Innovation efficiency and spatial spillover in urban agglomerations: A case of the Beijing‐Tianjin‐Hebei, the Yangtze River Delta, and the Pearl River Delta

Abstract

Based on panel data of innovation inputs and outputs in 53 cities of the three major Chinese urban agglomerations (UAs) spanning the 2001–2015 period, this study examines the influence of the spatial spillover effect among cities on innovation efficiency in UAs using the SFA method and a spatial econometric model. Three main conclusions can be draw from the empirical results. First, the innovation efficiency in the three UAs has increased over the research period, but there is enormous potential for improvement. Second, owing to the close socioeconomic linkages and the flow of innovation resources, there is a significantly positive spatial spillover effect between cities on innovation efficiency in the three UAs. In other words, innovation efficiency in a local city was positively influenced by the other cities in the UA. Particularly, the innovation efficiency in a local city is influenced by factors related to not only the city itself but also other cities in the UA. Third, as the geographical distance increases, the spillover effect on innovation efficiency shows nonlinear variations, indicating that the excessive expansion in UAs may not be attributed to innovation development.

Implications of China's innovation policy shift: Does “indigenous” mean closed?

“…However, there are further effects of spatial proximity on innovation besides co-location of collaboration partners. That is, spatial externalities and knowledge spillovers from neighboring regions are found to be crucial for regional innovation outcomes in China (Sheng, Zhao, Zhang, Song, & Miao, 2019;Wang, Cheng, Ye, & Wei, 2016). These effects might also play a role for the pursued innovation processes in our sample.…”

Urban Innovation Efficiency Improvement in the Guangdong–Hong Kong–Macao Greater Bay Area from the Perspective of Innovation Chains

“…For the research on the innovation efficiency of urban agglomerations, Zhao (2018) adopted the DEA method to study the innovation efficiency of cities in the GBA and compared the scale efficiency and technical efficiency [28]. Sheng et al (2019) used the SFA method and spatial econometric model to study innovation efficiency and spatial spillover effect of urban agglomerations in Beijing-Tianjin-Hebei, the Yangtze River Delta and the Pearl River Delta in China [29]. Ye and Xu et al (2021) conducted a comparative study on the innovation efficiency and influencing factors of the three major urban agglomerations in eastern China through the construction of an input-output index system [30,31].…”

Regional impact and spillover effect of public infrastructure investment: An empirical study in the Yangtze River Delta, China

“…Scholars have analyzed the spatial spillover effects of transportation infrastructure from the perspective of industrial agglomeration. They believe that transportation infrastructure can reduce transportation costs and improve transaction efficiency (Sheng, Zhao, Zhang, Song, & Miao, 2019). Nonetheless, Holtz‐Eakin and Schwart (1994) argued that a spatial spillover effect has no evidence.…”