Improving the coordination between technological innovation in high-tech industries and regional economic development is an important measure for all provinces (cities) to implement the innovation-driven development strategy. Based on the analysis of the mechanism of high-tech industrial technological innovation and regional economic development, this paper constructs the measurement index system of high-tech industrial technological innovation and regional economic development, and the chain network DEA model, entropy weight method, coupling coordination model, and exploratory spatial data analysis technology are comprehensively used to empirically analyze the technological innovation efficiency of high-tech industries, regional economic development level, and the coupling coordination relationship between them and the spatiotemporal evolution trend in 24 provinces (cities) of China from 2009 to 2018. The results show that (1) there are significant differences in the average level of technological innovation efficiency of high-tech industry in each stage, which is the most prominent in the technology research and development stage, followed by the industrialization stage, and finally in the technology transformation stage. (2) The degree of coupling and coordination between high-tech industrial technological innovation and regional economic development is increasing year by year, which is in the adaptation stage of high-tech industrial technological innovation and regional economic development. (3) From the perspective of spatial pattern, there is a positive spatial autocorrelation between the coupling coordination degree of high-tech industrial technological innovation and regional economic development. The number of provinces (cities) with low coupling coordination degree is much larger than that with high coupling coordination degree, showing a serious imbalance of regional heterogeneity and forming two spatial aggregation areas of “high-high” diffusion effect and “low-low” low-speed growth.
Supply-demand matching is critical for the increase of response speed, the improvement of resource utilization, and the building of long-term partnership. This study will contribute to the present supply-demand matching studies by (1) summarizing the dynamic broker dominant supply-demand matching problem (B-SDMP), (2) proposing the dynamic broker dominant supply-demand matching approach, inclusive of (a) the building of the distributed constraint satisfaction model based on the dynamic negotiation among agents and (b) the design of an asynchronous backtracking algorithm according to interaction among agents, and (3) the design and development of a multiagent dynamic supply-demand matching system. To verify the validity and usability of the method, the system test and case simulation are conducted. The matching solutions yielded from this B-SDMP analysis can help the buyers find the appropriate sellers on one commodity/service under dynamic environment and stimulate the building of long-term partnership among the sellers, buyers, and broker as a stable supply chain.
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