Third places as catalysts for technological innovation? Evidence from a grid cell level analysis of Nanjing, China*

The Impact of Land-Use Mix on Technological Innovation: Evidence from a Grid-Cell-Level Analysis of Shanghai, China

“…Although the benefits of land-use mix have been widely discussed from different perspectives, relatively little attention has been paid to empirically investigating the impacts of land-use mix on innovation capacity, especially at the intra-urban level. However, there are some notable exceptions that have examined the determinants of the intra-urban geography of technological innovation based on grid cell analyses, though these studies have not emphasized the role of land-use mix [19,20]. Here, we argue that land-use mix could influence technological innovation in at least three ways.…”

“…Specifically, the first group, which represents the impact of agglomeration on technological innovation, includes two independent variables. The variable Popu_den controls for the impact of population density on technological innovation, which has been widely considered in existing studies [1,6,20]. One might argue that the density of talented people could be a better choice; however, detailed data on talented people are unavailable at the grid cell level.…”

“…The other control variable Research_den is the number of research facilities that each grid contains. These research facilities generally include labs and engineering technology centers at the provincial level or above, which is one of the common variables that have been controlled for in the literature [9][10][11]20]. Based on the empirical findings of existing studies, both variables are expected to be positively associated with technological innovation.…”

“…These facilities usually function as third places which could provide shared spaces for people to communicate and exchange ideas. Moreover, the role of third places in facilitating the technological innovation process has been demonstrated in some recent studies [20]. Therefore, we choose to include this set of control variables.…”

“…Based on empirical evidence from China's Pearl River Delta, Wu et al showed that built environment factors, including a healthy environment, mixed land use, commuting convenience, and the technology atmosphere, all demonstrate significant impacts on regional innovation productivity [19]. In a recent case study on Nanjing, Li et innovation capacity is associated with the quantity and diversity of third places such as restaurants, parks, and coffee shops [20].…”