Belief triggers to action in artificial intelligence arenas: Exploring the role of AI intention and top management support in multi-level investigation

• Ali Nawaz Khan ^[1] ; Naseer Abbas Khan ^[2]
  1. [1] Hubei Engineering University

     Hubei Engineering University

     China

     
  2. [2] University of Sargodha

     University of Sargodha

     Pakistán

     
• Localización: European Research on Management and Business Economics, ISSN 2444-8834, Vol. 31, Nº. 3, 2025, págs. 14-25
• Idioma: inglés
• DOI: 10.1016/j.iedeen.2025.100285
• Enlaces
  • Texto completo
• Resumen

  • This study investigates the impact of belief about artificial intelligence (AI) on AI continuous usage in Business-to-Business (B2B) contexts through the lens of socio-technical system theory (STST). Using multilevel structural equation modeling of data from 460 employees across 78 software firms in Southern China, this study examines how beliefs about AI influence AI continuous usage, mediated by intention to use AI and moderated by top management support. Results demonstrate that positive belief about AI significantly enhance intention to use AI and AI continuous usage, and also indicate a significant mediating effect of intention to use AI. Top management support emerged as a significant organizational-level moderator of these relationships. The findings of this study contribute to understanding AI adoption in B2B service sectors by integrating human and technical factors within an STST framework.

• Referencias bibliográficas
  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
  • Al-bloush, T. B., & Wahab, N. A. (2019). The influence of usage intention and performance towards the future of online banking. E-. In...
  • Alzahrani, A. I., Mahmud, I., Ramayah, T., Alfarraj, O., & Alalwan, N. (2017). Modelling digital library success using the DeLone and...
  • Ameen, N., Choudrie, J., Jones, P., & Anand, A. (2022). Innovative technologies and small-medium sized enterprises in times of crisis....
  • Atienza-Barba, M., de la, C., del Río-Rama, M., Meseguer-Martínez, A., ´ & BarbaS´ anchez, V. (2024). Artificial intelligence and organizational...
  • Bagozzi, R. P. (2006). Explaining consumer behavior and consumer action: From fragmentation to unity. Seoul Journal of Business, 12(2), 111–143.
  • Barba-S´anchez, V., Meseguer-Martínez, A., Gouveia-Rodrigues, R., & Raposo, M. L. (2024). Effects of digital transformation on firm performance:...
  • Belanger, F., Watson, M., B, M., & Swan, B. R (2013). A multi- level socio-technical systems telecommuting framework. Behaviour and Information...
  • B´elanger, J., Edwards, P. K., & Haiven, L. (2020). Workplace industrial relations and the global challenge. Cornell University Press.
  • Bersin J. (2018). “Talent trends technology disruptions for 2018”. Bliese P.D. (2000). Within-group agreement, non-independence, and reliability: Implications...
  • Cai, X., Khan, N. A., & Egorova, O. (2023). Transactional leadership matters in green creative behaviour through workplace learning and...
  • Cao, X., & Yu, L. (2019). Exploring the influence of excessive social media use at work: A three-dimension usage perspective. International...
  • Chang, Y. Y. (2015). A multilevel examination of high-performance work systems and unit-level organisational ambidexterity. Human Resource...
  • Chatterjee S., & Bhattacharjee. (2020). ‘Adoption of artificial intelligence in higher education: A quantitative analysis using structural...
  • Chatterjee, S., Chaudhuri, R., & Vrontis, D. (2022). Does remote work flexibility enhance organization performance? Moderating role of...
  • Chaveesuk, S., Khalid, B., & Chaiyasoonthorn, W. (2021). Digital payment system innovations: A marketing perspective on intention and...
  • Choudhury, A. (2022). Factors influencing clinicians’ willingness to use an AI-based clinical decision support system. Frontiers in Digital...
  • Doorn, N. (2021). Artificial intelligence in the water domain: Opportunities for responsible use. Science of the Total Environment, 755, Article...
  • Durndell, A., & Haag, Z. (2002). Computer self-efficacy, computer anxiety, attitudes towards the internet and reported experience with...
  • Fishbein M., & Ajzen I. . (1977). Belief, attitude, intention, and behavior: An introduction to theory and research.
  • Fishbein M., & Ajzen I. (1975). Belief, attitude, intention and behavior: An introduction Addison-Wesley, to theory and research.
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal...
  • Govers, M., & van Amelsvoort, P. (2023). A theoretical essay on socio-technical systems design thinking in the era of digital transformation....
  • Grace, K., Salvatier, J., Dafoe, A., Zhang, B., & Evans, O. (2018). When will AI exceed human performance? Evidence from AI experts. Journal...
  • Guenole, N., & Feinzig, S. (2018). The business case for ai in HR: With insights and tips on getting started. IBM Smarter Workforce Institute,...
  • Hair, J. F., Jr. Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM):...
  • Hammer, M., & Champy, J. (2001). Reengineering the corporation: A manifesto for business revolution. New York: Harper Collins.
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation...
  • Hox, J., Moerbeek, M., & Van de Schoot, R. (2017). Multilevel analysis: Techniques and applications. Routledge.
  • Hui, Z., Khan, N. A., & Akhtar, M. (2024). AI-based virtual assistant and transformational leadership in social cognitive theory perspective:...
  • James, L. R., Demaree, R. G., & Wolf, G. (1984). Estimating within-group interrater reliability with and without response bias. Journal...
  • Jarrahi, M. H. (2018). Artificial Intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons,...
  • Kankanhalli, B. C. Y., & Tan, K. K. W. (2005). Contributing knowledge to electronic knowledge repositories: An empirical investigation....
  • Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications...
  • Kasilingam, D. L. (2020). Understanding the attitude and intention to use smartphone chatbots for shopping. Technology in Society, 62, Article...
  • Khan, A. N., & Ali, A. (2018). Factors affecting retailer’s adopti on of mobile payment systems: A SEM-neural network modeling approach....
  • Khan, A. N., & Kwan, H. K. (2025). AI, agility, and environmental performance: A new framework for construction project managers. Journal...
  • Management, 151(3), Article 4025003. https://doi.org/10.1061/JCEMD4.COENG14584 Khan, N. A. (2024). Artificial intelligence, self-efficacy...
  • Khan, N. A., Hassan, S., Pravdina, N., & Akhtar, M. (2023). Drivers of sustainability: Technological and relational factors influencing...
  • Khan, N. A., Maialeh, R., Akhtar, M., & Ramzan, M. (2024b). The role of AI self-efficacy in religious contexts in public sector: The social...
  • Kwak, Y., Ahn, J. W., & Seo, Y. H. (2022). Influence of AI ethics awareness, attitude, anxiety, and self-efficacy on nursing students’...
  • LeBreton, J. M., & Senter, J. L. (2008). Answers to 20 questions about interrater reliability and interrater agreement. Organizational...
  • Lichtenthaler, U. (2019). Extremes of acceptance: Employee attitudes toward artificial intelligence. Journal of Business Strategy, 41, 39–45.
  • Lin, R. R., & Lee, J. C. (2023). The supports provided by artificial intelligence to continuous usage intention of mobile banking: Evidence...
  • Makarius, E. E., Mukherjee, D., Fox, J. D., & Fox, A. K. (2020). Rising with the machines: A sociotechnical framework for bringing artificial...
  • Malodia, S., Mishra, M., Fait, M., Papa, A., & Dezi, L. (2023). To digit or to head? Designing digital transformation journey of SMEs...
  • Marei, A., Daoud, L., Ibrahim, M., & Al-Jabaly, S. (2021). Moderating role of top management support in electronic procurement usage of...
  • Memmedova, K., & Ertuna, B. (2023). Fuzzy logic modelling of the relationship between attitudes towards military services and soldiers’...
  • Moradi, M., & Dass, M. (2022). Applications of artificial intelligence in B2B marketing: Challenges and future directions. Industrial...
  • Pan, Y., Froese, F., Liu, N., Hu, Y., & Ye, M. (2022). The adoption of artificial intelligence in employee recruitment: The influence...
  • Pasmore, W., Winby, S., Mohrman, S. A., & Vanasse, R. (2019). Reflections: Sociotechnical systems design and organization change. Journal...
  • Pelau, C., Dabija, D. C., & Ene, I. (2021). What makes an AI device human-like? The role of interaction quality, empathy and perceived...
  • Podsakoff, P., MacKenzie, S., & Lee, J. (2003). Common method biases in behavioral research: A critical review of the literature and recommended...
  • Polisetty, A., Chakraborty, D., G, S., Kar, A. K., & Pahari, S. (2024). What determines AI adoption in companies? Mixed-method evidence....
  • Preacher, K. J., Zyphur, M. J., & Zhang, Z. (2010). A general multilevel SEM framework for assessing multilevel mediation. Psychological...
  • Rafferty, A. E., & Minbashian, A. (2019). Cognitive beliefs and positive emotions about change: Relationships with employee change readiness...
  • Rafiki, A., Hidayat, S. E., & Al Abdul Razzaq, D. (2019). CRM and organizational performance: A survey on telecommunication companies...
  • Rahman, M. S., Bag, S., Gupta, S., & Sivarajah, U. (2023). Technology readiness of B2B firms and AI-based customer relationship management...
  • Ratchford, B. T. (2020). The history of academic research in marketing and its implications for the future. Spanish Journal of Marketing,...
  • Roppelt, J. S., Kanbach, D. K., & Kraus, S. (2024). Artificial intelligence in healthcare institutions: A systematic literature review...
  • Rusthollkarhu, S., Toukola, S., Aarikka-Stenroos, L., & Mahlam¨aki, T. (2022). ManagingB2B customer journeys in digital era: Four management...
  • Shao, Z., Li, X., Luo, Y., & Benitez, J. (2024). The differential impacts of top management support and transformational supervisory leadership...
  • Sony, M., & Naik, S. (2020). Industry 4.0 integration with socio-technical systems theory: A systematic review and proposed theoretical...
  • Stein, J. P., Messingschlager, T., Gnambs, T., Hutmacher, F., & Appel, M. (2024). Attitudes towards AI: Measurement and associations with...
  • Trist, E., & Bamforth, K. (1951). Some social and psychological consequences of the longwall method of coal-getting. Human Relations,...
  • Trist, E. R. I. C., & Emery, F. R. E. D. (1960). Socio Technical Systems Theory. van Esch, P., Black, J. S., & Ferolie, J. (2019)....
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS...
  • Wang, X., Lin, X., & Shao, B. (2024). Security and privacy protection in developing ethical AI: A mixed-methods study from a marketing...
  • Xiongfei, C., Ali, A., Pitafi, A., Khan, A. N., & Waqas, M. (2021). A socio-technical system approach to knowledge creation and team performance:...
  • Xiongfei, C., Khan, A. N., Ali, A., & Khan, N. A. (2020). Consequences of cyberbullying and social overload while using SNSs: A study...
  • Zhao, Y., & Bacao, F. (2021). How does the pandemic facilitate mobile payment? An investigation on users’ perspective under the COVID-19...