cross_efficiency_fuzzy {deaR}

Cross efficiency fuzzy analysis

Description

Computes the cross-efficiency fuzzy tables from DEA fuzzy data or a Guo-Tanaka DEA model solution. The (crisp) relative efficiencies for the case h = 1 are obtained from the CCR model (model_multiplier).

Usage

cross_efficiency_fuzzy(datadea,
                       orientation = c("io", "oo"),
                       h = 1,
                       selfapp = TRUE)

Arguments

datadea

An object of class dea_fuzzy or deadata_fuzzy. If it is of class dea_fuzzy it must have been obtained with modelfuzzy_guotanaka.

orientation

A string, equal to "io" (input-oriented) or "oo" (output-oriented).

h

A numeric vector with the h-levels (in [0,1]).

selfapp

Logical. If it is TRUE, self-appraisal is included in the average scores of A and e.

Author(s)

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

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

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

University of Valencia (Spain)

References

Doyle, J.; Green, R. (1994). “Efficiency and Cross Efficiency in DEA: Derivations, Meanings and the Uses”, Journal of Operational Research Society, 45(5), 567–578. doi:10.2307/2584392

Guo, P.; Tanaka, H. (2001). "Fuzzy DEA: A Perceptual Evaluation Method", Fuzzy Sets and Systems, 119, 149–160. doi:10.1016/S0165-0114(99)00106-2

León, T.; Liern, V.; Ruiz, J.L.; Sirvent, I. (2003). "A Fuzzy Mathematical Programming Approach to the assessment of efficiency with DEA Models", Fuzzy Sets Systems, 139(2), 407–419. doi:10.1016/S0165-0114(02)00608-5

Sexton, T.R., Silkman, R.H.; Hogan, A.J. (1986). Data envelopment analysis: critique and extensions. In: Silkman RH (ed) Measuring efficiency: an assessment of data envelopment analysis, vol 32. Jossey-Bass, San Francisco, pp 73–104. doi:10.1002/ev.1441

Examples

 data("Guo_Tanaka_2001")
 datadea <- make_deadata_fuzzy(datadea = Guo_Tanaka_2001, 
                               inputs.mL = 2:3, 
                               inputs.dL = 4:5, 
                               outputs.mL = 6:7, 
                               outputs.dL = 8:9)
 result <- cross_efficiency_fuzzy(datadea = datadea, 
                                  h = seq(0, 1, 0.2))