Evolution of talent policies in Guangdong-Hong Kong-Macao greater bay area: An LDA thematic model approach - Jinpeng Wen; Hongxing Han (PLoS ONE, 2025)
As construction of the Guangdong-Hong Kong-Macao Greater Bay Area advances, talent has become the core driving force for its development. This study quantitatively analyzes 94 talent policies from Guangdong, Hong Kong, and Macao, revealing the strategic focuses and thematic evolution of these policies across different stages from a time-series perspective. It also distills relevant experiences to propose optimization strategies and a development blueprint for talent policies in the region. By combining historical review and thematic modeling, this study categorizes talent policies from the three regions over the past five years (2019–2024) into three phases: initial phase, developmental phase, and deep plowing phase. Theme heat analysis and similarity analysis are then applied to clarify the strategic focus and evolutionary trajectory of each phase, while the implementation effects of the talent policies are evaluated based on four dimensions: talent inflow volume, talent satisfaction, economic impact, and social influence. The Latent Dirichlet Allocation (LDA) model uncovers seven strategic talent themes and their heat distribution across the three phases. The study reveals that “Hong Kong and Macao tax incentives” have consistently served as the cornerstone of talent policy throughout the development process, while also fostering the rapid emergence of related themes. Looking ahead, efforts will be dedicated to building a comprehensive talent ecosystem integrating education, science and technology, and social security, thereby positioning the Guangdong-Hong Kong-Macao Greater Bay Area as an international first-class bay area. Finally, this paper draws on the successful experiences of the Yangtze River Delta, Beijing-Tianjin-Hebei region, and other international bay areas to formulate targeted strategies for the development of the Guangdong-Hong Kong-Macao Greater Bay Area.