nonparaeff (version 0.5-13)

revenue.dea: Linear Programming for Revenue Maximization

Description

Solve the Revenue Maximization Probem with Given Output Prices

Usage

revenue.dea(base = NULL, frontier = NULL, noutput = 1, output.price = NULL)

Arguments

base

A data set for DMUs to be evaluated. A data frame with J1*(M+N) dimention, where J1 is the number of DMUs, M for the number of inputs, and N for the number of outputs.

frontier

A data set for DMUs to be used in constructing a production possibility set (PPS). A data frame with J2*(M+N) dimention, where J2 is the number of DMUs, M for the number of inputs, and N for the number of outputs.

noutput

The number of outputs (M).

output.price

A vector for market prices of outputs.

Value

A data frame with J1*(N+6), which has optimal N output factors, maximized revenue when overally efficient, maximized revenue when technically-efficient, revealed revenue, overall efficiency, allocative efficiency, and technical efficiency.

Details

The revenue maximization problem under the CRS assumption is calculated. See Cooper et al. (2007).

References

Cooper, W., Seiford, L. and Tone, K. (2007). Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software (2nd ed.). Springer Verlag, New York.

Lee, J. and Oh, D. (forthcoming). Efficiency Analysis: Data Envelopment Analysis. Press (in Korean).

See Also

cost.dea

Examples

# NOT RUN {
tab8.3 <- data.frame(y1 = c(1, 3, 6, 6, 3, 9),
                          y2 = c(6, 6, 3, 5, 4, 1),
                          x = c(1, 1, 1, 1, 1, 1))
tab8.3.ps.f <- c(p1 = 2, p2 = 2)
(ex8.3 <- revenue.dea(base = tab8.3,
                    noutput = 2, output.price = tab8.3.ps.f))
# }