The Industrial Robot Evolution in the World. A First Dendrogram for a Cluster Analysis
Fecha
2020-02-04Estado
info:eu-repo/semantics/publishedVersionMetadatos
Mostrar el registro completo del ítemResumen
Adoption of high tech robot systems help economies and companies to be more competitive. We have analyzed the evolution of 71 countries, calculating
the robot density (robots for each 10,000 people of active population). We have used a clustering algorithm using the dissimilarity measure which takes
into consideration both the proximity of the values and the behavior of the series (temporal correlation). Our preliminary findings show that there exist four different
clusters, based on their robot densification evolution over the years. These clusters, composed of countries with a similar evolution over time, have also
similar competitiveness levels. Adoption of high tech robot systems help economies and companies to be more competitive. We have analyzed the evolution of 71 countries, calculating
the robot density (robots for each 10,000 people of active population). We have used a clustering algorithm using the dissimilarity measure which takes
into consideration both the proximity of the values and the behavior of the series (temporal correlation). Our preliminary findings show that there exist four different
clusters, based on their robot densification evolution over the years. These clusters, composed of countries with a similar evolution over time, have also
similar competitiveness levels.
The Industrial Robot Evolution in the World. A First Dendrogram for a Cluster Analysis
Tipo de Actividad
Artículos en revistasISSN
2195-3562Materias/ categorías / ODS
Innovación docente y Analytics (GIIDA)Palabras Clave
Robot, Automation, Global competitiveness,Employment,ClusterRobot, Automation, Global competitiveness,Employment,Cluster