Computers and Operations Research
Using DEA window analysis to measure efficiencies of Taiwan's integrated telecommunication firms
Telecommunications Policy
Short Communication: Matrix games with interval data
Computers and Industrial Engineering
Efficiency measurement and ranking of the tutorial system using IDEA
Expert Systems with Applications: An International Journal
Interval efficiency assessment using data envelopment analysis
Fuzzy Sets and Systems
An efficiency-driven approach for setting revenue target
Decision Support Systems
The mean-absolute deviation portfolio selection problem with interval-valued returns
Journal of Computational and Applied Mathematics
Sensitivity and stability analysis in fuzzy data envelopment analysis
Fuzzy Optimization and Decision Making
A geometrical approach for fuzzy DEA frontiers using different T norms
WSEAS TRANSACTIONS on SYSTEMS
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Data Envelopment Analysis (DEA) models, as ordinarily employed, assume that the data for all inputs and outputs are known exactly. In some applications, however, a number of factors may involve imprecise data, which take forms such as ordinal rankings and knowledge only of bounds. Here we provide an example involving a Korean mobile telecommunication company. The Imprecise Data Envelopment Analysis (IDEA) method we use permits us to deal not only with imprecise data and exact data but also with weight restrictions as in the (now) widely used "Assurance Region" (AR) and "cone-ratio envelopment" approaches to DEA. We also show how to transform AR bounds on thevariables, obtained from managerial assessments, for instance, intodata adjustments. This involves an extended IDEA model, which we refer to as AR-IDEA. All these uses are illustrated by an example application directed to evaluate efficiencies of branch offices of a telecommunication company in Korea.