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清华大学教育研究[ISSN:1001-4519/CN:11-1610/G4]

卷:

期数:

2026年02期

页码:

68-76

栏目:

世界一流大学

出版日期:

2026-04-20

文章信息/Info

Title:

Lagging Effects of Research Input and Output in China’s First-Class Universities

作者:

胡勇军 陈奕喆

上海交通大学 深远海大科学设施办公室

Author(s):

HU Yong-jun CHEN Yi-zhe

Deep-ocean Large-scale Scienti?c Facility Command Of?ce, Shanghai Jiao Tong University

关键词:

新质生产力; 一流大学; 研发投入产出; 滞后效应

Keywords:

new-quality productive forces;  ?rst-class universities;  R&D input-output;  time-lag mechanisms

分类号:

G644

DOI:

10.14138/j.1001-4519.2026.02.006808

文献标志码:

A

摘要:

本研究立足新质生产力视角考察一流大学研发投入和研发产出之间的作用机制，解读其滞后效应的内在机理，基于34所中国一流大学2001-2020年的研发投入和产出数据，采用面板自回归分布滞后模型分析其滞后效应，结果显示，当年的研发总体产出受前1年研发产出和前2年研发投入的显著影响。其中论文产出和技术转让收入受前1年产出和前2年投入的显著影响，专利授权数受前1年产出和前1年投入的显著影响。一流大学研发投入产出滞后机制的背后是知识生产过程的螺旋嵌套、科研生产的非线性路径、科研生产要素的多元产出形式等多重因素。启示高校瞄准垂直领域持续发力，破除科研投入产出因果思维，通过评价创新助推科研创新。

Abstract:

From the perspective of new-quality productive forces, this study examined the mechanism linking R&D inputs and outputs in world-class universities and the internal logic underlying their time-lag effect. Drawing on R&D input and output data from 34 Chinese world-class universities covering the period 2001-2020, it employs a panel autoregressive distributed lag (ARDL) model to analyze the time-lag effect.The results revealed that the total annual R&D output is signi?cantly driven by the R&D output of the previous year and the R&D input of two years prior. Speci?cally, paper publications and technology transfer income are signi?cantly affected by the output of t-1 and the input of t-2. At the same time, the number of patent grants is signi?cantly in?uenced by both the output and input of t-1. Beneath the time-lag mechanism of R&D inputoutput in world-class universities lie multiple factors, including the spirally nested nature of the knowledge production process, the nonlinear pathways of scienti?c research, and the diversi?ed output forms of scienti?c research. The findings offer implications for universities to focus on and sustain efforts in vertical fields,abandon linear causal thinking in R&D input-output models, and boost scienti?c and technological innovation through evaluation innovation.

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更新日期/Last Update: 2026-04-20