Identification of key actors in Industry 4.0 informal R&D network
DOI:
https://doi.org/10.4108/eetinis.v9i31.1181Keywords:
R&D, Network, Industry 4.0Abstract
INTRODUCTION: Industry 4.0 is a concept covering various research areas. Their development depends on the cooperation among several stakeholders, particularly public R&D (Research and Development) organisations.
OBJECTIVES: This article aims to provide a mapping of informal strategic R&D partnerships of public R&D organisations in an ambiguously defined area of Industry 4.0.
METHODS: Scientific collaboration mapping method based on self-identification is used. Moreover, social network analysis is used to discuss patterns and specific characteristics of this network. Empirical data are gathered through a questionnaire survey focused on managers of RD teams in the Slovak Republic.
RESULTS: The resulting network of public R&D organisations operating in the field of Industry 4.0 in the Slovak Republic is connected, though characterised by low density. Intra-regional cooperation prevailed only in the region of the capital city. In other regions, cross-regional cooperation was dominant. Most cooperations occur between universities; cooperation between faculties and within one faculty is less frequent. Key teams of the network were identified based on their performance in three selected indicators of centrality. Three of them represented the first layer or core of the network.
CONCLUSION: Within the network, active actors with a high number of cooperation and those located in its network centre who can support knowledge transfer across the identified R&D network are crucial. Our results confirmed that several variables are important to creating new collaborations and thus not limited to geographical proximity, institutional affinity and size of the workplace.
Downloads
References
Aldieri L, Kotsemir M, Paolo Vinci C. The impact of research collaboration on academic performance: An empirical analysis for some European countries. Socio-Econ. Plan. Sci. 2018; 62(C): 13-30.
Aldieri L, Kotsemir M, Paolo Vinci C. The Effects of Collaboration on Research Performance of Universities: An Analysis by Federal District and Scientific Fields in Russia. J. Knowl. Econ. 2020; 11: 766–787.
Balog M, Herčko J. Industry 4.0 - Technological Priorities in the Slovakia. PP: FAR. 2020; 12(1): 5-21.
Beaver D. Reflections on Scientific Collaboration (and its study): Past, Present, and Future. Scientometrics. 2001; 52(3): 365-377.
Beier G, et al. Industry 4.0: How it is defined from a sociotechnical perspective and how much sustainability it includes - A literature review. J. Clean. Prod. 2020; 259: 120856.
Bozeman B, Corley E. Scientists' collaboration strategies: Implications for scientific and technical human capital. Res. Policy. 2004; 33(4): 599-616.
Contandriopoulos D, Duhoux A, Larouche C, Perroux M. The Impact of a Researcher’s Structural Position on Scientific Performance: An Empirical Analysis. PLoS ONE. 2016; 11(8): e0161281.
Culot G, Nassimbeni G, Orzes G, Sartor M. Behind the definition of Industry 4.0: Analysis and open questions. Int. J. Prod. Econ. 2020; 226: 107617.
Garg KC, Padhi P. A study of collaboration in laser science and technology. Scientometrics. 2001; 51: 415–427.
Giustolisi O, Ridolfi L, Simone A. Embedding the intrinsic relevance of vertices in network analysis: the case of centrality metrics. Sci. Rep. 2020; 10(3297).
Hansen D, Shneiderman B, Smith M, Himelboim I. Analyzing Social Media Networks with NodeXL. Insights from a Connected World. Second Edition. Morgan Kaufmann; 2019.
Lee DH, Seo WI, Choe HCH, Kim DH. Collaboration network patterns and research performance: the case of Korean public research institutions. Scientometrics. 2012; 91: 925–942.
Liang L, Kretschmer H, Guo Y, Beaver D. Age structures of scientific collaboration in Chinese computer science. Scientometrics. 2001; 52: 471–486.
Lotrecchiano GR, et al. Individual motivation and threat indicators of collaboration readiness in scientific knowledge producing teams: a scoping review and domain analysis. Heliyon. 2016; 2(5).
Muriithi P, Horner D, Pemberton L, Wao H. Factors influencing research collaborations in Kenyan universities. Res. Policy. 2018; 47(1): 88-97.
National Academy of Science and Engineering: Securing the future of German manufacturing industry. Recommendations for implementing the strategic initiative INDUSTRIE 4.0. In: Final report of the Industrie 4.0 Working Group. 2013.
Nosalska K, et al. Industry 4.0: coherent definition framework with technological and organizational interdependencies. J. Manuf. Technol. Manag. 2020; 31(5).
Opsahl T, Agnessens F, Skvoretz J. Node centrality in weighted networks: Generalizing degree and shortest paths. Soc. Netw. 2010; 32(3): 245-251.
Porac J, et al. Human capital heterogeneity, collaborative relationships, and publication patterns in a multidisciplinary scientific alliance: a comparative case study of two scientific teams. Res. Policy. 2004 ; 33(4): 661-678.
Reji Kumar K, Manuel S. Collaborations of Indian institutions which conduct mathematical research: A study from the perspective of social network analysis. Scientometrics. 2018; 117: 1041–1051.
Rigby J, Edler J. Peering inside research networks: Some observations on the effect of the intensity of collaboration on the variability of research quality. Res. Policy. 2005; 34(6): 784-794.
Seglen PO, Aksnes DW. Scientific productivity and group size: a bibliometric analysis of norwegian microbiological research. Scientometrics. 2000; 49: 125–143.
Smit J, et al.: Industry 4.0. DG For Internal Policies. Policy Department A: Economic and scientific policy; 2016.
Tay IS, Chuan LT, Aziati AHN, Ahmad ANA. An Overview of Industry 4.0: Definition, Components, and Government Initiatives. J. Adv. Res. Dyn. Control Syst. 2018; 10(14).
The Royal Society: Knowledge, networks and nations. Global scientific collaboration in the 21st century. In: Excellence in Science, London; 2011.
Wowk K, et al. Evolving academic culture to meet societal needs. Comment. Nature. 2017; 3(35).
Zitt M, Bassecoulard E, Okubo Y. Shadows of the past in international cooperation: collaboration profiles of the top five producers of science. Scientometrics. 2000; 47: 627– 657.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 EAI Endorsed Transactions on Industrial Networks and Intelligent Systems

This work is licensed under a Creative Commons Attribution 3.0 Unported License.
This is an open-access article distributed under the terms of the Creative Commons Attribution CC BY 3.0 license, which permits unlimited use, distribution, and reproduction in any medium so long as the original work is properly cited.