Multi-actor influence in achieving sustainable complex innovation systems.Case studies in transportation, automotive and aging care industries
Time: Thu 2025-09-18 09.00
Location: T2 (Jacobssonsalen), Hälsovägen 11C, Huddinge
Video link: https://kth-se.zoom.us/j/65328718619
Language: English
Subject area: Technology and Health
Doctoral student: Qiuchen Wang , Hälsoinformatik och logistik
Opponent: Professor Mike Danilovic, Shanghai Dianji University, Kina och Högskolan i Halmstad
Supervisor: Professor Sebastiaan Meijer, Hälsoinformatik och logistik
QC 2025-08-29
Abstract
This thesis investigates the application of the Action, Factor and Goal (AFG) actor analysis method in complex technology innovation systems across three distinct domains: transportation, heavy automotive automation, and aging care. The research addresses the critical need to understand multi-actor influences in the early adoption stages of technological innovations. This challenge has become increasingly significant as innovation processes become more global and multifaceted. The study employs a mixed-method approach, combining qualitative data collection through interviews, observations, and document analysis with the structured AFG framework. This method comprehensively examines innovation adoption's technical, institutional, and social dimensions across the selected domains.
By leveraging AFG analysis, the study investigates multi-actor influences, uncovering how diverse behaviors, perspectives, and organizational priorities impact technological integration. In the transportation domain, AFG analysis reveals challenges in the electric road system (ERS) and mobility-as-a-service (MaaS) solutions. In the production domain, the study examines Human-Robot Collaboration (HRC) in heavy vehicle manufacturing, highlighting safety, ergonomics, and productivity considerations across regulatory and operational levels. In the aging care sector, AFG analysis addresses the adoption of Personal Emergency Response Systems (PERS) in an aging care home, capturing the interplay of caregiver practices, resident safety, and ethical concerns related to technology deployment.
Key findings reveal that the AFG method effectively captures multi-actor challenges by providing a structured analysis of system characteristics and actor concerns, visualizing stakeholder perceptions, and identifying potential conflicts and synergies.
The research contributes to innovation management and multi-actor analysis literature by demonstrating the AFG method’s adaptability and effectiveness in analyzing complex, multi-actor innovation systems. It also provides practical insights for project managers and policymakers on developing targeted communication plans, creating collaborative platforms, and tailoring adoption strategies to address specific actor needs and motivations.
Limitations of the AFG method implementation, including potential observer bias, qualitative nature, and static representation of dynamic systems, are acknowledged and addressed through proposed methodological refinements. Future research directions are suggested to enhance the method’s empirical validation and quantitative precision.
This thesis advances our understanding of multi-actor influences in technology innovation systems and offers a robust analytical tool for understanding the complexities of innovation adoption across diverse industrial sectors.