Digital technology adoption in European manufacturing: pathways to innovation and sustainability through AI and big data

ENG- This thesis investigates the adoption of digital technologies, specifically artificial intelligence (AI) and big data, within European manufacturing firms, highlighting the interplay between innovation, technological integration, and sustainability. In an era characterized by rapid technological advancement, firms are compelled to integrate digital solutions to remain competitive while addressing evolving sustainability demands. However, the process is often hindered by multiple factors, making it crucial to understand the complexities that drive or obstruct digital technology adoption Drawing on empirical data from a large-scale international survey, the study identifies key enablers—such as R&D cooperation, digital infrastructure, and sustainability practices—and barriers, including resource constraints and perceived usefulness, ecosystem and data management that influence digital technology adoption. The research offers a nuanced understanding of these adoption dynamics, emphasizing that technology adoption is not merely a technical endeavour but deeply influenced by organizational capacities, strategic alignment, and environmental challenges. In addition, the findings suggest that sustainability practices play a pivotal role not only in driving innovation but also in fostering AI and big data integration, creating a reciprocal relationship where digital technologies enhance sustainability performance while sustainability accelerates technological adoption. This dual role of sustainability expands the understanding of its influence on firms’ dynamic capabilities, pushing beyond its traditionally understood impact on environmental goals. By extending multiple theoretical frameworks and offering practical insights, this research contributes to the growing discourse on digital transformation in manufacturing. It not only emphasizes the necessity of integrating sustainability into digital strategies but also advocates for a forward-thinking, cumulative approach to AI and big data adoption. The findings are particularly relevant for manufacturing firms navigating the challenges of digitalization while striving to meet sustainability objectives