Research and Development of Data Science and AI Tools for Project Management at Trafikverket
dc.contributor.author | Weijmer, Franz Erik | |
dc.contributor.department | Chalmers tekniska högskola / Institutionen för industri- och materialvetenskap | sv |
dc.contributor.department | Chalmers University of Technology / Department of Industrial and Materials Science | en |
dc.contributor.examiner | Bergsjö, Dag Henrik | |
dc.contributor.supervisor | Persson Schön, Per | |
dc.date.accessioned | 2025-07-09T07:38:30Z | |
dc.date.issued | 2025 | |
dc.date.submitted | ||
dc.description.abstract | This master’s thesis explores the application of product development methodology to the design and prototyping of data science tools within the public sector. The work was conducted in collaboration with Trafikverket, Sweden’s national transport administration, to support more efficient project management in large infrastructure projects. The study investigates how AI and data-driven tools can be identified, evaluated, and developed at a public agency. The research follows a structured product development process comprising user needs analysis, opportunity identification and screening, concept development, prototyping, and deployment assessment. Initial insights were gathered through interviews, meetings, and a survey conducted with Trafikverket staff. The data of which was collected and assembled into a needs list. Several potential AI tool concepts were proposed and screened throughout these conversations. Four high-potential concepts were screened through a ranking and comparison to the needs list. One of these concepts, an AI-supported clustering tool for managing public consultation feedback (Samråd), was chosen for prototyping. Using Swedish-language text embeddings and the BERTopic framework, the tool was designed to automatically group and summarize incoming insights to reduce manual workload and increase response consistency. This opportunity also underwent a deployment assessment of economic, environmental, and social impacts. Based partly on the research knowledge from the project, but also based on a follow-up interview with a consultant at SWECO. This project demonstrates that utilizing a product development process was not only appropriate, but could also have been beneficiary as opposed to traditional data science processes for an organization with limited knowledge of their own needs for data science and AI tools and how to implement them. The outcomes serve as a road map and proof of concept for Trafikverket’s continued adoption of AI tools | |
dc.identifier.coursecode | IMSX30 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12380/310077 | |
dc.language.iso | eng | |
dc.setspec.uppsok | Technology | |
dc.subject | Product Development | |
dc.subject | Data Science | |
dc.subject | Artificial Intelligence | |
dc.subject | Public Sector Innovation | |
dc.subject | Project Management | |
dc.subject | Opportunity Identification | |
dc.title | Research and Development of Data Science and AI Tools for Project Management at Trafikverket | |
dc.type.degree | Examensarbete för masterexamen | sv |
dc.type.degree | Master's Thesis | en |
dc.type.uppsok | H | |
local.programme | Product development (MPPDE), MSc |
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