Information Technology and the Distribution of Inventive Activity

Chris  Forman; Avi  Goldfarb; Shane  Greenstein

Chapter | The Changing Frontier: Rethinking Science and Innovation Policy | 2015

Information Technology and the Distribution of Inventive Activity

by Chris Forman, Avi Goldfarb and Shane Greenstein

Abstract

We examine the relationship between the diffusion of advanced Internet technology and the geographic concentration of invention, as measured by patents. First, we show that patenting became more concentrated from the early 1990s to the early 2000s and, similarly, that counties that were leaders in patenting in the early 1990s produced relatively more patents by the early 2000s. Second, we compare the extent of invention in counties that were leaders in Internet adoption to those that were not. We see little difference in the growth rate of patenting between leaders and laggards in Internet adoption, on average. However, we find that the rate of patent growth was faster among counties who were not leaders in patenting in the early 1990s but were leaders in Internet adoption by 2000, suggesting that the Internet helped stem the trend towards more geographic concentration. We show that these results are largely driven by patents filed by distant collaborators rather than non-collaborative patents or patents by non-distant collaborators, suggesting low cost long-distance digital communication as a potential mechanism.

Keywords: Patents; Geographic Location; Internet; Innovation and Invention;

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Forman, Chris, Avi Goldfarb, and Shane Greenstein. "Information Technology and the Distribution of Inventive Activity." In The Changing Frontier: Rethinking Science and Innovation Policy, edited by Adam Jaffe and Benjamin Jones, 169–196. University of Chicago Press, 2015.

An Israeli startup founded in 2014, Zebra Medical Vision developed algorithms that produced diagnoses from X-rays, mammograms, and CT-scans. The algorithms used deep learning and digitized radiology scans to create software that could assist doctors in making diagnoses. By July 2018, Zebra had developed seven algorithms to analyze scans for emphysema, liver density, compression fractures, bone density, brain bleeds, breast cancer, and a calcium score used to detect calcified plaque in coronary arteries. For each scan analyzed, Zebra charged hospitals $1. By 2018 Zebra found itself in a race with its competitors to perfect these algorithms, create software tools, distribute the tools to physician partners, and create a market. Zebra already had several partners in the U.S. and Europe who gave feedback on its development. Management had to answer the following questions: What should they do next at Zebra? Should they work on the accuracy of the already developed algorithms or continue to develop many new tools? If they chose to develop new products, which applications should they address? And how should they go to market?

Case | HBS Case Collection | November 2019

DeepMap: Charting the Road Ahead For Autonomous Vehicles

Shane Greenstein and Nicole Tempest Keller

Founded in 2016, DeepMap developed high definition (HD) mapping software and localization services for Level 4+ autonomous vehicles. Traditional navigational maps were accurate to a few meters, which was sufficient for drivers, but not for machine-driven vehicles which required centimeter level accuracy. Autonomous vehicles required a new form of map that was highly precise, produced a 3D representation of the surrounding area, enabled vehicles to locate themselves within the map, provided information for how to navigate safely using the correct rules of the road, and was updated continuously as road conditions changed. DeepMap was not selling a static mapping database, but rather licensing its software under a software-as-a-service model. As a startup with limited resources navigating a nascent market, DeepMap faced uncertainty across several dimensions: the timing of overall AV market adoption, which countries would adopt fastest, which AV segments would move most rapidly, which sensor technologies would become standard, and what impact regulation would have. They also faced the challenge of serving customers on a global scale. As DeepMap looked ahead, it had to decide how and where to focus and allocate its funding in order to achieve its short and long-term objectives.

Keywords: mapping software; autonomous vehicles; Business Startups; Software; Technological Innovation; Technology Adoption; Service Delivery; Global Range; Resource Allocation; Strategic Planning; Technology Industry; Auto Industry;

Citation:

Greenstein, Shane, and Nicole Tempest Keller. "DeepMap: Charting the Road Ahead For Autonomous Vehicles." Harvard Business School Case 620-047, November 2019. View Details

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In several markets, firms compete not for consumer expenditure but consumer attention. We examine user priorities over the allocation of their time, and interpret that behavior in light of salient tensions in policy discussions over universal service, data caps, and related policy topics, such as merger analysis. Specifically, we use extensive microdata on user online choice to characterize the demand for the services offered online, which drives a household’s supply of attention. Our data cover a period of time that saw the introduction of many new and notable sites and new devices on which to access them. In our analysis, we assess “how” households supply their attention along various dimensions, such as their concentration of attention across the universe of sites and the amount of attention expenditure per domain visit. Remarkably, we find no change in “how” households allocated their attention despite drastically changing where they allocated it. Moreover, conditional on total attention expenditure, demographics entirely fail to predict our key measures of attention allocation decisions. We highlight several important implications, for policy and beyond, stemming from the persistence and demographic orthogonality of our novel attention measures.

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Information Technology and the Distribution of Inventive Activity

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