Minerva Unbound: Knowledge Stocks, Knowledge Flows and New Knowledge Production

By Lynne G. Zucker, Michael R. Darby, Jonathan Furner, Robert C. Liu, Hong-Chih Ma. 2007

242 citations recorded by the source corpus.

Subfields: Accounting, Economics and Econometrics, Management of Technology and Innovation

View Paper: https://www.semanticscholar.org/paper/6d014bf13fe80b80e1f39ee8c07c93fd544ab8fd

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Citations in the corpus

Crystallography Open Database (COD): an open-access collection of crystal structures and platform for world-wide collaboration (2011, background): “Such technical possibilities open new ways for the development of science, where more eyes and more brains thinking on a subject as a rule have more success than a single person in isolation, and, when working together, create more new knowledge to everyones advantage; growth of scientific knowledge”
The Role of Technological Change in Green Growth (2012, unknown): “11 Examples of the former include Adams, Clemmons, and Stephan ( 2004, 2006), Adams and Clemmons (2008), Jones et al. (2008), Wuchty et al. (2007), and Zucker et al. (2007).”
How Much Does Immigration Boost Innovation? (2009, unknown): “Levin 2001). William R. Kerr (2008) documents the surge in the share of US patents awarded to US-based inventors with Chinese and Indian names to 12 percent of the total by 2004, and Wadhwa et al.”
The emergence of new technology-based industries: the case of fuel cells and its technological relatedness to regional knowledge bases (2016, methodology): “…statistics are a at D T U L ibrary on June 10, 2016 http://joeg.oxfordjournals.org/ D ow nloaded from widely used approach in quantitative studies to assess levels of competences for different units of analysis (see e.g. Patel and Pavitt (1997) for large firms and Zucker et al. (2007) for regions).”
A Network-based view of regional growth (2014, background): “…the role of inter-organisational networks as facilitators of knowledge flow has increasingly come to prominence across the economics, geography and management fields (Zucker et al., 2007; Tappeiner et al., 2008; Maggioni and Uberti, 2009; Bergenholtz and Waldstrøm, 2011; Colombo et al., 2011).”
Connecting local entrepreneurial ecosystems to global innovation networks: open innovation, double networks and knowledge integration (2011, background): “Nanotechnology is making similar demands, stretching engineering toward biology (Avenel et al., 2007; Zucker et al., 2007).”
Entrepreneurship, innovation and regional growth: a network theory (2015, background): “…of regional economic growth are increasingly considered to be based on the role that the production, distribution and use of knowledge play within and across regional economies (Grossman and Helpman 1994; Harris 2001; Ibert 2007; Zucker et al. 2007; Vaz and Nijkamp 2009; Antonelli et al. 2011).”
Regional Branching Reconsidered: Emergence of the Fuel Cell Industry in European Regions (2014, background): “Several different emerging industries have received attention in economic geography (see, e.g., Feldman and Lendel 2010; Feldman 2003; Dahl, Østergaard, and Dalum 2010; Zucker, Darby, and Brewer 1998; Zucker et al. 2007), but they have primarily been studied through the lens of clusters (Braunerhjel”
The innovative performance of firms in heterogeneous environments: the interplay between external knowledge and internal absorptive capacities (2018, background): “…signals the attractiveness of each local labor market in terms of knowledgeable inflows, following existing contributions that adapt the knowledge production framework to extended input specifications (e.g. Zucker et al., 2007; Ramani et al., 2008; Czarnitzki et al., 2009; Crescenzi et al., 2015).”
Impact of public and private research funding on scientific production: The case of nanotechnology (2012, background): “Zucker et al. (2007) insist on the necessity of collaboration between institutions to foster information exchange.”
Movement of Star Scientists and Engineers and High-Tech Firm Entry (2006, unknown): “…and an iterative probabilistic method which scores words and phrases according to their relative frequency of appearance in a learning set of expert-identified nano-articles and articles and patents generally (Ma, Furner, Zucker, and Darby 2006; Zucker, Darby, Ma, Furner, and Liu 2007).”