Abstract: Taking the science and technology talent policies of 9+2 cities in Guangdong-Hong Kong-Macao Great Bay Area from 2001 to 2020 as research object, this paper describes the characteristics and evolution patterns of the synergy among policy departments, objectives and tools through descriptive statistics and quantitative analysis of policy texts, and then constructs a production function model and applies ridge regression analysis to study the mechanism of how the synergy between policy objective and policy tool influences regional innovation performance. Based on the research, some findings are as follows. Firstly, with the promotion of the strategy on developing a quality workforce, the number of science and technology talent policies issued in Guangdong-Hong Kong-Macao Great Bay Area has increased overall, but there are regional differences. Secondly, policy objectives are not structurally balanced, as reflected in great importance attached to talent quality and efficiency but little attention paid to the flow and scale of talents; the use of policy tools is also unbalanced, with environmental policy tools used insufficiently. Thirdly, the cooperation among policy publishing departments strengthens, resulting in enhanced synergy of policy objectives and a trend towards comprehensive utilization of various policy tools. Fourthly, the impact of different policy objectives and tools on regional innovation performance has significant directional differences, and not all synergies are conducive to improving regional innovation performance. The research conclusions are meaningful for promoting the effective allocation of scientific and technological talent resources in the Guangdong-Hong Kong-Macao Greater Bay Area, for the government to formulate precise talent policies, and for promoting regional coordinated development and international competitiveness.

Key words: policy synergy, regional innovation performance, science and technology talent policy, Guangdong-Hong Kong-Macao Greater Bay Area