Looking for Mr. Schumpeter: Where Are We in the Competition--Innovation Debate?

By Richard J. Gilbert. Innovation Policy and the Economy, 2006

486 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/737eeffedfed8591c3d984b43309096f0747fb36

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Citations in the corpus

What Do We Learn from Schumpeterian Growth Theory (2013, unknown): “29See the recent analytical surveys by Gilbert (2006), Vives (2008), and Schmutzler (2010).”
Does AMD Spur Intel to Innovate More? (2011, background): “Despite the absence of conclusive theoretical or empirical evidence, the Federal Trade Commission (FTC) increasingly cites the potential negative effect of competition on innovation as a concern (Gilbert 2006).”
Declining Competition and Investment in the U.S. (2017, unknown): “The theoretical point is straightforward, but as Richard Gilbert states, “differences in market structure, the characteristics of innovations, and the dynamics of discovery lead to seemingly endless variations in the theoretical relationship between competition and [innovation]”. The point we wish t”
Overlapping Ownership, R&D Spillovers, and Antitrust Policy (2019, unknown): “The extant literature (see Gilbert 2006), most of which focuses on the potential bene(cid:133)ts 11 Shelegia and Spiegel (2012) study a Bertrand competition model.”
Inverted-U relationship between R&D intensity and survival : evidence on scale and complementarity effects in UK data. (2016, unknown): “As indicated by Gilbert (2006), a given level of market concentration induces different levels of innovation inputs or outputs − depending on the initial level of concentration.”
A Dynamic Network Measure of Technological Change (2017, result): “Much like research on social networks, this literature has produced conflicting theoretical arguments and empirical findings (Gilbert 2006, Ahuja et al. 2008).”
1 Moving Beyond Schumpeter: Management Research on the Determinants of Technological Innovation (2008, background): “Although methodological problems, such as non-random samples, poor controls, endogeneity problems, and quality of data, are partly responsible for this lack of consensus, part of the confusion is due to lack of conceptual clarity (Cohen & Levin, 1989; Gilbert, 2006).”