TY - JOUR
T1 - Policy interactions with research trajectories: The case of cyber-physical convergence in manufacturing and industrials
T2 - The case of cyber-physical convergence in manufacturing and industrials
AU - Bordoloi, Tausif
AU - Shapira, Philip
AU - Mativenga, Paul
N1 - Funding Information:
The types of sponsor acknowledged include research councils, regional and federal government departments and agencies, universities, scholarship and fellowship programmes, foundations and firms. There were more than 6500 names (and their variants) of sponsors. Different variants (abbreviations, acronyms, spelling errors) of sponsors were cleaned (manually and using VantagePoint) and then combined. After two rounds of cleaning, we zoomed in on the top ten sponsors in terms of articles with funding acknowledgement ( Fig. 10 ). All sponsors in the top ten group funded more papers in the 2016–2019 period than in the prior 2010–2015 period. These ten sponsors accounted for 53.9% of the funded articles (or 1466 articles) published between 2010 and 2019, within which a group of five funders is acknowledged in about 83% of the articles. The National Natural Science Foundation of China (NSFC) leads with 427 articles, followed by the European Union or EU (308 articles), the National Science Foundation or NSF (288 articles) and the two German sponsors – the Federal Ministry of Education and Research or BMBF (101 articles) and the German Research Foundation or DFG (81 articles). Overall, the US has three funders amongst the top ten global sponsors (including U.S. Department of Energy and Defense Advanced Research Projects Agency), Germany has two, China, South Korea, Taiwan, the U.K. and the EU have one each.
Funding Information:
Tausif Bordoloi is supported by a doctoral scholarship from the Alliance Manchester Business School , The University of Manchester. The funding source had no involvement in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.
Funding Information:
The number of papers with acknowledged NSFC sponsorship has increased by more than 15 times since the inflection point in 2016 and overtaken both the EU and the NSF by 2017. In addition to NSFC, which is managed by the Ministry of Science and Technology of China, two other notable Chinese funders in the top 20 research sponsors are the National Basic Research Program of China (973 Program) and the China Postdoctoral Science Foundation. Backed by such support, China's output in cyber-physical convergence research has increased by over 300% from 77 articles in 2015 to 370 in 2019.
Publisher Copyright:
© 2021 Elsevier Inc.
PY - 2022/2/1
Y1 - 2022/2/1
N2 - 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.
AB - 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.
KW - Digital manufacturing
KW - Industrial internet
KW - Industrie 4.0
KW - Industry 4.0
KW - Smart manufacturing
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=pure_starter&SrcAuth=WosAPI&KeyUT=WOS:000775946700039&DestLinkType=FullRecord&DestApp=WOS_CPL
U2 - 10.1016/j.techfore.2021.121347
DO - 10.1016/j.techfore.2021.121347
M3 - Article
SN - 0040-1625
VL - 175
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
M1 - 121347
ER -