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Resource Specialisation

Source: R/resource_specialisation.R
resource_specialisation.Rd

Analyses whether resources specialise in specific activities.

This metric can give an overview of which resources are performing certain activities more than others, and which resources are responsible for containing all knowledge or capabilities on one topic.

Usage

resource_specialisation(
  log,
  level = c("log", "activity", "resource"),
  sort = TRUE
)

resource_specialization(
  log,
  level = c("log", "activity", "resource"),
  sort = TRUE
)

# S3 method for class 'log'
resource_specialisation(
  log,
  level = c("log", "activity", "resource"),
  sort = TRUE
)

# S3 method for class 'grouped_log'
resource_specialisation(
  log,
  level = c("log", "activity", "resource"),
  sort = TRUE
)

Arguments

log

log: Object of class log or derivatives (grouped_log, eventlog, activitylog, etc.).

level

character (default "log"): Level of granularity for the analysis: "log" (default), , "activity", or "resource". For more information, see vignette("metrics", "edeaR") and 'Details' below.

sort

logical (default TRUE): Sort output on count. Only for levels with frequency count output.

Details

Argument level has the following options:

  • At "log" level, this metric provides summary statistics on the number of distinct activities executed per resource.

  • On "activity" level, this metric provides an overview of the absolute and relative number of different resources executing this activity within the complete log. This will give insights into which activities resources are specialised in.

  • On "resource" level, this metric shows the absolute and relative number of distinct activities that each resource executes.

Methods (by class)

  • resource_specialisation(log): Computes the resource specialisation for a log.

  • resource_specialisation(grouped_log): Computes the resource specialisation for a grouped_log.

References

Swennen, M. (2018). Using Event Log Knowledge to Support Operational Exellence Techniques (Doctoral dissertation). Hasselt University.

See also

Other metrics: activity_frequency(), activity_presence(), end_activities(), idle_time(), number_of_repetitions(), number_of_selfloops(), number_of_traces(), processing_time(), resource_frequency(), resource_involvement(), start_activities(), throughput_time(), trace_coverage(), trace_length()