adea (version 1.5.1)

adea_loads: Compute the variables loads for DEA analysis with specified weights

Description

The adea_loads function calculates variable loads for Data Envelopment Analysis (DEA) with user-specified weights for input and output variables.

Usage

adea_loads(
  input,
  output,
  ux,
  vy,
  load.orientation = c("inoutput", "input", "output")
)

Value

Loads for model, input and output variables

Arguments

input

A matrix or a data frame containing the inputs of the units to be evaluated, with one row for each DMU and one column for each input.

output

A matrix or a data frame containing the outputs of the units to be evaluated, with one row for each DMU and one column for each output.

ux

A matrix of weights for DMUs and input variables.

vy

A matrix of weights for DMUs and output variables.

load.orientation

This parameter allows the selection of variables to be included in load analysis. The default is "inoutput" which means that all input and output variables will be included. Use "input" or "output" to include only input or output variables in load analysis.

Details

In DEA analysis, even when the efficiency scores remain constants, there is a significant degree of freedom in selecting the sets of weights for input and output variables.

Not all sets of weights assign the same importance to the variables. This function allows you to compute the load of each variable based on the provided weights. It also computes load.levels, which represents the minimum values of such loads.

It's important to note that different sets of weights result in different ways to model efficiency. This function does not solve any model. It provides the loads for the specified weights, as described in the theoretical ADEA model.

This function is primarily intended for research and internal use.

Examples

# Load data
data('cardealers4')
# Define input and output
input <- cardealers4[, c('Employees', 'Depreciation')]
output <- cardealers4[, c('CarsSold', 'WorkOrders')]
# Make dea analysis
model <- dea(input, output)
# Show results
model
#   Dealer A  Dealer B  Dealer C  Dealer D  Dealer E  Dealer F
# 0.9915929 1.0000000 0.8928571 0.8653846 1.0000000 0.6515044 
# Compute loads for such weights
adea_loads(input, output, model$ux, model$vy)
# $load
# [1] 0
# $input
#    Employees Depreciation 
#            0            2 
# $iinput
# Employees 
#         1 
# $output
#   CarsSold WorkOrders 
#  1.1025075  0.8974925 
# $ioutput
# WorkOrders