Philip Shapira
Part-Time Professor
- School of Public Policy
- Technology Policy and Assessment Center
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
- 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
- Science, Technology, and Innovation Policy
Focuses:
- Asia (East)
- Europe
- United States
- United States - Georgia
- Regional Development
- Emerging Technologies - Innovation
- Small and Midsize Enterprises
- Technology Management and Policy
Recent Publications
Journal Articles
- The digitalisation paradox of everyday scientific labour: How mundane knowledge work is amplified and diversified in the biosciences
In: Research Policy [Peer Reviewed]
Date: January 2023
This paper examines how automation and digitalisation influence the way everyday scientific work practices are organised and conducted. Drawing on a practice-based study of the field of synthetic biology, the paper uses ethnographic, interview and survey data to offer a sociomaterial and relational perspective of technological change. As automation and digitalisation are deployed in research settings, our results show the emergence and persistence of what we call ‘mundane knowledge work’, including practices of checking, sharing and standardising data; and preparing, repairing and supervising laboratory robots. While these are subsidiary practices that are often invisible in comparison to scientific outputs used to measure performance, we find that mundane knowledge work constitutes a fundamental part of automated and digitalised biosciences, shaping scientists' working time and responsibilities. Contrary to expectations of the removal of such work by automation and digitalisation, we show that mundane work around data and robots persists through ‘amplification’ and ‘diversification’ processes. We argue that the persistence of mundane knowledge work suggests a digitalization paradox in the context of everyday labour: while robotics and advanced data analytics aim at simplifying work processes, they also contribute to increasing their complexity in terms of number and diversity of tasks in creative, knowledge-intensive professions.
- Analyzing research outcomes and spillovers at a U.S. nanotechnology user facility
In: Journal of Nanoparticle Research [Peer Reviewed]
Date: November 2022
- Analyzing research outcomes and spillovers at a US nanotechnology user facility
In: Journal of Nanoparticle Research [Peer Reviewed]
Date: November 2022
Abstract
This paper maps research outcomes and identifies spillover effects at a US University Research Center (URC) that offers user facilities for nanotechnology research. We use scientometric and network science approaches to analyze measures of topical orientation, productivity, impact, and collaboration applied to URC-related Web of Science abstract publications records. A focus is on the analysis of spillover effects on external organizations (i.e., non-affiliated users). Our findings suggest the URC’s network relies on external organizations acting as brokers, to provide access to the facilities to other external organizations. Analysis of heterophily indicates that collaboration among internal and external organizations is enhanced by the facilities, while articles written by a mix of co-authors affiliated with internal and external organizations are likely to be more cited. These results provide insights on how URCs with user facilities can create conditions for diverse collaboration and greater research impact.
- Building a Bottom-Up Bioeconomy
In: Issues in Science and Technology
Date: 2022
- Commercializing Emerging Technologies through Networks: Insights from Strategies of UK Nanotechnology Small and Midsize Enterprises
In: Journal of Technology Transfer [Peer Reviewed]
Date: 2022
- Policy interactions with research trajectories: The case of cyber-physical convergence in manufacturing and industrials
In: Technological Forecasting and Social Change [Peer Reviewed]
Date: 2022
- 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.
- 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.