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论文编号：	15548
作者编号：	1120211180
上传时间：	2025/12/5 14:48:08
中文题目：	创新绩效反馈持续性对企业研发投资的影响研究
英文题目：	Persistent Innovation Performance Feedback and Its Impact on Corporate R&D Investment
指导老师：	程新生
中文关键字：	创新绩效反馈持续性；研发投资强度；研发投资策略；管理者风险承担意愿
英文关键字：	Persistence of Innovation Performance Feedback; R&D Investment Intensity; R&D Investment Strategy；Managerial Risk-Taking Propensity
中文摘要：	在知识经济和数字经济深度融合的宏观背景下，创新已成为国家实现高质量发展和企业构筑可持续竞争优势的关键路径。作为国家创新体系的主力军，高科技企业一方面承担着产业升级与技术突破的使命，另一方面也面临创新活动长期性、高不确定性和高风险等多重挑战，研发投资决策由此成为学界与实践界关注的核心问题。绩效反馈通常指企业在特定时期将实际绩效与抱负水平进行比较后形成的评价结果，其中绩效反馈顺差和绩效反馈落差分别对应实际绩效高于或低于抱负水平的正向与负向偏离。本文在此基础上将分析视角聚焦于创新领域，并将创新绩效期望顺差和创新绩效期望落差界定为企业创新产出水平相对于创新抱负水平的正向和负向偏离，并以其在连续期间内的持续存在和累积程度刻画创新绩效反馈持续性。既有研究多围绕单一时期绩效反馈与研发投入强度之间的关系展开，普遍忽视创新绩效反馈在时间维度上的持续性特征，也缺乏对企业在研发投资方向与模式等策略维度上差异化选择的系统分析。为弥补上述不足，本文立足企业行为理论，整合绩效反馈理论、前景理论与注意力基础观，探讨创新绩效反馈持续性对企业研发投资强度与策略选择的影响机制及其情境差异。 紧扣上述现实情境和研究缺口，本文围绕三个核心问题展开研究：第一，创新绩效期望顺差持续性如何影响企业研发投资强度，管理层风险承担意愿与创新关注在其中发挥的中介作用；第二，创新绩效期望落差持续性是否会对企业研发投入产生非线性影响，企业在不同持续阶段如何在“问题驱动型搜索”和“威胁—刚性反应”之间转换；第三，在不同创新绩效反馈持续性情形下，企业在研发投资方向（路径维持）与模式（合作研发）上采取何种策略组合，不同策略选择又将如何反过来影响后续创新绩效，从而构建“创新绩效反馈—研发投资策略—创新绩效结果”的动态循环机制。 本文以2007—2023年中国A股高科技企业为研究样本，构建创新绩效期望顺差与落差及其持续性指标，考察其对研发投资强度和研发投资策略选择的影响，并引入财务绩效反馈和行业技术迭代速度作为关键情境变量，以反映企业内部资源约束和外部技术环境特征，同时结合产权性质和行业竞争程度开展多维度比较分析，以揭示创新绩效反馈持续性影响企业研发决策的内在机制与边界条件。研究表明：第一，在创新绩效期望顺差持续的情境下，持续超越创新期望水平显著促进企业增加研发投入，管理层风险承担意愿和创新关注在其中起到重要中介作用，且财务绩效顺差和高技术迭代环境进一步强化这一激励效应。第二，在创新绩效期望落差持续的情境下，企业研发投入呈现倒 U 型变化：短期至中期的创新绩效期望落差激发问题驱动型搜索，促进研发投入增加；但当落差持续时间过长时，“威胁—刚性”效应显现，管理层转向风险规避和资源收缩，研发投入随之下降，财务资源相对充裕和技术迭代较快的企业能够在一定程度上延缓这一收缩过程。第三，从研发投资策略看，创新绩效期望顺差持续性使企业倾向于采取“高路径维持、低合作研发”的稳健型策略，通过巩固技术积累和既有优势延续创新领先地位；而创新绩效期望落差持续性则促使企业转向“低路径维持、高合作研发”的开放型策略，以期通过外部协同与资源共享实现创新绩效的修复与逆转。 在理论贡献方面，本文将“持续性”这一时间维度系统引入绩效反馈分析框架，揭示创新绩效期望顺差与落差持续性对企业研发投资行为的动态影响机制，拓展了绩效反馈理论在长期创新情境下的解释边界；将绩效反馈持续性研究从财务绩效领域扩展至创新绩效领域，识别出创新绩效在生成逻辑与作用路径上的独特性；基于注意力基础观与高阶梯队理论，揭示管理层风险承担意愿与创新关注在顺差持续性影响研发投资中的关键中介作用，并构建包含财务绩效反馈和行业技术迭代速度的内外部情境分析框架；进一步突破以往对研发投资“量”的单一关注，将研发投资策略纳入分析，构建“创新绩效反馈—研发策略选择—创新绩效结果”的动态循环逻辑。 在实践贡献方面，本研究结论为企业和政策制定者提供了有针对性的管理启示与决策依据。对于企业而言，揭示了创新绩效顺差与落差持续性对研发投资强度及研发方向与合作模式等策略选择的影响，有助于管理层在不同创新绩效状态下合理解读绩效反馈，平衡短期压力与长期创新投入，匹配研发资源与策略组合。对于政策制定者而言，研究识别了财务绩效与行业技术迭代速度等关键情境因素，为构建以绩效持续性为导向的差异化创新支持与风险补偿政策提供依据，有助于提升产业创新体系的韧性与资源配置效率。
英文摘要：	In the era of the knowledge and digital economy, innovation has become both a core national strategy for achieving high-quality development and a fundamental pathway for enterprises to build sustainable competitive advantages. As the main driving force within the national innovation system, high-tech enterprises not only shoulder the mission of industrial upgrading, but also face multiple challenges arising from the inherently long-term, uncertain and high-risk nature of innovation activities. R&D investment thus plays a crucial role in sustaining firms’ innovative capacity and has attracted growing attention from both academia and industry. Yet most existing studies focus on the impact of single-period performance feedback on R&D investment intensity, while largely overlooking the temporal persistence of innovation performance feedback and firms’ differentiated strategic choices regarding the direction and mode of R&D investment. In practice, enterprises may experience sustained periods of innovation performance surplus or deficit which, through managerial risk perception and attention allocation mechanisms, shape R&D investment behaviour and are further conditioned by internal and external contextual factors. To address these gaps, this study draws on the behavioural theory of the firm and integrates performance feedback theory, prospect theory and the attention-based view to systematically examine how the persistence of innovation performance feedback affects firms’ R&D investment intensity and strategic choices, and how these relationships vary across different organisational and environmental contexts. Focusing on this core issue, the study addresses three main research questions. First, it investigates how the persistence of innovation performance surpluses influences R&D investment intensity, with managerial risk-taking propensity and innovation attention acting as mediating mechanisms under the upper echelons framework. Second, it examines the non-linear impact of the persistence of innovation performance deficits on R&D investment intensity, highlighting how firms’ responses evolve from problem-driven search to threat–rigidity as deficit persistence increases. Third, it analyses how firms adjust their R&D investment direction and mode under different persistence scenarios of innovation performance, and further evaluates how alternative R&D strategies feed back into innovation outcomes, thereby constructing a dynamic cycle of innovation performance feedback – R&D strategy choice – innovation performance outcomes. Using data on Chinese A-share listed high-tech firms from 2007 to 2023, the study explores how the persistence of innovation performance surpluses and deficits affects firms’ R&D investment intensity, strategic orientation and subsequent innovation outcomes. Financial performance feedback and the rate of industry technological iteration are introduced as key moderating variables, capturing internal resource conditions and external environmental dynamics. Together with ownership structure and industry competition intensity, these variables underpin a series of multidimensional empirical tests and comparative analyses that reveal the mechanisms and boundary conditions through which innovation performance persistence shapes R&D decision-making. The main empirical findings are as follows. First, when innovation performance surpluses persist, firms that consistently exceed their innovation aspirations significantly increase R&D investment. Persistent surpluses enhance managerial risk-taking propensity and innovation attention, thereby raising the priority of innovation in resource allocation. This positive incentive effect is further strengthened under favourable financial performance and faster technological iteration. Second, when innovation performance deficits persist, firms’ R&D investment exhibits an inverted U-shaped pattern. Short- to medium-term deficits stimulate problem-driven search and spur higher R&D expenditure, whereas prolonged deficits trigger a threat–rigidity response, leading managers to become more risk-averse and to scale back resource commitment to innovation. Firms with more abundant financial resources and operating in industries with rapid technological renewal are better able to delay or mitigate this contraction. Third, from an R&D strategy perspective, persistent innovation performance surpluses encourage firms to adopt relatively stable configurations characterised by high path maintenance and limited collaboration, consolidating technological accumulation and competitive advantages in order to sustain innovation leadership. By contrast, persistent innovation performance deficits prompt firms to pursue more open configurations characterised by lower path maintenance and greater collaboration, leveraging external partnerships and shared resources to restore and reverse innovation underperformance. From a theoretical perspective, this study makes several contributions. First, it explicitly introduces the temporal dimension of persistence into the performance feedback framework, revealing the dynamic mechanisms through which persistent innovation performance surpluses and deficits influence R&D investment, thereby extending performance feedback theory beyond static, single-period “magnitude effects” and enhancing its explanatory power for long-term innovation behaviour. Second, it shifts the context of performance feedback persistence research from financial performance to innovation performance, identifying the distinctive generative logic and impact pathways of innovation outcomes and offering a new lens for understanding non-financial performance feedback. Third, drawing on the attention-based view and upper echelons theory, it identifies the mediating roles of managerial risk-taking propensity and innovation attention in the relationship between innovation performance persistence and R&D investment, and develops a dual-context analytical framework incorporating financial performance feedback and technological iteration speed, thereby enriching our understanding of the complex mechanisms of performance feedback. Finally, by moving beyond a sole focus on the quantity of R&D investment to incorporate the strategic dimensions of investment direction and mode, the study develops a dynamic framework of innovation performance feedback – R&D strategy – innovation performance outcomes, providing a systematic theoretical account of how high-tech firms build and sustain innovation advantages through structural R&D decisions. From a practical perspective, the findings offer targeted implications for both enterprises and policymakers. For firms, the study clarifies how persistent innovation performance surpluses and deficits systematically shape R&D investment intensity and strategic choices, helping management to interpret performance feedback more effectively, balance short-term pressures with long-term innovation commitments and allocate innovation resources more rationally. Firms in a persistent surplus state should maintain strategic focus and continuously strengthen core capabilities, while those in a persistent deficit state should preserve R&D resilience and adjust their R&D direction and collaboration mode to achieve innovation catch-up. For policymakers, the identification of the moderating roles of financial performance and technological iteration speed provides empirical support for designing differentiated and targeted innovation policies. These insights contribute to the refinement of incentive mechanisms and risk-compensation schemes oriented towards performance persistence, thereby enhancing the efficiency and resilience of the national innovation system.
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