Measuring the Direction of Innovation: Frontier Tools in Unassisted Machine Learning

44 Pages Posted: 4 Jun 2020 Last revised: 2 Aug 2021

See all articles by Florenta Teodoridis

Florenta Teodoridis

University of Southern California - Marshall School of Business

Jino Lu

University of Southern California - Marshall School of Business

Jeffrey L. Furman

Boston University - Department of Strategy & Policy; National Bureau of Economic Research (NBER)

Date Written: August 1, 2021

Abstract

As strategy research has increasingly recognized the roles of innovation and knowledge as drivers of firm- and industry-level outcomes, greater attention has been given to the effort to identify relationships among ideas and the distances between knowledge bases. In this paper, we develop a methodology that infers the mapping of the knowledge landscape based on researchers’ text documents. The approach is based on an unassisted machine learning technique, Hierarchical Dirichlet Process (HDP), which flexibly identifies patterns in text corpora. The resulting mapping of the knowledge landscape enables calculations of distance and movement, measures that are valuable in several contexts for research in strategy and innovation. We benchmark demonstrate the benefits of our approach in the context of 44 years of USPTO data.

Keywords: Innovation, topic modeling, machine learning, knowledge landscape, distance in knowledge space, movement in knowledge space, diversity, knowledge trajectories, rate and direction of innovation

JEL Classification: O30, O31, O33, O39

Suggested Citation

Teodoridis, Florenta and Lu, Jino and Furman, Jeffrey L., Measuring the Direction of Innovation: Frontier Tools in Unassisted Machine Learning (August 1, 2021). Available at SSRN: https://ssrn.com/abstract=3596233 or http://dx.doi.org/10.2139/ssrn.3596233

Florenta Teodoridis (Contact Author)

University of Southern California - Marshall School of Business ( email )

701 Exposition Blvd
Los Angeles, CA California 90089
United States

Jino Lu

University of Southern California - Marshall School of Business ( email )

701 Exposition Blvd, HOH 431
Los Angeles, CA California 90089-1424
United States

Jeffrey L. Furman

Boston University - Department of Strategy & Policy ( email )

595 Commonwealth Avenue
Boston, MA 02215
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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