同行研发动态与企业最优研发区间的演化机制研究——基于“红皇后效应”理论

摘要/Abstract

摘要： 研发投资对创新发展和产业升级具有重要意义。本文基于行业研发竞争视角,通过构建包含研发障碍点和研发饱和点的动态优化模型,并运用时变门槛模型进行实证检验,探究了企业最优研发区间动态演化的内在机理。研究发现,企业存在依赖于同行研发水平动态变化的最优研发区间。随着行业研发水平提高,最优研发区间的下界(研发障碍点)显著上升,上界(研发饱和点)显著下降。机制分析表明,企业最优研发区间的动态演化过程受到"红皇后效应"的显著影响。风险后果分析发现,实现最优研发区间能够增强企业风险承担能力,降低财务困境风险。本文拓展了行业创新生态塑造企业研发决策的理论内涵,对引领企业实施创新驱动发展战略具有重要启示。

关键词: 最优研发区间, 动态演化, 行业研发竞争, 时变门槛, 企业绩效

Abstract: R&D investment is important for achieving innovative development and industrial upgrading. Based on the perspective of industry R&D competition, this paper explores the internal mechanism of dynamic evolution of the optimal interval for firms' R&D investment by constructing a dynamic optimization model including R&D barrier point and R&D saturation point, and using the time-varying threshold model for empirical tests. We find that firms have an optimal interval of R&D investment that depends on the R&D level of their peers. As the R&D level of the industry increases, the lower bound (R&D barrier point) of the optimal interval rises significantly, while the upper bound (R&D saturation point) decreases significantly. The mechanism analysis reveals that the dynamic evolution of firms' optimal R&D investment interval is influenced considerably by the "Red Queen effect." The risk consequence analysis further shows that achieving the optimal R&D interval enhances a firm's risk-bearing capacity and reduces the likelihood of financial distress. This paper expands the theoretical connotation of industry innovation ecology shaping enterprises' R&D decision-making, and has important implications for leading enterprises to implement an innovation-driven development strategy.

Key words: optimal interval for firms'R&D investment, dynamic evolution, industry R&D competition, time-varying threshold, firm performance

杨利雄, 姚良燕, 吴建祖. 同行研发动态与企业最优研发区间的演化机制研究——基于“红皇后效应”理论[J]. 管理评论, 2026, 38(5): 3-16.

Yang Lixiong, Yao Liangyan, Wu Jianzu. Research on the Evolutionary Mechanism of Peer R&D Dynamics and Firms' Optimal R&D Investment Interval: Based on the Red Queen Effect Theory[J]. Management Review, 2026, 38(5): 3-16.

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