Compute DEA efficiency scores

Computes data envelopment analysis (DEA) efficiency scores for a set of decision-making units, under any of the returns-to-scale assumptions supported by dea. The numerical work is done by the Benchmarking package; this function wraps it so the input/output data follow the dea_data contract and the call sits inside one consistent entry point.

Usage

compute_efficiency(
  x,
  rts = c("crs", "vrs", "drs", "irs", "irs2", "fdh", "add"),
  orientation = "in",
  dual = TRUE,
  slack = FALSE,
  ...
)

Arguments

x

A dea_data object, or a data frame coerced by as_dea_data using the default i_/o_ prefix detection. For non-default column selection (explicit inputs/ outputs/id), build the object first with dea_data and pass it in.

rts

Returns to scale, one of "crs", "vrs", "drs", "irs", "irs2", "fdh" or "add".

orientation

Measurement orientation, forwarded to dea (e.g. "in", "out" or "graph").

dual

Logical; if TRUE the multiplier (dual) solution is also returned. Set FALSE to skip it when only the scores are needed.

slack

Logical; if TRUE slacks are computed as well.

...

Further arguments forwarded to dea.

Value

The Farrell object returned by dea, whose $eff component holds the efficiency scores.

Details

The returns-to-scale assumption is selected with rts: in particular "crs" (constant) and "vrs" (variable) are the two most common models, but "drs", "irs", "irs2", "fdh" and "add" are available as well.

See also

dea, which performs the computation; dea_data for the data contract.

Examples

df <- data.frame(i_x = c(2, 3, 4), o_y = c(1, 2, 2))
compute_efficiency(df, rts = "crs")$eff
#> [1] 0.75 1.00 0.75
compute_efficiency(df, rts = "vrs")$eff
#> [1] 1.00 1.00 0.75