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Connecting pre-existing digitalization and technology adoption speed with AI-driven business model transformation via
Domitilla Magni1,2, Sikandar Ali Qalati3, Hanan Eid Badwy4
1Department of Economics and Business Management Sciences, Catholic University of Sacre Heart, Milan, 20123, Italy. domitilla.magni@unicatt.it.
Abstract:
This study investigates how pre-existing digitalization and technology adoption speed shape AI-driven business model transformation, with particular attention to the mediating role of employee competencies. Grounded in the resource-based view and digital transformation theory, the study employs structural equation modeling on survey data collected from 421 employees across various industries operating in Egypt. The results reveal that pre-existing digitalization and technology adoption speed directly and indirectly influence AI-driven business model transformation. Moreover, employee competencies significantly influence AI-driven business model transformation and partially mediate the effects of pre-existing digitalization and technology adoption speed on this outcome. This work contributes to the literature on artificial intelligence and digital transformation by demonstrating that employee competencies constitute a pivotal organizational mechanism linking the technological environment to business model innovation. Further, the study offers empirical insights into an emerging economy where the interplay between human capital and technological advancement has not been adequately studied.
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