dm.dynamic.bc: Dynamic DEA in the presence of intertemporal Budget...

In DJL: Distance Measure Based Judgment and Learning

Dynamic DEA in the presence of intertemporal Budget Constraints

Description

Employs the Farrell measure on carry-over budget as well as input or output

Usage

dm.dynamic.bc(xdata, ydata, zdata, bdata, rts="crs", orientation="i", wv=NULL)

Arguments

xdata	Input array (n by m by t)
ydata	Output array (n by s by t)
zdata	Budget(spent) array (n by b by t)
bdata	Budget(secured) array (n by b)
rts	Returns to scale assumption "crs" Constant RTS (default) "vrs" Variable RTS "irs" Increasing RTS "drs" Decreasing RTS
orientation	Orientation of the measurement "i" Input-orientation (default) "o" Output-orientation
wv	Weight vector for scalarization (1 by m or s)

Value

$eff.s	System Efficiency
$eff.t	Period Efficiency
$lambda	Intensity vectors
$xslack	Input slack
$yslack	Output slack
$zslack	Budget(spent) slack
$aslack	Budget(available) slack

Author(s)

Dong-Joon Lim, PhD

References

Lim, D.-J., M.-S., Kim, & K.-W., Lee. (2020). "A revised dynamic DEA model with budget constraints." International Transactions in Operational Research (In press).

See Also

dm.dea Distance measure using DEA

Examples

# Load data
  df.io <- array(c(2, 4, 8, 4, 1, 2, 2, 2, 3, 6, 12, 6,
                   5, 4, 3, 8, 1, 1, 1, 1, 5, 4,  3, 8),
                 c(4, 3, 2), 
                 dimnames = list(LETTERS[1:4], c("X", "Y", "z"), c("t1", "t2")))
  df.Z.0 <- array(c(9, 12, 18, 24), c(4, 1), dimnames = list(LETTERS[1:4], c("Z^0")))

# Run
  dm.dynamic.bc(df.io[,1,], df.io[,2,], df.io[,3,], df.Z.0)

DJL documentation built on March 31, 2023, 9:05 p.m.