PurposeThe mega railway infrastructure projects are faced with complex environments and multi-level management challenges. Thus, the mega railway infrastructure project management system not only needs to focus on its composition, but also needs to consider changes and impacts of internal and external environment.Design/methodology/approachThis study attempts to introduce the concept of dissipative structure from the perspective of complexity theory and constructs a positive entropy and negentropy flow index system for mega railway infrastructure project management system in order to analyze the factors of management system more deeply. The Brusselator model is used to construct the structure of the mega railway infrastructure project management system, and the entropy method is used to calculate the positive entropy and negentropy values to verify whether the management system is a dissipative structure.FindingsA plateau railway project in China was used as an example for an empirical study, not only its own characteristics are analyzed, but also the role of constraints and facilitation of the internal and external environment. Based on the research results, several effective suggestions are put forward to improve the stability and work efficiency of mega railway infrastructure project management system.Originality/valueThis study demonstrates that mega railway infrastructure project management system has the characteristics of dissipative structure. It can provide theoretical support for the development of mega railway infrastructure project management system from disorderly state to orderly state.
Innovation is the main driving force to promote national technological progress. It is of great significance to explore the optimal path to improve innovation efficiency by using the qualitative method and neural network prediction model to promote the high-quality development of the national economy. This study focuses on high-tech industries in the eastern, central and western regions of China; a factor-dependent research framework for innovation efficiency improvement in high-tech industries is constructed in China. The fuzzy-set qualitative comparative analysis method (QCA) is used to explore multiple paths to enhance the innovation efficiency of China’s high-tech industries. Then, a GA-PSO-BP neural network is used to construct an optimization model for the enhancement path of technological innovation efficiency, which clarifies the optimal path for the enhancement of innovation efficiency of high-tech industries in the eastern, central and western regions of China. Finally, innovation management strategies for high-tech industries are presented with regional features. The study finds that none of the individual conditions are necessary to promote the innovation efficiency of China’s high-tech industries, and only the linkage effect of the factors can achieve the goal of improving the innovation efficiency level of China’s high-tech industries. There are four configuration paths to improve the innovation efficiency of China’s high-tech industries, which are: “Multinational company (MNC) innovation—economic development—government support”; “MNC innovation—government support”; “economic development—government support”; and “economic development”. The characteristics of regional heterogeneity make differences in the optimal paths of innovation efficiency improvement in high-tech industries in eastern, central and western regions of China.
Technological innovation of multinational corporations (MNC) is an important engine to drive the world’s scientific and technological progress, which plays an important role in the sustainable development of global innovation. With China’s high-tech industry from 2009 to 2020 as the research sample, this study empirically analyzes the impact of MNCs’ two-stage innovation on the innovation efficiency of China’s high-tech industry through the perspective of base regression, threshold effect, and regional heterogeneity. It was found that MNC research and development (R&D) efficiency and achievement transformation efficiency have a positive impact on the innovation efficiency of high-tech industries in China, with nonlinear features and regional heterogeneity. This study provides an empirical basis for the efficient use of MNC’s innovative resources and the sustainable development of China’s high-tech industry.
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