2021). Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption. Journal of Business Research, 122, 180–191.
Flanagin, A.J., & Metzger, M.J. (2001). Internet use in the contemporary media environment. Human Communication Research, 27(1), 153–181.
Gallego, M.D., Bueno, S., & Noyes, J. (2016). Second Life adoption in education: A motivational model based on Uses and Gratifications theory. Computers & Education, 100, 81–93.
Gursoy, D., Chi, O.H., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157–169.
Hair, J.F., Gabriel, M., & Patel, V. (2014). AMOS covariance-based structural equation modeling (CB-SEM): Guidelines on its application as a marketing research tool. Brazilian Journal of Marketing, 13(2).
Hamouda, M. (2021). Purchase intention through mobile applications: A customer experience lens. International Journal of Retail & Distribution Management, 49(10), 1464–1480.
Heenrink, M., Krose, B., Wielinga, B., & Evers, V. (2008). Enjoyment, intention to use and actual use of a conversational robot by elderly people. In Proceeding of the 3rd ACM/IEEE International Conference on Human Robot Interaction (pp. 113–120). New York, NY
Herzog, H. (1940). Professor quiz: A gratification study. In P.F. Lazarsfeld (Ed.), Radio and the printed page (pp. 64–93). Duell, Sloan & Pearce.
Herzog, H. (1944). What do we really know about daytime serial listeners. In P.F. Lazarsfeld, & F.N. Stanton (Eds.), Radio research 1942–1943 (pp. 3–33). Duell, Sloan & Pearce.
Hong, S.J., & Tam, K.Y. (2006). Understanding the adoption of multipurpose information appliances: The case of mobile data services. Information Systems Research, 17(2), 162–179.
Hoy, M.B. (2018). Alexa, Siri, Cortana, and more: An introduction to voice assistants. Medical Reference Services Quarterly, 37(1), 81–88.
Hsiao, M.H., & Chen, L.C. (2015). Smart phone demand: An empirical study on the relationships between phone handset, internet access and mobile services. Telematics and Informatics, 32(1), 158–168.
Hsu, C.L., & Lin, J.C.C. (2016). Effect of perceived value and social influences on mobile app stickiness and in-app purchase intention. Technological Forecasting and Social Change, 108, 42–53.
Huang, C.C. (2017). The impacts of brand experiences on brand loyalty: Mediators of brand love and trust. Management Decision, 55(5), 915–934.
Huang, M.H., & Rust, R.T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155–172.
Huang, M.H., & Rust, R.T. (2020). Engaged to a robot? The role of AI in service. Journal of Service Research, 109467052090226. https:// doi.org/10.1177/1094670520902266.
Huang, M.H., & Rust, R.T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30–50.
Kalkbrenner, M.T. (2023). Alpha, omega, and H internal consistency reliability estimates: Reviewing these options and when to use them. Counseling Outcome Research and Evaluation, 14(1), 77–88.
Katz, E., Blumler, J.G., & Gurevitch, M. (1974). Utilization of mass communication by the individual. In J.G. Blumler, & E. Katz (Eds.). The use of mass communications: Current perspectives on gratifications research. Beverly Hills, CA: Sage.
Kim, D., Kim, S., Ha, H.T., & Kim, S. (2020a). Smartphone-based image analysis coupled to paper-based colorimetric devices. Current Applied Physics, 20(9), 1013–1018.
Kim, J., Lee, H., & Lee, J. (2020b). Smartphone preferences and brand loyalty: A discrete choice model reflecting the reference point and peer effect. Journal of Retailing and Consumer Services, 52, 101907.
Korhan, O., & Ersoy, M. (2016). Usability and functionality factors of the social network site application users from the perspective of uses and gratification theory. Quality & Quantity, 50, 1799–1816.
Laricchia, F. (2023, June 6). Smartphone Statistics: Adoption, Usage, and Market Share. Retrieved from https://www.statista.com/topics/840/smartphones/#topic_Overview
Lee, K.Y., Sheehan, L., Lee, K., Chang, Y., (2021). The continuation and recommendation intention of artificial intelligence-based voice assistant systems (AIVAS): The influence of personal traits. Internet Res., 31(5), 1899–1939.
Leung, L., & Wei, R. (1998). The gratifications of pager use: Sociability, information-seeking, entertainment, utility, and fashion and status. Telematics and Informatics, 15(4), 253–264.
Leung, L., & Wei, R. (1998a). Factors influencing the adoption of interactive TV in Hong Kong: Implications for advertising. Asian Journal of Communication, 8(2), 124–147.
Leung, L., & Wei, R. (1998b). The gratifications of pager use: Sociability, information-seeking, entertainment, utility, and fashion and status. Telematics and Informatics, 15(4), 253–264.
Leung, L., & Wei, R. (2000). More than just talk on the move: Uses and gratifications of the cellular phone. Journalism & Mass Communication Quarterly, 77(2), 308–320.
Liao, J., Li, M., Wei, H., & Tong, Z. (2021). Antecedents of smartphone brand switching: A push–pull–mooring framework. Asia Pacific Journal of Marketing and Logistics, 33(7), 1596–1614.
Liu-Thompkins, Y., Okazaki, S., & Li, H. (2022). Artificial empathy in marketing interactions: Bridging the human-AI gap in affective and social customer experience. Journal of the Academy of Marketing Science, 50(6), 1198–1218.
Lombard, M. (1995). Direct responses to people on the screen: Television and personal space. Communication Research, 22(3), 288–324.
Lou, C., & Xie, Q. (2021). Something social, something entertaining? How digital content marketing augments consumer experience and brand loyalty. International Journal of Advertising, 40(3), 376–402.
McLean, G., & Osei-Frimpong, K. (2019). Hey Alexa… Examine the variables influencing the use of artificial intelligent in-home voice assistants. Computers in Human Behavior, 99, 28–37.
McLean, G., Al-Nabhani, K., & Wilson, A. (2018). Developing a mobile applications customer experience model (MACE) –Implications for retailers. Journal of Business Research, 85, 325–336.
Menon, D. (2022). Purchase and continuation intentions of over-the-top (OTT) video streaming platform subscriptions: A uses and gratification theory perspective. Telematics and Informatics Reports, 5, 100006.
Mixon-Webster, J. (2020). The Promise of Threat. The Yale Review, 108(4), 110–111.
Molinillo, S., Aguilar-Illescas, R., Anaya-Sanchez, R., & Carvajal-Trujillo, E. (2022). The customer retail app experience: Implications for customer loyalty. Journal of Retailing and Consumer Services, 65, 102842.
Moon, H.Y., & Lee, B.Y. (2022). Self-service technologies (SSTs) in airline services: Multimediating effects of flow experience and SST evaluation. International Journal of Contemporary Hospitality Management, 34(6), 2176–2198.
Moon, Y. (2000). Intimate exchanges: Using computers to elicit self-disclosure from consumers. Journal of Consumer Research, 26(4), 323–339.
Moore, S., Bulmer, S., & Elms, J. (2022). The social significance of AI in retail on customer experience and shopping practices. Journal of Retailing and Consumer Services, 64, 102755.
Morkunas, M., & Rudienė, E. (2020). The impact of social servicescape factors on customers’ satisfaction and repurchase intentions in mid-range restaurants in Baltic states. Journal of Open Innovation: Technology, Market, and Complexity, 6(3), 77.
Nass, C., & Moon, Y. (2000). Machines and mindlessness: Social responses to computers. Journal of Social Issues, 56(1), 81–103.
Nicolescu, L., & Tudorache, M.T. (2022). Human-computer interaction in customer service: The experience with AI chatbots—A systematic literature review. Electronics, 11(10), 1579.
Osbourne, E., & Arora, A.S. (2022). Artificial Intelligence (AI) in marketing: How AI supports marketers throughout the consumer journey. In Managing Social Robotics and Socio-cultural Business Norms: Parallel Worlds of Emerging AI and Human Virtues (pp. 75–90). Cham: Springer International Publishing.
Pawar, S.K., & Vispute, S.A. (2023). Exploring international students’ adoption of AI-enabled voice assistants in enrolment decision making: A grounded theory approach. Journal of Marketing for Higher Education, pp. 1–20.
Petroc, T. (2023). Smartphone mobile network subscriptions worldwide 2016-2028. Statista.com. Retrieved from https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/
Pitardi, V., & Marriott, H.R. (2021). Alexa, she’s not human but… Unveiling the drivers of consumers’ trust in voice‐based artificial intelligence. Psychology & Marketing, 38(4), 626–642.
Ponsignon, F. (2023). Making the customer experience journey more hedonic in a traditionally utilitarian service context: A case study. Journal of Service Management, 34(2), 294–315.
Qing, T., & Haiying, D. (2021). How to achieve consumer continuance intention toward branded apps—From the consumer–brand engagement perspective. Journal of Retailing and Consumer Services, 60, 102486.
Ruggiero, T.E. (2000). Uses and gratifications theory in the 21st century. Mass Communication & Society, 3(1), 3–37.
Schuitema, G., Anable, J., Skippon, S., & Kinnear, N. (2013). The role of instrumental, hedonic and symbolic attributes in the intention to adopt electric vehicles. Transportation Research Part A: Policy and Practice, 48, 39–49.
Seduram, L., Perumal, S., & Shaari, H.B. (2016). Theoretical examination of mobile phone brand loyalty. Int. Acad. Res. J. Bus. Technol, 2, 1–7.
Sheng, M.L., & Teo, T.S. (2012). Product attributes and brand equity in the mobile domain: The mediating role of customer experience. International Journal of Information Management, 32(2), 139–146.
Song, H., Altinay, L., Sun, N., & Wang, X.L. (2018). The influence of social interactions on senior customers’ experiences and loneliness. International Journal of Contemporary Hospitality Management, 30(8), 2773–2790.
Stein, A., & Ramaseshan, B. (2020). The customer experience–loyalty link: Moderating role of motivation orientation. Journal of Service Management, 31(1), 51–78.
Sunnebo, D. (2018). Xiaomi takes aim at Europe- Kantar World Panel. Retrieved from https://www.kantarworldpanel.com/global/News/Xiaomi-takes-aim-at-Europe
Van der Wurff, R. (2011). Are news media substitutes? Gratifications, contents, and uses. Journal of Media Economics, 24(3), 139–157.
Van Doorn, J., Mende, M., Noble, S.M., Hulland, J., Ostrom, A.L., Grewal, D., & Petersen, J.A. (2017). Domo arigato Mr. Roboto: Emergence of automated social presence in organizational frontlines and customers’ service experiences. Journal of Service Research, 20(1), 43–58.
Wang, X., Lin, X., & Gonzales, A. (2023). The impacts of social media on job satisfaction: Task-oriented use and relationship-oriented use. International Journal of Human–Computer Interaction, pp. 1–16.
Wang, X., Lin, X., & Liu, Z. (2019). Understanding consumers’ post-adoption behavior in sharing economy services. Journal of Computer Information Systems.
Xie, C., Wang, Y., & Cheng, Y. (2022). Does artificial intelligence satisfy you? A meta-analysis of user gratification and user satisfaction with AI-powered chatbots. International Journal of Human–Computer Interaction, pp. 1–11.
Yang, H.J., Fang, M., Yao, J., & Su, M. (2023). Green cooperation in last-mile logistics and consumer loyalty: An empirical analysis of a theoretical framework. Journal of Retailing and Consumer Services, 73, 103308.
Yang, Y., & Lee, L.C. (2010). Dynamics and heterogeneity in the process of human frailty and aging: Evidence from the US older adult population. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 65(2), 246–255.
Yuan, C., Zhang, C., & Wang, S. (2022). Social anxiety as a moderator in consumer willingness to accept AI assistants based on utilitarian and hedonic values. Journal of Retailing and Consumer Services, 65, 102878.
Zaidi, N., Tyagi, P., & Singh, A. (2019). Nokia’s comeback—Is it revival of an iconic brand? Asian Case Research Journal, 23(02), 415–426.
Zhou, T. (2011). An empirical examination of users’ post-adoption behaviour of mobile services. Behaviour & Information Technology, 30(2), 241–250.
