制造业创新生态系统数字化转型的动力机制研究——基于GT和S-D模型的混合研究方法  

Research on the Driving Mechanism of Digital Transformation in Manufacturing Innovation Ecosystem——Based on a Mixed Research Approach of GT and S-D Models

作　　者：邹宗峰[1] 孙希昀 ZOU Zong-feng;SUN Xi-yun(School of Management,Shanghai University,200444)

机构地区：[1]上海大学管理学院,200444

出　　处：《上海经济研究》2025年第1期67-80,共14页Shanghai Journal of Economics

基　　金：国家社会科学基金项目“数智创新生态系统价值共创的冲突机制及治理体系研究”(批准号:23BGL058)阶段性成果之一。

摘　　要：创新生态系统数字化转型是创新3.0时代制造业突破转型困境及构建数字竞争格局的重要途径,为探索制造业创新生态系统数字化转型的内在逻辑,综合运用线性与复杂性科学研究方法,通过扎根理论与多案例研究识别数字化转型过程的关键影响因素,构建系统动力学模型对主体交互子系统、资源获取子系统、知识创造子系统仿真分析,深入揭示创新生态系统特质影响数字化转型绩效的内在机制及动态规律,剖析创新生态系统数字化转型的传导过程与动力机制。研究发现:制造业创新生态系统数字化转型过程呈现S型曲线发展模式,种群异质性、种群制衡性通过主体交互子系统正向影响数字化转型绩效,大量正负反馈回路之间的复杂非线性作用呈现为系统层面的线性高秩序现象;资源互补性、资源获取能力通过资源获取子系统正向影响数字化转型绩效,复杂系统演化内部正负反馈机制抗争呈现边际效应递减的复杂现象;网络合作度、网络开放度通过知识创造子系统正向影响数字化转型绩效,在时间维度上呈现出复杂性,具有区间特征。根据研究结果,提出鼓励异质性种群价值共创,加强产学研合作及营造鼓励创新的生态环境等建议。Digital transformation within the innovation ecosystem is an important way for manufacturing industries to break through the transformation dilemma and build a digital competitive landscape in the innovation 3.O era.To investigate the underlying principles of digital transformation within the manufacturing innovation ecosystem,this paper synthesizes linear and complexity scientific research methodologies,employing grounded theory and multiple case studies to identify the key influencing factors in the digital transformation process.It develops a system dynamics model and conducts simulation analyses on the subsystems of agent interaction,resource acquisition,and knowledge creation to thoroughly elucidate the internal mechanisms and dynamic principles governing how the characteristics of the innovation ecosystem influence digital transformation performance.Additionally,it examines the transmission process and driving mechanisms of digital transformation within this ecosystem.The study reveals that the digital transformation process within the manufacturing innovation ecosystem adheres to an S-shaped curve model.Heterogeneity and balance within the population positively influence digital transformation performance through the agent interaction subsystem.The intricate nonlinear interactions among various positive and negative feedback loops manifest as a linear high-order phenomenon at the system level.Resource complementarity and resource acquisition capabilities positively influence digital transformation performance through the resource acquisition subsystem.The intricate evolutionary internal positive and negative feedback mechanisms interact,resulting in a complex phenomenon characterized by diminishing marginal effects.The degree of network cooperation and network openness positively influence digital transformation performance through the knowledge creation subsystem,exhibiting complexity over time with interval characteristics.Based on the research findings,this paper proposes suggestions such as encouraging

关 键 词：制造业数字化转型 创新生态系统 动力机制 扎根理论 仿真分析 

分 类 号：F293.1[经济管理—国民经济]