Against the backdrop of the "Talent-Strong Nation" strategy, regional competition for talent is intensifying. However, local science and technology talent policies commonly suffer from "fragmentation" and "policy silos," which sever the intrinsic links between the four key stages of talent work—"attraction, cultivation, retention, and utilization"—leading to low policy efficacy. This paper focuses on the systematicness and integration of talent policy, taking Qingyuan City as a typical analytical field. Using qualitative research methods, it deeply analyzes the internal logic and practical dilemmas of "full-chain synergy" in science and technology talent policy. The study posits that full-chain synergy is a necessary requirement driven by four logics: the value logic of responding to the "holistic" needs of talent throughout their life cycle; the functional logic of ensuring the "emergent" realization of the policy system's functions; the objective logic of reducing "dual" transaction costs for both talent and market entities; and the governance logic of advancing the "holistic governance" paradigm shift. However, the case analysis of Qingyuan City reveals four practical dilemmas: cognitive barriers of "prioritizing attraction over cultivation, retention, and utilization"; structural barriers of overlapping and fragmented functions; instrumental misalignment between the policy chain and the industrial chain; and operational blockages in information and evaluation mechanisms. To address this, the paper proposes implementation pathways to construct full-chain synergy from a mechanism design perspective: First, constructing a synergistic governance architecture centered on unified rights and responsibilities to achieve holistic top-level design. Second, reshaping a closed-loop operational system based on process re-engineering to achieve seamless process management. Third, anchoring a precise linkage objective guided by industrial demand to achieve a high fit between policy and needs. Fourth, establishing a long-term evaluation orientation supported by systematic assessment to achieve systemic incentive-constraint alignment. This research aims to provide theoretical reference and practical insights for local governments seeking to optimize their talent policy systems and build high-level talent ecosystems.
Li et al. (Wed,) studied this question.