Evolution of the Chinese Industry-University-Research Collaborative Innovation System

Hindawi Complexity Volume 2017, Article ID 4215805, 13 pages https://doi.org/10.1155/2017/4215805 Research Article Evolution of the Chinese Industry-University-Research Collaborative Innovation System Jianyu Zhao1,2 and Guangdong Wu3 1 School of Economics and Management, Harbin Engineering University, Heilongjiang, Harbin 150001, China School of Management, Harbin Institute of Technology, Heilongjiang, Harbin 150001, China 3 School of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang 330013, China 2 Correspondence should be addressed to Jianyu Zhao; Received 28 November 2016; Revised 19 March 2017; Accepted 29 March 2017; Published 9 April 2017 Academic Editor: Katarzyna Musial Copyright © 2017 Jianyu Zhao and Guangdong Wu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The goal of this study was to reveal the mechanism of the Chinese industry-university-research collaborative innovation (IURCI) and interactions between the elements in the system and find issues that exist in the collaborative innovation process. Based on the theoretical perspective of innovation and complexity science, we summarized the elements of the IURCI as innovation capability, research and development (R&D) configuration, and knowledge transfer and established a theoretical model to describe the evolution of the IURCI system. We used simulation technology to determine the interactions among variables and the evolution trend of the system. The results showed that the R&D configuration can promote the evolution of innovation capability and knowledge transfer and that innovation capacity is the current dominant factor in the evolution of the Chinese IURCI system and is highly positively correlated with R&D configuration. The evolutionary trend of knowledge transfer was gentler, and its contribution to the evolution of the Chinese IURCI system was less than that of R&D configuration. When innovation, R&D configuration, and knowledge transfer are relatively balanced, the collaborative innovation system can achieve high speed and stable evolution. 1. Introduction Innovation is an important stimulator of economic development and is also a key element in the global competitiveness of the country. As the world’s second largest economy, China has made great progress along the road of independent innovation, research, and development investment, and the number of academic achievements and patents has been ranked at the top in the world. But in spite of this progress, there is a disconnection between the economy and technology in the process of innovation in China. On the one hand, the Global Competitiveness Report developed by the World Economic Forum according to the Global Competitiveness Index (GCI) showed that China’s technological readiness for innovation (ranked at #88) has seriously hampered the country’s competitiveness ranking, indicating that the innovation capability of core technology in Chinese enterprises is still relatively backward, failing to form an innovation-driven development model, and many industry’s core technologies with significantly shorter cycles of innovation are still heavily dependent on foreign countries. On the other hand, the conversion rate of technological achievements has been low for a long time in Chinese universities and research institutions; therefore, higher education training is lagging behind (ranked #62). Universities and research institutions cannot effectively meet the knowledge requirements for innovation, which is also an important factor that has led to delays in the Chinese innovation system. The Organization for Economic Co-operation and Development’s China Innovation Policy Research Report pointed out that coordination and integration in China’s innovation system is not perfect, and the synergy between constituent subjects in the system is low. Compared with developed countries, Chinese enterprises not only lack the R&D capabilities of core technology, but also the effects of knowledge accumulation are relatively poor. Enterprises tend to be more cost-oriented and lack the motivation to carry out and use public research achievements. Meanwhile, enterprises, universities, and research 2 institutes rarely share innovation resources, most types of technology transfer are carried out under the guidance of government, and universities and research institutions do not take the initiative to understand the technology needs of industry. These problems have seriously hampered knowledge spillover in the Chinese innovation system and have become an obstacle that China must overcome to build an innovation-driven country through independent innovation. An effective measure to solve the above problem is to establish a practical and effective Chinese cooperative research innovation system, thus contributing to the rapid transformation of public scientific and technological achievements of Chinese enterprises and universities as well as research institutions, and to promote scientific research in Chinese universities and institutes that feeds the demand for industrial innovation, thus allowing technological development and industrial development to move forward together. Research on the evolution of the Chinese industry-university-research (IUR) collaborative innovation (IURCI) system can help identify the interactions between the elements of Chinese IURCI systems and, through identifying problems in the process of collaborative innovation, can help Chinese enterprises and universities as well as research institutions emerge from the knowledge dilemma of collaborative innovation. This study therefore has theoretical and practical value for enhancing collaborative innovation efficiency and promoting IURCI development in China. In contrast to the past static perspective, we established an evolutionary logistics/dynamics equation to describe the research collaborative innovation system in China, using relevant methods from game theory to solve it. On this basis, we collected indices and data that have influenced Chinese IURCI from 2005 to 2014, simulated the evolution morphology of related variables by MATLAB software, analyzed the interactions between elements and dynamic evolution, and demonstrated in detail the evolution mechanism of the research innovation system in China. In this study, while revealing the essence of Chinese IURCI, we have tried to establish a new research framework and explain 2 issues: first, there are different degrees of interaction among variables in the Chinese IURCI system, with different levels of contribution to the evolution of a collaborative innovation system and, second, when the default initial value of evolution changes, an evolutionary trend develops among the variables. In Section 2 of this paper, we describe our analysis of (...truncated)