inis 22(31): 3

Research Article

Identification of key actors in Industry 4.0 informal R&D network

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  • @ARTICLE{10.4108/eetinis.v9i31.1181,
        author={Ľ. Kotorov\^{a} Slušn\^{a} and M. Balog},
        title={Identification of key actors in Industry 4.0 informal R\&D network},
        journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems},
        volume={9},
        number={31},
        publisher={EAI},
        journal_a={INIS},
        year={2022},
        month={5},
        keywords={R\&D, Network, Industry 4.0},
        doi={10.4108/eetinis.v9i31.1181}
    }
    
  • Ľ. Kotorová Slušná
    M. Balog
    Year: 2022
    Identification of key actors in Industry 4.0 informal R&D network
    INIS
    EAI
    DOI: 10.4108/eetinis.v9i31.1181
Ľ. Kotorová Slušná1,*, M. Balog1
  • 1: Centre of Social and Psychological Sciences, SAS, Šancová 56, 811 05 Bratislava, Slovakia
*Contact email: proglslu@savba.sk

Abstract

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 RD 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.