Contagion-Based Chatbot Usage Intention: Synthesizing Technology Adoption And Social Contagion Theory
DOI:
https://doi.org/10.58344/jws.v3i2.535Keywords:
Chatbot, Continuous Intention, Social Contagion Theory, Coercive Pressure, Technology AdoptionAbstract
Chatbots have become transformative technology in the banking industry. However, there is still a knowledge gap in understanding the influence of social contagion on chatbot user behavior. This research aims to identify and analyze the intention to use chatbots based on the synthesis of technology adoption and social contagion theories. The research method used is quantitative, employing a survey approach and collecting data through online questionnaires from 300 chatbot users in private banks in Manado. Data analysis was conducted using smartPLS. The research results indicate that factors such as Perceived Effectiveness, Perceived Ease of Use, and Coercive Pressure significantly influence users' intention to continue using chatbots. However, normative pressure and mimicry do not have a significant impact. These findings provide an important contribution to theoretical understanding and practical application in the sustainable use of chatbots in the banking industry, which can assist banks in designing more effective marketing strategies and services.
References
Adam, M., Wessel, M., & Benlian, A. (2021). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31(2), 427–445.
Ahmad, A., Rasul, T., Yousaf, A., & Zaman, U. (2020). Understanding factors influencing elderly diabetic patients' intention to use digital health wearables: extending the technology acceptance model (TAM). Journal of Open Innovation: Technology, Market, and Complexity, 6(3), 81.
Al-Emran, M., Arpaci, I., & Salloum, S. A. (2020). An empirical examination of continuous intention to use m-learning: An integrated model. Education and Information Technologies, 25, 2899–2918.
Alsharo, M., Alnsour, Y., & Alabdallah, M. (2020). How habit affects continuous use: evidence from Jordan’s national health information system. Informatics for Health and Social Care, 45(1), 43–56.
Ashfaq, M., Yun, J., Yu, S., & Loureiro, S. M. C. (2020). I, Chatbot: Modeling the determinants of users’ satisfaction and continuance intention of AI-powered service agents. Telematics and Informatics, 54, 101473.
Carranza, R., Díaz, E., Sánchez-Camacho, C., & Martín-Consuegra, D. (2021). e-Banking adoption: an opportunity for customer value co-creation. Frontiers in Psychology, 11, 621248.
Chaouali, W., & El Hedhli, K. (2018). Toward a contagion-based model of mobile banking adoption. International Journal of Bank Marketing, 37(1), 69–96.
Duarte, P., e Silva, S. C., & Ferreira, M. B. (2018). How convenient is it? Delivering online shopping convenience to enhance customer satisfaction and encourage e-WOM. Journal of Retailing and Consumer Services, 44, 161–169.
Fauzi, A. A. (2019). CRITICAL FACTORS ON SME MANAGEMENT OF ONLINE DELIVERY SERVICE APPLICATION. International Journal of Business and Society, 20(3), 1130–1148.
Foroughi, B., Iranmanesh, M., & Hyun, S. S. (2019). Understanding the determinants of mobile banking continuance usage intention. Journal of Enterprise Information Management, 32(6), 1015–1033.
Gupta, P., Prashar, S., Vijay, T. S., & Parsad, C. (2021). Examining the influence of antecedents of continuous intention to use an informational app: the role of perceived usefulness and perceived ease of use. International Journal of Business Information Systems, 36(2), 270–287.
Hair Jr, J. F., Ringle, C. M., Danks, N. p, Hult, G. T., Sarstedt, M., Bolyai.Babes, & Ray, S. (2021). Review of Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook. In Structural Equation Modeling: A Multidisciplinary Journal. https://doi.org/10.1080/10705511.2022.2108813
Hiqmah, F. (2020). Determinants of the Intention of Social Aid Beneficiaries to Use Banking Self-Service Technology (SST). The International Technology Management Review, 10(1), 12–18.
Hosseini, M., Shajari, S., & Akbarabadi, M. (2022). Identifying multi-channel value co-creator groups in the banking industry. Journal of Retailing and Consumer Services, 65, 102312.
Hwang, S., & Kim, J. (2021). Toward a chatbot for financial sustainability. Sustainability, 13(6), 3173.
Ilhamalimy, R. R., & Ali, H. (2021). Model perceived risk and trust: e-WOM and purchase intention (the role OF trust mediating IN online shopping IN shop Indonesia). Dinasti International Journal of Digital Business Management, 2(2), 204–221.
Jain, M., Kumar, P., Kota, R., & Patel, S. N. (2018). Evaluating and informing the design of chatbots. Proceedings of the 2018 Designing Interactive Systems Conference, 895–906.
Karri, S. P. R., & Kumar, B. S. (2020). Deep learning techniques for implementation of chatbots. 2020 International Conference on Computer Communication and Informatics (ICCCI), 1–5.
Kemp, A., Palmer, E., & Strelan, P. (2019). A taxonomy of factors affecting attitudes towards educational technologies for use with technology acceptance models. British Journal of Educational Technology, 50(5), 2394–2413.
Kiogothe, M. W. (2018). Factors influencing adoption of mobile banking in Kenya: a case of commercial banks’ customers in Nairobi County. Strathmore University.
Lee, C. M. J., Che-Ha, N., & Alwi, S. F. S. (2021). Service customer orientation and social sustainability: The case of small, medium enterprises. Journal of Business Research, 122, 751–760.
Lui, A., & Lamb, G. W. (2018). Artificial intelligence and augmented intelligence collaboration: regaining trust and confidence in the financial sector. Information & Communications Technology Law, 27(3), 267–283.
Masocha, R., & Fatoki, O. (2018). The impact of coercive pressures on sustainability practices of small businesses in South Africa. Sustainability, 10(9), 3032.
Mero, J. (2018). The effects of two-way communication and chat service usage on consumer attitudes in the e-commerce retailing sector. Electronic Markets, 28, 205–217.
Misischia, C. V., Poecze, F., & Strauss, C. (2022). Chatbots in customer service: Their relevance and impact on service quality. Procedia Computer Science, 201, 421–428.
Nguyen, D. M., Chiu, Y.-T. H., & Le, H. D. (2021). Determinants of continuance intention towards banks’ chatbot services in Vietnam: A necessity for sustainable development. Sustainability, 13(14), 7625.
Prasetya, S. A., Erwin, A., & Galinium, M. (2018). Implementing Indonesian language chatbot for e-commerce sites using artificial intelligence markup language (AIML). Prosiding Seminar Nasional Pakar, 313–322.
Purwanto, A. (2021). Partial least squares structural equation modeling (PLS-SEM) analysis for social and management research: a literature review. Journal of Industrial Engineering & Management Research.
Rahmayati, R. (2021). Competition Strategy In The Islamic Banking Industry: An Empirical Review. International Journal Of Business, Economics, And Social Development, 2(2), 65–71.
Richad, R., Vivensius, V., Sfenrianto, S., & Kaburuan, E. R. (2019). Analysis of factors influencing millennials' technology acceptance of chatbots in the banking industry in Indonesia. International Journal of Civil Engineering and Technology, 10(4), 1270–1281.
Rohmatulloh, I. H., & Nugraha, J. (2022). Penggunaan Learning Management System di Pendidikan Tinggi Pada Masa Pandemi Covid-19: Model UTAUT. Jurnal Pendidikan Administrasi Perkantoran (JPAP), 10(1), 48–66.
Wang, Y. M., Ahmad, W., Arshad, M., Yin, H. L., Ahmed, B., & Ali, Z. (2021). Impact of coordination, psychological safety, and job security on employees’ performance: The moderating role of coercive pressure. Sustainability, 13(6), 3175.
Zarouali, B., Van den Broeck, E., Walrave, M., & Poels, K. (2018). Predicting consumer responses to a chatbot on Facebook. Cyberpsychology, Behavior, and Social Networking, 21(8), 491–497.
Zhang, S.-N., Li, Y.-Q., Liu, C.-H., & Ruan, W.-Q. (2019). Critical factors in identifying word-of-mouth enhanced with travel apps: the moderating roles of Confucian culture and the switching cost view. Asia Pacific Journal of Tourism Research, 24(5), 422–442.
Zhang, T., Lu, C., & Kizildag, M. (2018). Banking “on-the-go”: examining consumers’ adoption of mobile banking services. International Journal of Quality and Service Sciences, 10(3), 279–295.
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