| Kao_Liu_2003 {deaR} | R Documentation |
Data: Kao and Liu (2003).
Description
Data of 24 university libraries in Taiwan with one input and five outputs.
Usage
data("Kao_Liu_2003")
Format
Data frame with 24 rows and 11 columns. Definition of fuzzy inputs (X) and fuzzy outputs (Y):
- x1 = Patronage
It is a weighted sum of the standardized scores of faculty, graduate students, undergraduate students, and extension students in the range of 0 and 1.
- y1 = Collections
Books, serials, microforms, audiovisual works, and database.
- y2 = Personnel
Classified staff, unclassified staff, and student assistants.
- y3 = Expenditures
Capital expenditure, operating expenditure, and special expenditure.
- y4 = Buildings
Area and seats
- y5 = Services
Operating hours, attendance, circulation, communication channels, range of services, amount of services, etc.
- beta3_l
lower spread vector Expenditures
- beta3_u
upper spread vector Expenditures
- beta5_l
lower spread vector Services
- beta5_u
upper spread vector Services
Note
There are three observations that are missing: expenditures of Library 24 and services of Library 22 and Library 23. Kao and Liu (2000b) represent the expenditures of Library 24 by the triangular fuzzy number Y = (0.11; 0.41; 1.0). The services of Library 22 and Library 23 are expressed by a same triangular fuzzy number Y = (0.41; 0.69; 1.0).
Author(s)
Vicente Coll-Serrano (vicente.coll@uv.es). Quantitative Methods for Measuring Culture (MC2). Applied Economics.
Vicente Bolos (vicente.bolos@uv.es). Department of Business Mathematics
Rafael Benitez (rafael.suarez@uv.es). Department of Business Mathematics
University of Valencia (Spain)
Source
Kao, C., Liu, S.T. (2003). “A mathematical programming approach to fuzzy efficiency ranking”, International Journal of Production Economics, 85. doi:10.1016/S0925-5273(03)00026-4
See Also
make_deadata_fuzzy, model_basic
Examples
# Example. Replication of results in Kao and Liu (2003, p.152)
data_example <- make_deadata_fuzzy(Kao_Liu_2003,
dmus = 1,
inputs.mL = 2,
outputs.mL = 3:7,
outputs.dL = c(NA, NA, 8, NA, 10),
outputs.dR = c(NA, NA, 9, NA, 11))
result <- modelfuzzy_kaoliu(data_example,
kaoliu_modelname = "basic",
orientation = "oo",
rts = "vrs",
alpha = 0)
eff <- efficiencies(result)
eff