# How do policy tool combinations drive the construction of public health technology R&D alliances?

## TL;DR

This study explores how different policy tools influence the formation of public health technology R&D alliances, finding that demand-side measures like government procurement are most effective.

## Contribution

The study introduces a tripartite evolutionary game model to analyze the impact of policy tool combinations on alliance formation in public health R&D.

## Key findings

- Demand-side government procurement has the strongest incentive effect on enterprise and institutional participation.
- Excessive policy intervention can paradoxically reduce participation due to diminishing marginal returns.
- Optimizing policy tool mix and targeted incentives is essential for efficient public health R&D alliances.

## Abstract

To effectively respond to public health emergencies, establishing an efficient technology R&D alliance is critically important. This study develops a tripartite evolutionary game model involving the government, pharmaceutical enterprises, and academic and research institutions to examine how a combination of supply-side, demand-side, and environmental-side policy tools drives the formation of such alliances. The findings reveal that demand-side government procurement exerts the strongest incentive effect on enterprise and institutional participation, outperforming supply-side and environmental-side measures. Furthermore, policy intensity exhibits a scientifically discernible threshold: excessive intervention may not only increase fiscal pressure on the government but also paradoxically reduce willingness to participate due to diminishing marginal returns. Consequently, optimizing the mix of policy tools and implementing differentiated, targeted incentives are essential for fostering high-efficiency public health technology R&D alliances. This study offers a dynamic analytical framework and evidence-based guidance for policymakers in designing effective collaborative innovation strategies.