Technology intermediaries and regional innovation performance: an empirical study in China

Culture and regional innovation performance: an exploration in China

“…The use of patent data as innovation performance is criticized (Acs et al , 2002; Fritsch, 2002). Some scholars also suggest adding literature-based innovation counts (Acs et al , 2002) and the number of new products (Fritsch, 2002; Wu and Xu, 2013) to the innovation output to accurately assess RIP. However, due to the difficulty of accessing data related to literature-based innovation counts and new products in China, scholars still consider patents as the most reliable and consistent data for comparison in China (Li, 2006).…”

“…Among others, regional innovation system gains scholars’ special attention due to the relevance of the regional level (Cooke and Schienstock, 2000; Lau and Lo, 2015; Krugman, 1991) in the differences of their innovation activities and boundedness of knowledge flows among regions (Asheim and Gertler, 2006; Fritsch and Graf, 2011). Over time, scholars have studied regional innovation systems from different perspectives and foci, such as Belussi et al (2010) and Tödtling et al (2011b) on innovative firms; Bresnahan and Gambardella (2004), Cowan and Zinovyeva (2013) and Chen and Kenney (2006) on universities and research institutions; Buesa et al (2010), Fiore et al (2011) and Niosi (2000) on government; Inkinen and Suorsa (2010), Howells (2006) and Wu and Xu (2013) on intermediary agencies.…”

“…For instance, in the context of studying Chinese innovation, Li et al ’s (2014) regression analysis uses the granted patent count in the application year as RIP. Wu and Xu (2013) measure RIP in high-tech industries by using new product output and the number of patent applications and the number of patents granted.…”

“…As key factors influencing RIP, the following variables have been often considered and studied: science parks (Gkypali et al , 2016), regional policy (Landabaso, 1997), industrial structure and firm ownership (Li et al , 2014), absorptive capacity (Lau and Lo, 2015), regional R&D investment (Li, 2006), technology intermediaries (Wu and Xu, 2013), amongst others. Culture has seldom been studied as a determinant for RIP, but more employed to examine innovation output at the organizational level (Laforet, 2016; Zhang et al , 2015) and the national level (Prim et al , 2017; Rinne et al , 2012).…”

Can innovation really bring economic growth? The role of social filter in China

“…This implies that higher level of R&D endowment leads to higher level of output according to previous studies. Other factors such as government support and industry specific environment (e,g., Li,2009); Intermediary organization (e.g., Wu and Xu, 2013), and return migration (e.g., Sternberg and Müller, 2005) have also been found to be correlated with R&D efficiency in China.…”