Research Paper
Article citation: Mishra, R., & Singh, R. K. (2026). Exploring AI-enabled digital service platform adoption in industrial business-to-business firms through a mixed-method approach. Industrial Marketing Management, 135, 279–298. https://doi.org/10.1016/j.indmarman.2026.04.003
Abstract
Despite the increasing applications of artificial intelligence (AI)-enabled digital service platforms in business-to-business (B2B) industrial marketing, studies in this domain remain limited, especially in the context of AI-enabled platforms in industrial settings and emerging economies, such as India. To address this gap, the present study employs an exploratory sequential mixed-methods design. In the first phase, exploratory focus group interviews were conducted with industry practitioners to identify context-specific factors influencing the adoption of AI-enabled digital service platforms. Thereafter, using the insights from this phase, a conceptual model was developed that extends the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB) by incorporating perceived service quality and transformational leadership. In the second phase, the proposed framework was empirically analysed using survey data from 300 industrial B2B firms through covariance-based structural equation modelling.
The findings reveal that perceived ease of use, perceived usefulness, and perceived service quality significantly influence user attitudes, while perceived service quality, subjective norms, and attitude shape the behavioural intention to adopt AI-enabled digital service platforms. The study also suggests a mediated relationship between transformational leadership and attitude, facilitated by the perceived ease of use and usefulness. Furthermore, the research highlights the mediating role of attitude in the relationship between perceived service quality and the intention to use these platforms. The study contributes by extending TAM and TPB through the integration of transformational leadership and service quality, and by contextualising AI-enabled platform adoption within an emerging market B2B industrial setting and provides actionable guidance for practitioners and decision-makers.