Libraries {deaR}

Data: Cooper, Seiford and Tone (2007).

Description

Data for 23 public libraries of the Tokyo Metropolitan Area in 1986.

Usage

data("Libraries")

Format

Data frame with 23 rows and 7 columns. Definition of inputs (X) and outputs (Y):

x1 = AREA

Floor area (unit=1000 m2)

x2 = BOOKS

Number of books (unit=1000)

x3 = STAFF

Staff

x4 = POPULATION

Population (unit=1000)

y1 = REGISTERED

Registered residents (unit=1000)

y2 = BORROWED

Borrowed books (unit=1000)

Author(s)

Vicente Coll-Serrano ([e-mail]). Quantitative Methods for Measuring Culture (MC2). Applied Economics.

Vicente Bolos ([e-mail]). Department of Business Mathematics

Rafael Benitez ([e-mail]). Department of Business Mathematics

University of Valencia (Spain)

Source

Cooper, W.W.; Seiford, L.M. and Tone, K. (2007). Data Envelopment Analysis. A Comprehensive Text with Models, Applications, References and DEA-Solver Software. Springer.

See Also

make_deadata, model_basic

Examples

# Example 1. Non-controllable input (POPULATION).
# Replication of results in Cooper, Seiford and Tone (2007, p.221)
data(Libraries)
# POPULATION (non-controllable input) is the 4th input.
data_example <- make_deadata(Libraries,
                             dmus = 1,
                             inputs = 2:5,
                             nc_inputs = 4,
                             outputs = 6:7)
result <- model_basic(data_example,
                      orientation = "io",
                      rts = "crs")
efficiencies(result)
targets(result)

# Example 2. Non-discretionary input (POPULATION).
data(Libraries)
# POPULATION (non-controllable input) is the 4th input.
data_example2 <- make_deadata(Libraries,
                              dmus=1,
                              inputs=2:5,
                              nd_inputs=4,
                              outputs=6:7)
result2 <- model_basic(data_example2,
                       orientation="io",
                       rts="crs")
efficiencies(result2)
targets(result2)