Policy interactions with research trajectories: The case of cyber-physical convergence in manufacturing and industrials

Tausif Bordoloi, Philip Shapira and Paul Mativenga

Technological Forecasting and Social Change, 2022, vol. 175, issue C

Abstract: From the early 2010s, policymakers and firms in advanced industrial economies began introducing approaches to systemically exploit manufacturing and industrial data using the notion of cyber-physical convergence. Three innovation concepts have been especially highlighted: Smart Manufacturing, the Industrial Internet and Industrie 4.0. In parallel, academics have employed these concepts in numerous ways to advance 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, including the U.S. and Germany. Finally, the patterns of promoting their works in terms of the three concepts differ significantly amongst U.S.-, Germany- and China-based authors, which mirrors the different policy discourses prevalent in those countries.

Keywords: Industrie 4.0; Industry 4.0; Smart manufacturing; Industrial internet; Digital manufacturing (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:175:y:2022:i:c:s0040162521007782

DOI: 10.1016/j.techfore.2021.121347

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