数学的实践与认识2018,Vol.48Issue(1) :58-66.

元分析下高技术产业不同创新路径绩效研究

Performance Study on Innovation Paths of High-Tech Industry under the Perspective of Meta-Analysis——Based on the Comprehensive Analysis of five Panel Data Models

俞立平 宋夏云 王作功
数学的实践与认识2018,Vol.48Issue(1) :58-66.

元分析下高技术产业不同创新路径绩效研究

Performance Study on Innovation Paths of High-Tech Industry under the Perspective of Meta-Analysis——Based on the Comprehensive Analysis of five Panel Data Models

俞立平 1宋夏云 2王作功3
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作者信息

  • 1. 浙江工商大学管理工程与电子商务学院,浙江杭州310018;贵州财经大学金融学院,贵州贵阳550025
  • 2. 浙江财经大学科技学院,浙江杭州310018
  • 3. 贵州财经大学金融学院,贵州贵阳550025
  • 折叠

摘要

自主研发、引进技术、购买国内技术、更新改造几种创新路径对高技术产业具有十分重要的意义.由于不同计量模型各有优缺点,各模型的研究结论并不相同,而针对同一问题、同一数据根本就没有最佳模型,所以本文首先采用面板混合回归、面板数据模型、动态面板模型、面板联立方程模型、空间面板模型同时进行研究,然后采用元分析对5种研究结果加以整合,得到唯一结论.研究表明,自主研发绩效显著;更新改造是创新的必要补充,绩效良好;引进技术和购买国内技术总体绩效不高;元分析有利于提高研究的稳健性.

Abstract

Innovation paths, which including independent R&D, technological introduction, purchasing domestic technology and technical renovation and transformation, are of great significance on high-tech industry.Each econometric model has advantages and disadvantages,and the conclusions of models are not the same.There is no optimization model, so in this paper, firstly we use panel mixed regression, panel data model, dynamic panel model, panel simultaneous equation model and spatial panel model to do research respectively, then using a meta-analysis to integrate the five kinds of research results, finally arrive at an only conclusion.The results show that the performance of independent R&D is significant, technical renovation and transformation is the necessary supplement of innovation, whose performance is good.The global performance of technological introduction and purchasing domestic technology is not good.Meta-analysis is beneficial to improve the robustness of our research.

关键词

高技术产业/创新路径/绩效/元分析

Key words

high-tech industry/innovation path/performance/meta-analysis

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基金项目

教育部人文社会科学研究规划基金(17YJA630125)

浙江省哲学社科规划课题(17NDJC107YB)

浙江省软科学项目(2016C25018)

出版年

2018
数学的实践与认识
中国科学院数学与系统科学研究院

数学的实践与认识

CSTPCD北大核心
影响因子:0.349
ISSN:1000-0984
参考文献量2
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