数智赋能如何驱动区域医药制造业创新？——一个基于TOEP框架的研究

How Does Digital Intelligence Empowerment Drive Innovation in Regional Pharmaceutical Manufacturing?—A Study Based on the TOEP Framework

摘要: 医药制造业作为实现“制造强国”与“健康中国”战略的关键领域，其创新绩效提升亟需数智赋能驱动。然而，现有研究对数智赋能区域医药制造业的组态路径与多重因果机制缺乏深入探讨。本文基于技术–组织–环境–进程(TOEP)整合框架，采用模糊集定性比较分析(fsQCA)方法，以我国31个省级区域为案例，实证检验数智赋能区域医药制造业创新绩效的多元驱动机制。研究发现：(1) 区域医药制造业高创新绩效存在“技术–进程”双元驱动、“技术–组织–进程”三元协同、“技术–组织–环境–进程”四元并进三类组态路径，技术与进程是构成高创新绩效路径的普遍基础，但其效能最大化依赖于与组织、环境要素的系统协同；(2) 数智赋能路径呈现显著的区域异质性，领先地区依托全要素协同构建创新生态，其他地区则可通过强化技术与进程等核心组合，并辅以组织规模或环境基建等差异化条件实现高绩效，体现了基于禀赋的战略选择；(3) 高水平创新绩效的实现存在“殊途同归”的演化路径，各地区可通过要素强化与组合优化，实现从低阶路径向高阶协同路径的动态跃迁。研究结论从组态视角揭示了数智赋能区域医药制造业创新的复杂机理与多元路径，为实施差异化、精准化的区域产业政策提供了理论依据与实践启示。

Abstract: As a pivotal sector for realizing the “Manufacturing Power” and “Healthy China” strategies, pharmaceutical manufacturing urgently requires digital-intelligence enablement to enhance innovation performance. However, existing research lacks in-depth exploration of the configurational pathways and multiple causal mechanisms through which digital-intelligence enablement drives regional pharmaceutical manufacturing innovation. Grounded in the integrated Technology-Organization-Environment-Process (TOEP) framework, this study employs fuzzy-set Qualitative Comparative Analysis (fsQCA) and examines 31 provincial-level regions in China to empirically test the multiple driving mechanisms of digital-intelligence enablement for regional pharmaceutical manufacturing innovation performance. The findings reveal that: (1) High innovation performance in regional pharmaceutical manufacturing manifests through three configurational pathways: “Technology-Process” dual-driven, “Technology-Organization-Process” triadic synergy, and “Technology-Organization-Environment-Process” quadruple parallel advancement. Technology and Process constitute common foundations for high-performance pathways, yet their effectiveness maximizes only through systematic synergy with Organization and Environment elements; (2) Digital-intelligence enablement pathways exhibit significant regional heterogeneity—leading regions construct innovation ecosystems through comprehensive factor coordination, while other regions can achieve high performance by strengthening core combinations such as Technology-Process, supplemented by differentiated conditions like organizational scale or environmental infrastructure, reflecting strategic choices based on resource endowments; (3) The realization of high-level innovation performance demonstrates equifinality in evolutionary pathways, whereby various regions can achieve dynamic transitions from lower-order to higher-order synergistic pathways through element strengthening and combination optimization. These conclusions reveal the complex mechanisms and multiple pathways of digital-intelligence enabled innovation in regional pharmaceutical manufacturing from a configurational perspective, providing theoretical grounding and practical implications for implementing differentiated and precision-oriented regional industrial policies.