Patent Value and Citations: Creative Destruction or Strategic Disruption?

By David S. Abrams, Ufuk Akcigit, Jillian Grennan. 2013

121 citations recorded by the source corpus.

Subfields: Information Systems and Management, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/6fdeb0427c9df4af760a6461ed4c5e9b039917fa

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems and Management

1. Philippe Aghion

In Statistics and Probability

1. Ufuk Akcigit
2. Philippe Aghion
3. Richard Blundell
4. Jeffrey M. Wooldridge
5. Xiaohong Chen
6. Jochen Kluve
7. Christoph Rothe
8. Whitney K. Newey

Citations in the corpus

• Patent citation data in social science research: Overview and best practices (2017, unknown): “Recent work by Abrams, Akcigit, and Popadak (2013) also suggest an overall positive correlation between forward citations and patent value, but with an inverted-U-shaped relationship in which value falls at high citation rates.”
• Measuring Technological Innovation over the Long Run (2018, unknown): “By contrast, Abrams, Akcigit, and Popadak (2013) use a proprietary dataset that includes estimates of patent values based on licensing fees and show that the relation between private values and patent citations is non-monotonic.”
• Innovation and Top Income Inequality (2018, background): “As argued in Abrams et al. (2013), such variables are useful if there are nonlinearities between the value of a patent and the number of forward citations.”