Philip Shapira

Part-Time Professor

Member Of:
  • School of Public Policy
  • Technology Policy and Assessment Center
Office Location:
DM Smith 314

Overview

Philip Shapira is a Professor in the School of Public Policy at Georgia Institute of Technology and Professor of Management, Innovation and Policy with the Manchester Institute of Innovation Research, Alliance Manchester Business School, University of Manchester. His interests encompass science and technology policy, economic and regional development, innovation management and policy, industrial competitiveness, technology trajectories and assessment, innovation measurement, and policy evaluation. Prof. Shapira's current and recent research includes projects that examine nanotechnology research and innovation systems assessment, responsible research and innovation in synthetic biology, and next generation manufacturing and institutions for technology diffusion. Prof. Shapira is a director of the Georgia Tech Program in Science, Technology and Innovation Policy and the Georgia Manufacturing Survey. He is co-editor (with J. Edler, P. Cunningham, and A. Gök) of the Handbook of Innovation Policy Impact (Edward Elgar 2016) and (with R. Smits and S. Kuhlmann) of Innovation Policy: Theory and Practice. An International Handbook (Edward Elgar, 2010). Prof. Shapira is a Fellow of the American Association for the Advancement of Science and a Fellow of the Royal Society of Arts.

For recent publications by Prof. Shapira, please visit: http://works.bepress.com/pshapira/ and Google Scholar.

Philip Shapira is on Twitter @pshapira

Education:
  • Ph.D., University of California, Berkeley, City and Regional Planning
  • M.A., University of California, Berkeley, Economics
  • M.C.P., Massachusetts Institute of Technology, City Planning
  • Dip.TP (Dist.), Gloucestershire College of Art and Design, U.K.

Interests

Research Fields:
  • Science, Technology, and Innovation Policy
Geographic
Focuses:
  • Asia (East)
  • Europe
  • United States
  • United States - Georgia
Issues:
  • Regional Development
  • Emerging Technologies - Innovation
  • Small and Midsize Enterprises
  • Technology Management and Policy

Recent Publications

Journal Articles

  • Mapping technological innovation dynamics in artificial intelligence domains: Evidence from a global patent analysis
    In: PLoS ONE [Peer Reviewed]
    Date: December 2021

    Artificial intelligence (AI) is emerging as a technology at the center of many political, economic, and societal debates. This paper formulates a new AI patent search strategy and applies this to provide a landscape analysis of AI innovation dynamics and technology evolution. The paper uses patent analyses, network analyses, and source path link count algorithms to examine AI spatial and temporal trends, cooperation features, cross-organization knowledge flow and technological routes. Results indicate a growing yet concentrated, non-collaborative and multi-path development and protection profile for AI patenting, with cross-organization knowledge flows based mainly on interorganizational knowledge citation links.

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  • Policy interactions with research trajectories: The case of cyber-physical convergence in manufacturing and industrials
    In: Technological Forecasting and Social Change [Peer Reviewed]
    Date: November 2021

    From the early 2010s, policymakers and firms in advanced industrial economies began introducing approaches to systemically exploit manufacturing and industrial data (the notion of cyber-physical convergence). Three innovation concepts were especially highlighted: Smart Manufacturing, Industrial Internet and Industrie 4.0. In parallel, academics have employed these concepts in numerous ways to promote their work. Despite this broad interest, precise definition and delineation of the cyber-physical convergence research domain have received little attention. Also missing is systematic knowledge on the interactions of these concepts with research trajectories. This paper fills these gaps by operationalising a newly constructed definition of convergence, and delineating the associated research domain into five data-centric capabilities: Monitoring, Analytics, Modelling-and-Simulation, Transmission and Security. A bibliometric analysis of the domain is then performed for 2010–2019. There are three findings. First, Analytics and Security have assumed strategic positions within the domain, coinciding with a “strategic turn” in policy. Second, backed by concerted policy and funding efforts, growth in Chinese scientific output has outpaced key competitors U.S. and Germany. Finally, the patterns of promoting their works in terms of the three concepts differ significantly among U.S.-, Germany- and China-based authors, which mirrors the different policy discourses prevalent in those countries.

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  • Exploring new approaches to understanding innovation ecosystems
    In: Technology Analysis & Strategic Management, [Peer Reviewed]
    Date: September 2021

    Jan Youtie, Robert Ward, Philip Shapira, R. Sandra Schillo & E. Louise Earl (2021) Exploring new approaches to understanding innovation ecosystems, Technology Analysis & Strategic Management, DOI: 10.1080/09537325.2021.1972965

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  • Corporate engagement with nanotechnology through research publications
    In: Journal of Nanoparticle Research [Peer Reviewed]
    Date: March 2021

    Assessing corporate engagement with an emerging technology is essential for understanding the development of research and innovation systems. Corporate publishing is used as a system-level knowledge transfer indicator, but prior literature suggests that publishing can run counter to private sector needs for management of dissemination to ensure appropriability of research benefits. We examine the extent of corporate authorship and collaboration in nanotechnology publications from 2000 to 2019. The analysis identified 53,200 corporate  nanotechnology publications. Despite the potential for limits on collaboration with corporate authors, this paper finds that eight out of 10 nanotechnology corporate publications involved authors from multiple organizations and nearly one-third from multiple countries and that these percentages were higher in recent years. The USA is the leading nation in corporate nanotechnology publishing, followed by Japan and Germany, with China ranking fourth, albeit with the greatest publication growth rate. US corporate publishing is more highly cited and less cross-nationally collaborative. Asian countries also have fewer collaborative authorship ties outside of their home countries. European countries had more corporate collaborations with authors affiliated with organizations outside of their home countries. The paper concludes that distinguishing corporate publications,
    while difficult due to challenges in identifying small and medium-sized corporations and grouping variations in corporate names, can be beneficial to examining national systems of research and development.

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  • Tracking developments in artificial intelligence research: constructing and applying a new search strategy
    In: Scientometrics [Peer Reviewed]
    Date: February 2021

    Artificial intelligence, as an emerging and multidisciplinary domain of research and innovation, has attracted growing attention in recent years. Delineating the domain composition
    of artificial intelligence is central to profiling and tracking its development and trajectories. This paper puts forward a bibliometric definition for artificial intelligence which can
    be readily applied, including by researchers, managers, and policy analysts. Our approach starts with benchmark records of artificial intelligence captured by using a core keyword
    and specialized journal search. We then extract candidate terms from high frequency keywords of benchmark records, refine keywords and complement with the subject category
    “artificial intelligence”. We assess our search approach by comparing it with other three recent search strategies of artificial intelligence, using a common source of articles from
    the Web of Science. Using this source, we then profile patterns of growth and international diffusion of scientific research in artificial intelligence in recent years, identify top
    research sponsors in funding artificial intelligence and demonstrate how diverse disciplines contribute to the multidisciplinary development of artificial intelligence. We conclude with
    implications for search strategy development and suggestions of lines for further research. 

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