Perception of Gen Z Customers towards Chatbots as Service Agents A Qualitative Study in the Indian Context
Main Article Content
Keywords
Chatbot, Gen Z, customer perception, thematic analysis, India
Abstract
Rapid advancement in Artificial Intelligence (AI) has transformed the dynamics of interaction between organizations and consumers. The rapid emergence and adoption of AI chatbots have ushered in a new era of convenient and efficient customer service. This paper addresses the gap of how Gen Z perceives chatbots as an alternative for service interaction, considering that this sample of the population is relatively more tech savvy and understands technology better. Utilizing semi-structured interviews for in-depth interaction, a thematic analysis reveals six key themes: trust and reliability, nature of interaction, perceived usefulness/ease of use, advantages, disadvantages, and areas of improvement. Gen Z generally views chatbots as limited in handling complex queries, highlighting the importance of human intervention and database expansion. The identified themes provide valuable insights for organizations to highlight strengths and address weaknesses in AI chatbots’ interactions with customers. The findings assist managers responsible for technology implementation in understanding customer pain points, fostering enhanced value for both users and organizations leveraging chatbots. This paper offers a comprehensive analysis of user experiences to illuminate the advantages and shortcomings of chatbots as service agents.
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References
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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. https://doi.org/10.1016/j.ijinfomgt.2019.03.008
Hollebeek, L. D., Sprott, D. E., & Brady, M. K. (2021). Rise of the machines? customer engagement in automated service interactions. International Journal of Service Research, 24(1), 3–8. https://doi.org/10.1177/1094670520975110
Hoyer, W. D., Kroschke, M., Schmitt, B., & Kraume, K. (2020). Transforming the customer experience through new technologies. Journal of Interactive Marketing, 51, 57–71. https://doi.org/https://doi.org/10.1016/j.intmar.2020.04.001
IBM (2022) Global AI Adoption Index 2022. Accessed from https://www.ibm.com/downloads/cas/GVAGA3JP on 25-01-2024
Isaac, O., Ramayah, T., & Mutahar, A. M. (2018). Integrating user satisfaction and performance impact with technology acceptance model (TAM) to examine the internet usage within organizations in Yemen. Asian Journal of Information Technology, 17(1), 60–78. https://doi.org/10.3923/ajit.2018.60.78
Kala, D. (2022). Tourism & hospitality students’ perception towards the use of robots in service organizations: a qualitative study in India. Advances in Hospitality and Tourism Research, 10(2), 306–326. https://doi.org/10.30519/ahtr.969999
Kala, D., & Chaubey, D. S. (2023). Examination of relationships among technology acceptance, student engagement, and perceived learning on tourism-related MOOCs. Journal of Teaching in Travel & Tourism, 23(1), 39–56. https://doi.org/10.1080/15313220.2022.2038342
Kamoonpuri, S. Z., & Sengar, A. (2023). Hi, May AI help you? An analysis of the barriers impeding the implementation and use of artificial intelligence-enabled virtual assistants in retail. Journal of Retailing and Consumer Services, 72, 103258. https://doi.org/10.1016/j.jretconser.2023.103258
Kolnhofer-Derecskei, A., Reicher, R. Z., & Szeghegyi, A. (2017). The X and Y generations’ characteristics comparison. Acta Polytechnica Hungarica, 14(8), 107–125. http://acta.uni-obuda.hu/Kolnhofer-Derecskei_Reicher_Szeghegyi_79.pdf
Kwangsawad, A., & Jattamart, A. (2022). Overcoming customer innovation resistance to the sustainable adoption of chatbot services: A community-enterprise perspective in Thailand. Journal of Innovation and Knowledge, 7(3), 100211. https://doi.org/10.1016/j.jik.2022.100211
Larivière, B., Bowen, D., Andreassen, T. W., Kunz, W., Sirianni, N. J., Voss, C., & De Keyser, A. (2017). Service Encounter 2.0: An investigation into the roles of technology, employees and customers. Journal of Business Research, 79, 238–246. https://doi.org/10.1016/j.jbusres.2017.03.008
Law, R., Leung, D., & Chan, I. C. C. (2020). Progression and development of information and communication technology research in hospitality and tourism: A state-of-the-art review. International Journal of Contemporary Hospitality Management, 32(2), 511–534. https://doi.org/10.1108/IJCHM-07-2018-0586
Li, C. Y., & Zhang, J. T. (2023). Chatbots or me? Consumers’ switching between human agents and conversational agents. Journal of Retailing and Consumer Services, 72, 103264. https://doi.org/10.1016/j.jretconser.2023.103264
Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019). Frontiers: Machines vs. humans: The impact of artificial intelligence chatbot disclosure on customer purchases. Marketing Science, 38(6), 937–947. https://doi.org/10.1287/mksc.2019.1192
Malodia, S., Kaur, P., Ractham, P., Sakashita, M., & Dhir, A. (2022). Why do people avoid and postpone the use of voice assistants for transactional purposes? A perspective from decision avoidance theory. Journal of Business Research, 146(1), 605–618. https://doi.org/10.1016/j.jbusres.2022.03.045
Mcleay, F., Osburg, V. S., Yoganathan, V., & Patterson, A. (2021). Replaced by a robot: Service implications in the age of the machine. Journal of Service Research, 24(1), 104–121. https://doi.org/10.1177/1094670520933354
Meidute-Kavaliauskiene, I., Çiğdem, Ş., Yıldız, B., & Davidavicius, S. (2021). The effect of perceptions on service robot usage intention: A survey study in the service sector. Sustainability, 13(17). https://doi.org/10.3390/su13179655
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Published
Mar 27, 2024
Article Details
How to Cite
Saklani, S., & Kala, D. (2024). Perception of Gen Z Customers towards Chatbots as Service Agents: A Qualitative Study in the Indian Context. Journal of Telecommunications and the Digital Economy, 12(1), 356–376. https://doi.org/10.18080/jtde.v12n1.781
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Special Issue: Emerging Technologies and Innovation for Digital Economy and Transformation
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Author Biography
Sushant Saklani, UPES, India
School of Business, UPES
