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| Circling-layering Economy of Urban Agglomeration, Co-innovation and Industrial Upgrading |
| Chen Congbo1,Ye Azhong2,Lin Zhuang2 |
| (1. School of Business Administration Anhui University of Finance and Economics, Bengbu 233030, China;2. School of Economics and Management, Fuzhou University, Fuzhou 350108, China) |
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Abstract China urgently needs to achieve economic transformation through innovation-driven industrial upgrading to stand out in global competition and lead a new round of industrial reform. China's industrial upgrading involves the largest population and the most comprehensive industrial structure, but the industrial upgrading presents a significant spatial imbalance. The industrial structure of peripheral cities is weak, and the collaborative ability of innovation subjects within cities is insufficient. With the construction of high-speed railway infrastructure, spatial knowledge spillover has become a catalyst for industrial upgrading. The imbalance of industrial upgrading between peripheral cities and central cities can be remedied by spatial knowledge spillover. Therefore, it is necessary to study the spatial spillover effect of co-innovation on industrial upgrading under the circle structure.#br#Academics generally believe that innovation is the driving force for industrial upgrading on the premise that the technological progress direction selected by independent innovation and learning activities is consistent with the regional conditions, and the regional industrial upgrading and economic development can be effectively promoted. Meanwhile when technological progress is inconsistent with regional conditions, the increase in the number of innovative achievements can not match the effect of industrial upgrading. In terms of spatial spillovers driving industrial upgrading in neighboring regions, existing studies mainly focus on the impact of industrial transfer and spatial knowledge spillovers on industrial upgrading. As for the spatial impact of industrial transfer, domestic scholars use the “flying-geese model" to explain the industrial transfer and upgrading from developed regions to less developed regions. Some scholars also hold a critical attitude towards the "flying-geese model", for there are still some improvements. First, it has failed to deeply analyze the differences between the spatial spillover effects of co-innovation of heterogeneous cities on industrial upgrading. For the central cities with the status of “leader goose" and a large number of peripheral cities, the urban heterogeneity of the spatial effects of co-innovation on industrial upgrading remains to be found; second, the dynamic impact of co-innovation space spillover on industrial upgrading is not considered; third, the empirical method mostly adopts a linear spatial model. If the linear assumption of spatial dependency is relaxed, the model setting should be more realistic to obtain more accurate estimation results. Therefore, this paper studies the spatial-temporal effect and urban heterogeneity of industrial upgrading of co-innovation between central cities and peripheral cities in the urban agglomeration circling structure, and then explores why industrial upgrading of central cities is in a dominant position in the circling structure. In terms of demonstration, the dynamic threshold spatial Dubin model is applied for the first time to test the spatial spillover of the co-innovation of the center and peripheral cities on industrial upgrading.#br#This paper constructs an asymmetric spatial weight matrix based on the Yangtze River Delta Economic Zone panel data from 2009 to 2019 to characterize the spatial relationships of circling-layering economy, and then builds a semi-parametric two-mechanism dynamic spatial Durbin model to investigate the spatial and temporal effects of co-innovation on industrial upgrading and its urban heterogeneity. The findings are as follows: (1) the Yangtze River Delta Economic Zone industrial upgrading has significant dynamic and spatial correlation, and the spatial and temporal effects of co-innovation of neighboring cities on industrial upgrading cannot be ignored; (2) cooperative patents of central and peripheral cities can promote the industrial upgrading of neighboring cities in short and long run while the government funding of co-innovation by central cities is disadvantageous to the industrial upgrading of peripheral cities in long run; (3) the current effect of co-innovation on industrial upgrading of local cities shows a marginal decreasing trend, and the reason for maintaining the advantage of industrial upgrading of central cities is more likely to come from the spatial spillover of co-innovation from neighboring cities to central cities, rather than the advantages of the central city's own co-innovation. The results are helpful to understand the spatial and temporal effects of co-innovation on industrial upgrading and to promote the integrated development of innovation between central and peripheral cities, and provide practical significance to realize the industrial upgrading of urban agglomerations as a whole.#br#
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Received: 20 October 2022
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