Work

Improving innovation implementation capabilities through implementation science and takt production principles in the infrastructure sector

Year: 2026
Type: article
Abstract: Purpose The infrastructure sector has long suffered from challenges in bringing innovations into practice. This study aims to investigate how adapting implementation science and takt production principles could improve the innovation implementation capabilities of organizations in the sector. Design/methodology/approach This research belongs to the field of innovation implementation. A design science research (DSR) approach is adapted for constructing, testing, validating and refining a novel model integrating implementation science and takt production. Within DSR, the theory-based initial model was introduced in a sector-wide workshop and tested, validated and refined through a case study in four Finnish public sector infrastructure organizations. Findings The results indicate that the innovation implementation capabilities of the infrastructure sector organizations have room for improvement and would indeed benefit from the adoption of implementation science and takt production principles. The participants felt that utilizing the constructed model (the TAIMI model) was both beneficial and challenging. Consequently, successful innovation implementation appears to be significantly dependent on organizational and implementation project-specific implementation capabilities. In addition to the implementation model, adapting these new approaches requires improving organizational capabilities and organized coaching. Originality/value Previous research focuses largely on theoretical or instructive settings, whereas this study adds to the understanding of how genuine and effective progress and improved implementation capabilities can be achieved. Together with a conceptual TAIMI model, the gained insights guide on how the tested principles can be utilized in improving infrastructure sector’s productivity.
Language: English
Open Access status: hybrid
OpenAlex ID: W7225800916
FWCI:
Cites: 43
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