Uppsats

Understanding UX in Digital Transformation : A Service Design Approach in Traditional Manufacturing

Master-uppsats

KTH/Skolan för elektroteknik och datavetenskap (EECS)

Publicerad: 2025

Språk: Engelska

Sammanfattning

As traditional manufacturing firms adopt digital systems to modernize operations, misalignments often arise between how these systems are designed and how work actually happens on the shop floor. This thesis examines how such service-related factors shape user experience (UX) and influence the adoption of digital technologies among operators, engineers, and managers in a mid-sized furniture factory in China. Using a qualitative single-case study grounded in service design principles and Reflexive Thematic Analysis (RTA), the research draws on interviews, field observations, and co-creation workshops to explore how users navigate, adapt to, and engage with digital tools in their daily routines. The study identifies four interconnected service challenges: misaligned work-flows, insufficient feedback mechanisms, cognitive overload, and misunderstandings across roles. These issues reveal that digital adoption is not just a matter of usability or training, but also depends on emotional experience, trust, and organizational communication. By treating internal systems as employee-facing services, the thesis expands the application of service design to industrial UX, highlighting the situated and socially embedded nature of digital transformation. On a practical level, the findings offer actionable insights—such as embedding feedback and error recovery into interfaces, aligning digital processes with real production tasks, and establishing regular cross-role dialogue. Ultimately, the study suggests that sustainable digital transformation requires more than technological capability: it calls for a rethinking of how people, systems, and organizations evolve together through shared understanding and participatory design.

Information

Författare
Guo, Ziang
Lärosäte / institution
KTH/Skolan för elektroteknik och datavetenskap (EECS)
Publiceringsdatum
2025
Uppsatstyp
Master-uppsats
Språk
Engelska

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