Automation in Swedish Universities and Colleges: Qualitative research on benefits and challenges in automation usage
2024 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE credits
Student thesis
Abstract [en]
This research explores the utilization of automation technologies within Swedish universities and colleges. The primary goal was to understand the potential benefits and challenges associated with automation usage in higher education institutions. The research was conducted using qualitative methods, with written interviews via electronic mail with IT participants from 12 institutions. The results highlight a diverse range of automation platforms in use, such as Microsoft Power Platform, BluePrism, and custom-developed solutions. These platforms support various automation types, such as Robotic Process Automation (RPA) and Intelligent Automation (IA), and are applied in areas such as student administration and IT services. The operational enhancements also identified improvement in workflow, efficiency, cost savings, and enhanced data quality, showcasing the benefits on automation usage. Despite these benefits, the study also uncovered several challenges that are faced. These include resistance to change, technical complexities, resource constraints, and the need for skill development. The Technology Acceptance Model (TAM) and Task-Technology Fit (TTF) frameworks were used to analyze the results, revealing that perceived ease of use and usefulness to influence the adoption of automation technologies. Furthermore, aligning these technologies with specific institutional tasks is critical for their successful implementation. The study’s outcome provides valuable insights into the current state of automation usage in Swedish higher education institutions. It draws the importance of strategic planning, investment in staff training, and continuous evaluation of automation strategies to address challenges and maximize the benefits of automation. Future research could expand on these results by involving more institutions and exploring additional methods for data collection and analysis.
Place, publisher, year, edition, pages
2024. , p. 50
Keywords [en]
Automation Platforms, Operational Enhancements, Higher Education, TAM & TTF Frameworks
National Category
Information Systems, Social aspects
Identifiers
URN: urn:nbn:se:miun:diva-52616OAI: oai:DiVA.org:miun-52616DiVA, id: diva2:1901264
Subject / course
Computer Science IF1
Supervisors
Examiners
2024-09-262024-09-262024-09-27Bibliographically approved