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Industry 4.0: a perspective based on bibliometric analysis
dc.contributor.author | Cobo Martín, Manuel Jesús | |
dc.contributor.author | Jürgens, Björn | |
dc.contributor.author | Herrero Solana, Víctor | |
dc.contributor.author | Martínez Pérez, María Ángeles | |
dc.contributor.author | Herrera Viedma, Enrique | |
dc.date.accessioned | 2019-10-17T08:10:39Z | |
dc.date.available | 2019-10-17T08:10:39Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Cobo, M. J., Jürgens, B., Herrero-Solana, V., Martínez, M. A., & Herrera-Viedma, E. (2018). Industry 4.0: a perspective based on bibliometric analysis. Procedia computer science, 139, 364-371. | es_ES |
dc.identifier.uri | http://hdl.handle.net/10481/57395 | |
dc.description.abstract | The main aim of this contribution is to develop a co-words analysis of the Industry 4.0 research field in order to highlight the themes covered in the last five years (2013–2017). The software tool SciMAT is employed using an approach that allows us to uncover the main research themes and analyze them according to their performance and impact measures. An amount of 333 documents were retrieved from theWeb of Science. Our key findings are that the most important research themes were Cyber-Physical-Systems and Cloud-Computing | es_ES |
dc.description.sponsorship | The authors would like to acknowledge FEDER funds under grant TIN2016-75850-R, and to the program of promotion and development of research activity of the University of Cádiz. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier BV | es_ES |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 España | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | Bibliometric analysis | es_ES |
dc.subject | Science Mapping Analysis | es_ES |
dc.subject | co-words analysis | es_ES |
dc.subject | Industry 4.0 | es_ES |
dc.title | Industry 4.0: a perspective based on bibliometric analysis | es_ES |
dc.type | journal article | es_ES |
dc.rights.accessRights | open access | es_ES |
dc.identifier.doi | 10.1016/j.procs.2018.10.278 |