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 Below is a brief summary of the dissertation: 

In today’s rapidly evolving digital landscape, organizations often struggle to implement human-centric digital transformation effectively, even with major investments in advanced technologies. Many initiatives fail to resonate with users because they overlook how people seek, process, and use information—leading to a disconnect between technological advances and human informational preferences.

This thesis addresses that gap through three studies spanning key stages of digital transformation: digitization, digitalization, and digital innovation. First, it shows how tailoring consent strategies to customers’ information proactiveness, under GDPR, boosts compliance. Second, it reveals that addressing customers’ information-seeking needs during uncertain decision-making enhances the effectiveness of life-event targeting, underscoring the value of personalized engagement. Third, it demonstrates that aligning AI-infused AR technology with workers’ information processing capabilities improves productivity in industrial settings.

Collectively, these findings affirm that adapting digital transformation initiatives to human informational behaviors leads to better outcomes—whether measured by compliance, engagement, or productivity. By understanding and integrating how individuals seek, process, and use information, organizations can design digital solutions that resonate deeply with users, resulting in higher adoption rates and meaningful impact. This thesis concludes that technological progress alone is not enough; a harmonious union of tech with human information traits is essential for successful digital transformation. Future research can explore additional informational characteristics and contexts, ensuring organizations remain adaptable as human-information interactions evolve. By doing so, businesses can more effectively navigate the digital landscape, paving the way for a more inclusive, efficient, and responsive ecosystem.