The drivers of collaborative innovation of the comprehensive utilization technologies of coal fly ash in China: a network analysis

• Published in: Environmental science and pollution research international Vol. 29; no. 37; pp. 56291 - 56308
• Main Authors: Yu, Xiaokun, Cui, Yue, Chen, Yilin, Chang, I-Shin, Wu, Jing
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2022; Springer Nature B.V
• Subjects: Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Coal; Collaboration; Cooperation; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental Health; Environmental science; Fly ash; Innovations; Level indicators; Network analysis; Organizations; Patent applications; R&D; Regression analysis; Research & development; Research Article; Research facilities; Research institutions; Social networks; Social organization; Technological change; Utilization; Waste Water Technology; Water Management; Water Pollution Control; China; Coal fly ash; Network evolution; Social network analysis; Collaborative innovation network; Complex network theory
• ISSN: 0944-1344; 1614-7499
• DOI: 10.1007/s11356-022-19816-5

Coal consumption brings a lot of coal fly ash (CFA). It requires interdisciplinary efforts in research, policy, and practice to improve the utilization of CFA. Although there have been a lot of achievements in technological innovation, the utilization of CFA is still difficult to match its output. So, it is urgent to explore how to guide its effective innovation. This paper uses social network analysis to discuss the characteristics of the collaborative innovation network of CFA comprehensive utilization technology in China. Then, this paper uses regression analysis to explore the differences in innovation performance under different research and development (R&D) backgrounds. The results show that (1) based on the network-level indicators, the collaborative innovation scale has an obvious trend of expanding. Partnerships increased from 20 to 574. Meanwhile, the network shows obvious scale-free and “small-world” characteristics, indicating that innovation resources are concentrated in a few organizations. (2) Based on the node-level indicators, the major contributor has shifted from universities and research institutions to enterprises. Enterprises account for the highest proportion (73%) and have the highest centrality (8.3). The betweenness centrality of the universities is 265, and only 14% of the organizations are universities which means universities play an important role in connecting different organizations in the network, but their participation in the collaborative innovation is insufficient. (3) Based on the collaborative relationship-level indicators, the cooperation is lack of depth. Only a small number of organizations, especially enterprises, have stable partners, showing the characteristic of “low cooperation width and high cooperation depth,” which means fewer partners but more frequently collaborative innovation. (4) Based on the innovation performance, the innovation performance under the category of cooperative R&D, especially industry-academy cooperation, is better than that of independent R&D. But, industry-academy cooperation only occupied 43% of collaborative relationships in the network. Finally, this paper puts forward suggestions for governments from five aspects: decentralization, defining roles of enterprise and university, encouraging collaboration, changing the idea of the patent application, and promoting deeper cooperation.