revenue.dea: Linear Programming for Revenue Maximization

In nonparaeff: Nonparametric Methods for Measuring Efficiency and Productivity

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.

Details

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

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.

Author(s)

Dong-hyun Oh, [e-mail]

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

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))

nonparaeff documentation built on June 21, 2022, 9:05 a.m.