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| Research on Comprehensive Measurement and Influencing Factors of Collaborative Innovation Efficiency of China's Four Urban Clusters |
| Sun Zhenqing,Li Huanhuan,Liu Baoliu |
| (School of Economics and Management, Tianjin University of Science and Technology,Tianjin 300222,China) |
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Abstract As the central strategic area of the country's economic growth and an important part of the new urbanization, the coastal urban agglomerations in eastern China have important practical significance for achieving high-quality economic development. Based on the 2005-2017 prefecture-level city data, taking the Beijing-Tianjin-Hebei, Shandong Peninsula, Yangtze River Delta and Pearl River Delta urban agglomerations as the research objects, the three-stage DEA method is used to measure the efficiency of collaborative innovation of the four urban agglomerations and analyze their temporal and spatial characteristics, using Tobit The regression model analyzes the main factors that affect the efficiency of collaborative innovation in different urban agglomerations, and the results show that:①excluding the influence of external environment and random factors, the average comprehensive efficiency of the other three urban agglomerations is higher than that of the first stage Decrease;②external environmental factors have a significant impact on the efficiency of collaborative innovation. Regional economic levels and government financial support are negatively related to the efficiency of collaborative innovation; R&D support, industrial structure, and opening to the outside world are positively related to the efficiency of collaborative innovation;③the efficiency of collaborative innovation is generally on the rise, but there is a spatial imbalance in the internal city hierarchy;④there are also differences in the main factors that affect the efficiency of collaborative innovation in different urban agglomerations. Based on the above results, it aims to put forward suggestions to promote the collaborative innovation development of different urban agglomerations.
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Received: 11 October 2020
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