摘要
如何准确测量企业创新是国家创新驱动发展战略背景下学界和业界亟待解决的关键问题。近年来,专利和研发支出作为当前主流企业创新代理指标备受质疑。为此,基于上市公司分析师报告文本,引入机器学习领域非监督学习方法,通过构建隐含狄利克雷分配主题模型,开发一种新的测量企业创新的方法,并与当前主流方法进行比较。研究发现:①基于文本的企业创新测量方法既适用于专利和研发企业,也适用于非专利和非研发企业;②对于专利和研发企业而言,基于文本的企业创新与企业专利申请和研发支出显著相关;对于非专利和非研发企业而言,新测量方法能够有效识别企业利用新技术、开辟新市场等创新实践;③时间序列分析表明,基于文本分析的企业创新能够准确反映样本区间企业创新活动宏观趋势。
The Chinese government firmly adheres to the path of independent innovation with Chinese characteristics and implement an innovation-driven development strategy.As the main body of innovation,enterprises play a pivotal role in promoting national innovation and transformation,therefore the research on corporate innovation has received extensive attention from the academic community.Scholars have carried out a variety of theoretical and empirical studies around corporate innovation and have obtained some remarkable achievements.However,the important issue of how to accurately measure corporate innovation waits to be addressed.This problem is challenging for both the academic circles and the industrial field especially under the background of the national innovation-driven development strategy in China.The current mainstream proxy indicators of corporate innovation,such as numbers of patents and research and development(R&D)expenditures,have recently been criticized since they can only reflect some aspects of corporate innovation,while ignoring other vital parts of corporate innovation activities.Wherefore this paper tries to develop a new method to comprehensively and accurately measure corporate innovation based on text analysis using the natural language processing technique and machine learning algorithms.This research introduces the unsupervised learning method in the field of machine learning and develops a new method of measuring corporate innovation by constructing the Latent Dirichlet Allocation(LDA)topic model based on the text of analyst reports of listed companies.The textual content of analyst reports covers both the objective description and professional evaluation on various aspects of corporate innovation,such as product innovation,process innovation,market innovation,supply source innovation and so on.Besides,it has similar characteristics in terms of text structure and wording,which lays a good foundation for the use of LDA topic modeling method.To start with,Python3.8 is applied to write a program
作者
叶琴
蔡建峰
张秋韵
Ye Qin;Cai Jianfeng;Zhang Qiuyun(School of Management,Northwestern Polytechnical University;School of Computer Science,Northwestern Polytechnical University,Xi'an 710129,China)
出处
《科技进步与对策》
北大核心
2024年第2期90-98,共9页
Science & Technology Progress and Policy
基金
国家社会科学基金重大项目(18ZDA103)
国家社会科学基金一般项目(21BGL012)。
