AI Adoption in B2B Markets: Exploring Drivers and Barriers through Behavioural Reasoning Theory and a Care Approach

Authors

Keywords:

Technology Adoption, Artificial Intelligence, Care Value, B2B Marketing

Abstract

This study investigates AI adoption in B2B marketing within Iranian steel industry by integrating Behavioral Reasoning Theory with a care approach. Specifically, it examines how care value, reasons for and against AI adoption, and attitude shape intention adoption, while also assessing the moderating role of brand reputation. A quantitative survey-based design was employed, and data were collected from 275 respondents working in the Iranian steel industry. The proposed model was tested using PLS-SEM, with moderation effects assessed through PROCESS Macro. The findings indicate that attitude is a strong predictor of AI intention adoption and serves as a key mechanism through which organizational reasons influence intention. The results further show that both enabling and inhibiting reasons of AI adoption. By extending BRT with care value in B2B context, this study contributes to the AI adoption literature and offers practical insights for firms seeking to implement AI responsibly and effectively.

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References

Acikgoz, F., Perez‐Vega, R., Okumus, F., & Stylos, N. (2023). Consumer engagement with AI‐powered voice assistants: A behavioral reasoning perspective. Psychology & Marketing, 40(11), 2226–2243. https://doi.org/10.1002/mar.21873

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Bagozzi, R. P. (1992). The Self-Regulation of Attitudes, Intentions, and Behavior. Social Psychology Quarterly, 55(2), 178. https://doi.org/10.2307/2786945

Bian, Q., & Forsythe, S. (2012). Purchase intention for luxury brands: A cross cultural comparison. Journal of Business Research, 65(10), 1443–1451. https://doi.org/10.1016/j.jbusres.2011.10.010

Claudy, M. C., & Peterson, M. (2014). Understanding the Underutilization of Urban Bicycle Commuting: A Behavioral Reasoning Perspective. Journal of Public Policy & Marketing, 33(2), 173–187. https://doi.org/10.1509/jppm.13.087

Claudy, M. C., Garcia, R., & O’Driscoll, A. (2015). Consumer resistance to innovation—a behavioral reasoning perspective. Journal of the Academy of Marketing Science, 43(4), 528–544. https://doi.org/10.1007/s11747-014-0399-0

Cohn, J. (2020). In A Different Code: Artificial Intelligence and The Ethics of Care. The International Review of Information Ethics, 28. https://doi.org/10.29173/irie383

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Dowling, G. R. (2016). Defining and Measuring Corporate Reputations. European Management Review, 13(3), 207–223. https://doi.org/10.1111/emre.12081

Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., …, & Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., …, & Wright, R. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642

Efron, B. (1992). Bootstrap Methods: Another Look at the Jackknife. Springer Series in Statistics, 569–593. https://doi.org/10.1007/978-1-4612-4380-9_41

Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5

Fombrun, C. J. (1996). Reputation: Realizing value from the corporate image. Harvard Business School Press.

Fombrun, C., & Shanley, M. (1990). WHAT'S IN A NAME? REPUTATION BUILDING AND CORPORATE STRATEGY. Academy of Management Journal, 33(2), 233–258. https://doi.org/10.2307/256324

Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

Gesk, T. S., & Leyer, M. (2022). Artificial intelligence in public services: When and why citizens accept its usage. Government Information Quarterly, 39(3), 101704. https://doi.org/10.1016/j.giq.2022.101704

Gilligan, C. (1982). In a different voice: Psychological theory and women’s development. Harvard University Press.

Grewal, D., Guha, A., Satornino, C. B., & Schweiger, E. B. (2021). Artificial intelligence: The light and the darkness. Journal of Business Research, 136, 229–236. https://doi.org/10.1016/j.jbusres.2021.07.043

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

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203

Hartmann, P., & Apaolaza-Ibáñez, V. (2012). Consumer attitude and purchase intention toward green energy brands: The roles of psychological benefits and environmental concern. Journal of Business Research, 65(9), 1254–1263. https://doi.org/10.1016/j.jbusres.2011.11.001

Hayes, A. F., Montoya, A. K., & Rockwood, N. J. (2017). The Analysis of Mechanisms and Their Contingencies: PROCESS versus Structural Equation Modeling. Australasian Marketing Journal, 25(1), 76–81. https://doi.org/10.1016/j.ausmj.2017.02.001

Helm, S. (2007). One reputation or many?. Corporate Communications: An International Journal, 12(3), 238–254. https://doi.org/10.1108/13563280710776842

Huang, M. H., & Rust, R. T. (2018). Artificial Intelligence in Service. Journal of Service Research, 21(2), 155–172. https://doi.org/10.1177/1094670517752459

Kahneman, D., & Tversky, A. (1982). The Psychology of Preferences. Scientific American, 246(1), 160–173. https://doi.org/10.1038/scientificamerican0182-160

Lalicic, L., & Weismayer, C. (2021). Consumers’ reasons and perceived value co-creation of using artificial intelligence-enabled travel service agents. Journal of Business Research, 129, 891–901. https://doi.org/10.1016/j.jbusres.2020.11.005

Paschen, J., Kietzmann, J., & Kietzmann, T. C. (2019). Artificial intelligence (AI) and its implications for market knowledge in B2B marketing. Journal of Business & Industrial Marketing, 34(7), 1410–1419. https://doi.org/10.1108/JBIM-10-2018-0295

Paschen, J., Wilson, M., & Ferreira, J. J. (2020). Collaborative intelligence: How human and artificial intelligence create value along the B2B sales funnel. Business Horizons, 63(3), 403–414. https://doi.org/10.1016/j.bushor.2020.01.003

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

Rahman, M. S., Bag, S., Gupta, S., & Sivarajah, U. (2023). Technology readiness of B2B firms and AI-based customer relationship management capability for enhancing social sustainability performance. Journal of Business Research, 156, 113525. https://doi.org/10.1016/j.jbusres.2022.113525

Raisch, S., & Krakowski, S. (2021). Artificial Intelligence and Management: The Automation–Augmentation Paradox. Academy of Management Review, 46(1), 192–210. https://doi.org/10.5465/amr.2018.0072

Rammer, C., Fernández, G. P., & Czarnitzki, D. (2022). Artificial intelligence and industrial innovation: Evidence from German firm-level data. Research Policy, 51(7), 104555. https://doi.org/10.1016/j.respol.2022.104555

Rasheed, H. M. W., He, Y., Khizar, H. M. U., & Abbas, H. S. M. (2023). Exploring Consumer-Robot interaction in the hospitality sector: Unpacking the reasons for adoption (or resistance) to artificial intelligence. Technological Forecasting and Social Change, 192, 122555. https://doi.org/10.1016/j.techfore.2023.122555

Ryan, J., & Casidy, R. (2018). The role of brand reputation in organic food consumption: A behavioral reasoning perspective. Journal of Retailing and Consumer Services, 41, 239–247. https://doi.org/10.1016/j.jretconser.2018.01.002

Sahu, A. K., Padhy, R. K., & Dhir, A. (2020). Envisioning the Future of Behavioral Decision-Making: A Systematic Literature Review of Behavioral Reasoning Theory. Australasian Marketing Journal, 28(4), 145–159. https://doi.org/10.1016/j.ausmj.2020.05.001

Sarstedt, M., Hair, J. F., Pick, M., Liengaard, B. D., Radomir, L. c. m., & Ringle, C. M. (2022). Progress in partial least squares structural equation modeling use in marketing research in the last decade. Psychology & Marketing, 39(5), 1035–1064. https://doi.org/10.1002/mar.21640

Schwartz, S. H. (2012). An Overview of the Schwartz Theory of Basic Values. Online Readings in Psychology and Culture, 2(1). https://doi.org/10.9707/2307-0919.1116

Tronto, J. C. (1993). Moral boundaries: A political argument for an ethic of care. Routledge.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward A Unified View1. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

Villegas-Galaviz, C., & Martin, K. (2024). Moral distance, AI, and the ethics of care. AI & SOCIETY, 39(4), 1695–1706. https://doi.org/10.1007/s00146-023-01642-z

Westaby, J. D. (2005). Behavioral reasoning theory: Identifying new linkages underlying intentions and behavior. Organizational Behavior and Human Decision Processes, 98(2), 97–120. https://doi.org/10.1016/j.obhdp.2005.07.003

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Akbari Tari, S., & Makizadeh, V. . (2026). AI Adoption in B2B Markets: Exploring Drivers and Barriers through Behavioural Reasoning Theory and a Care Approach. AI and Tech in Behavioral and Social Sciences. https://journals.kmanpub.com/index.php/aitechbesosci/article/view/6503