This study aims to examine the configuration and dynamics of triple helix relations (academics, industry, government) in Indonesia, evaluate the institutional capabilities of universities in transforming research outputs into innovations with socio-economic value, and formulate a policy framework conducive to productive collaboration and innovation downstreaming. This study employed a mixed-methods approach with a sequential explanatory design. The target population consisted of three actor groups: academics from accredited public and private universities, industry practitioners from priority sectors, and government officials from relevant ministries/agencies. Quantitative data were collected through a questionnaire survey of 450 respondents consisting of academics, industry practitioners, and government officials selected using a purposive stratified sampling technique. Qualitative data were collected through in-depth interviews, focus group discussions (FGDs), and policy document analysis. Quantitative data analysis used descriptive and inferential statistics (Structural Equation Modeling/multiple regression), while qualitative data were analyzed using thematic analysis. The results showed that triple helix collaboration in Indonesia remains sporadic (72%) and is dominated by technical consulting (45%) and internships (40%), while joint research only reaches 18%. The institutional capacity of universities is still weak, with only 35% having a professionally managed Science and Technology Park and 73% acknowledging that Technology Transfer Office staff play more of an administrative than a strategic role. The matching fund program is known to 82% of academics, but the proposal success rate is only 22% due to administrative complexity and overlapping regulations between ministries. The integration of higher education into the national innovation system requires simultaneous interventions at three levels: strengthening institutional capacity at the micro level, establishing collaboration platforms with clear governance at the meso level, and harmonizing policies and regulations at the macro level. Future research is recommended to use longitudinal approaches and social network analysis to map the evolution of innovation networks more comprehensively.
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