model_nonradial function

Non-radial DEA model.

Non-radial DEA model allows for non-proportional reductions in each input or augmentations in each output.

model_nonradial(datadea,
                dmu_eval = NULL,
                dmu_ref = NULL,
                orientation = c("io", "oo"),
                rts = c("crs", "vrs", "nirs", "ndrs", "grs"),
                L = 1,
                U = 1,
                maxslack = TRUE,
                weight_slack = 1,
                compute_target = TRUE,
                returnlp = FALSE,
                ...)

Arguments

• datadea: A deadata object, including n DMUs, m inputs and s outputs.
• dmu_eval: A numeric vector containing which DMUs have to be evaluated. If NULL (default), all DMUs are considered.
• dmu_ref: A numeric vector containing which DMUs are the evaluation reference set. If NULL (default), all DMUs are considered.
• orientation: A string, equal to "io" (input-oriented) or "oo" (output-oriented).
• rts: A string, determining the type of returns to scale, equal to "crs" (constant), "vrs" (variable), "nirs" (non-increasing), "ndrs" (non-decreasing) or "grs" (generalized).
• L: Lower bound for the generalized returns to scale (grs).
• U: Upper bound for the generalized returns to scale (grs).
• maxslack: Logical. If it is TRUE, it computes the max slack solution.
• weight_slack: If input-oriented, it is a value, vector of length s, or matrix s x ne (where ne is the length of dmu_eval) with the weights of the output slacks for the max slack solution. If output-oriented, it is a value, vector of length m, or matrix m x ne with the weights of the input slacks for the max slack solution.
• compute_target: Logical. If it is TRUE, it computes targets of the max slack solution.
• returnlp: Logical. If it is TRUE, it returns the linear problems (objective function and constraints) of stage 1.
• ...: Ignored, for compatibility issues.

Examples

# Replication of results in Wu, Tsai and Zhou (2011)
data("Hotels")
data_hotels <- make_deadata(Hotels, 
                            inputs = 2:5, 
                            outputs = 6:8)
result <- model_nonradial(data_hotels, 
                          orientation = "oo", 
                          rts = "vrs")
efficiencies(result)

References

Banker, R.D.; Morey, R.C. (1986). "Efficiency Analysis for Exogenously Fixed Inputs and Outputs", Operations Research, 34, 80-97. tools:::Rd_expr_doi("10.1287/opre.34.4.513")

Färe, R.; Lovell, C.K. (1978). "Measuring the Technical Efficiency of Production", Journal of Economic Theory, 19(1), 150-162. tools:::Rd_expr_doi("10.1016/0022-0531(78)90060-1")

Wu, J.; Tsai, H.; Zhou, Z. (2011). "Improving Efficiency in International Tourist Hotels in Taipei Using a Non-Radial DEA Model", International Journal of Contemporary Hospitatlity Management, 23(1), 66-83. tools:::Rd_expr_doi("10.1108/09596111111101670")

Zhu, J. (1996). “Data Envelopment Analysis with Preference Structure”, The Journal of the Operational Research Society, 47(1), 136. tools:::Rd_expr_doi("10.2307/2584258")

See Also

model_deaps, model_profit, model_sbmeff

Author(s)

Vicente Coll-Serrano (vicente.coll@uv.es ). Quantitative Methods for Measuring Culture (MC2). Applied Economics.

Vicente Bolós (vicente.bolos@uv.es ). Department of Business Mathematics

Rafael Benítez (rafael.suarez@uv.es ). Department of Business Mathematics

University of Valencia (Spain)