Data

Aseem Kaul and I have used NBER patent data to assess when firms invest in more potentially radical invention activity (Academy of Management Journal, 2018). Two measures based on our approach are publicly available below.

As the paper describes, the measure looks at the class-to-class citation pattern of patents to endogenously determine how rare a given citation is. If patents in Class A frequently cite patents in Class B, then a new A-to-B citation would be common and expected (i.e., not rare, radical, or exploratory). If, however, hardly anyone in Class A had cited a Class B patent in the last five years, then such a citation would signal an attempt at a more radical recombination. This is the core intuition behind the measure (class-year normalized), the details of which are described in the article.

• J. P. Eggers & Aseem Kaul, 2018. "Motivation and Ability? A Behavioral Perspective on the Pursuit of Radical Invention in Multi-Technology Incumbents." Academy of Management Journal, 61 (1): 67–93.

  • Link to AMJ page

  • Download the paper directly here

Below you can download the measure for all patents in the NBER patent dataset from 1981 to 2006. The file contains the USPTO patent number for the patent, and two new measures -- explore_max and explore_avg. The former looks at all citations the patent makes and takes the value of the MOST unlikely citation (the highest value of exploration). This is the measure used in the paper above for the main analysis. The second measure averages the exploration score for all citations made by the patent.

Download Eggers & Kaul measure here.

If you use the data, please cite the paper. And if you have any questions or concerns, feel free to reach out to us.