作者姓名

张丽萍

年度

2023

刊物名称

ENTROPY

刊号

刊物期别

SCIE

刊物级别

作者顺序

1

被转载

文章摘要

Based on   authorized patents of China’s artificial   intelligence industry from 2013 to 2022, this paper constructs an Industry–University–Research institution (IUR) collaboration network and an Inter-Firm   (IF) collaboration network and used the entropy weight method to take both   the quantity and quality of patents into account to calculate the innovation   performance of firms. Through the hierarchical clustering algorithm and   classification and regression trees (CART) algorithm, in-depth analysis has   been conducted on the intricate non-linear influence mechanisms between   multiple variables and a firm’s innovation   performance. The findings indicate the following: (1) Based on the network   centrality (NC), structural hole (SH), collaboration breadth (CB), and   collaboration depth (CD) of both IUR and IF collaboration networks, two types   of focal firms are identified. (2) For different types of focal firms, the   combinations of network characteristics affecting their innovation   performance are various. (3) In the IUR collaboration network, focal firms   with a wide range of heterogeneous collaborative partners can obtain high   innovation performance. However, focal firms in the IF collaboration network   can achieve the same aim by maintaining deep collaboration with other focal   firms. This paper not only helps firms make scientific decisions for   development but also provides valuable suggestions for government   policymakers.