Abstract: The orderly operation of the science and technology (S&T) talent policy system constitutes a fundamental guarantee for the construction and governance of high-level talent hubs. However, the intrinsic interaction mechanisms among the constituent elements within this system remain inadequately explored and require further revelation. To address this gap, this study leverages panel data from the Mainland Chinese city cluster within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) spanning the period 2007–2021. Employing an integrated methodological approach that combines dynamic fuzzy-set Qualitative Comparative Analysis (fsQCA) and BERTopic machine learning, the research investigates the synergistic effects of key factors—namely innovation motivation, innovation capability, innovation emotion, and institutional environment—on enhancing the level of orderly operation within the S&T talent system. This investigation is grounded in an "individual-organizational" interaction perspective and systematically explores these dynamics across both temporal and spatial dimensions. The analysis yields several significant findings. Firstly, the orderly operation of the S&T talent policy system manifests through multiple pathways underpinned by complex mechanisms. Five distinct configurations were identified: a "motivation"-dominated synergy-driven type; an "emotion"-dominated regulation-driven type; a "motivation-emotion"-dominated synergy-driven type; a "motivation-capability"-dominated synergy-regulation-driven type; and a multi-factor synergy regulation-driven type. Crucially, within these five pathways, none of the individual or organizational factors alone constitutes a necessary condition for achieving a high degree of system orderliness. Instead, the research reveals the existence of equifinality—equivalent substitutability—between specific condition combinations. Notably, substitutable relationships exist between "motivation-driven" mechanisms and "regulatory intensity," between "emotion-driven" mechanisms and "interdepartmental coordination," and between the combination of "capability cultivation + interdepartmental coordination + regulatory intensity" and "emotion-driven" mechanisms. Among these, motivation-driven mechanisms consistently emerge as a core condition across multiple pathways, playing a pivotal role in achieving high system orderliness.Secondly, weak innovation motivation coupled with low regulatory intensity is identified as a primary constraint negatively impacting the orderly operation of the S&T talent policy system. Thirdly, the development trajectory of this system within the GBA's Mainland city cluster exhibits significant time effects, with 2013 and 2017 serving as critical inflection points. Heterogeneous pathways observed prior to these nodes consistently converged towards states characterized by high consistency and stability thereafter. Fourthly, distinct regions demonstrate differentiated realization pathways for achieving system orderliness, highlighting the significant influence of specific contextual conditions on the effective configuration of factors. From a theoretical perspective, this research offers novel contributions. By adopting the "individual-organizational" interaction lens, it focuses on micro-level elements influencing S&T talents—specifically individual innovation motivation, capability, and emotion—thereby revealing the synergistic mechanisms operating between conditions at the individual and organizational levels. Furthermore, grounded in the theory of policy attention allocation, the study clarifies the equifinal relationships among key elements, systematically delineating both the core conditions and the substitutable pathways essential for realizing the orderly operation of the S&T talent policy system.From a pactical perspective, the findings provide actionable insights for policymakers. Decision-makers should prioritize "motivation-driven" mechanisms while also flexibly utilizing the identified equivalent substitutability relationships to optimize the allocation of policy attention. Crucially, capability cultivation is not a universally applicable key mechanism, its effectiveness is contingent upon regional economic, social, and cultural environmental factors. During policy design and implementation, policymakers must simultaneously address individual talent needs and organizational synergy mechanisms to ensure the policy system operates sustainably and efficiently.Consequently, the conclusions provide robust theoretical support and concrete policy recommendations aimed at enhancing the operational effectiveness and governance of S&T talent policy systems.