A procedure for ranking efficient units in data envelopment analysis
Management Science
The use of data envelopment analysis for technology selection
Computers and Industrial Engineering
Multicriteria decision analysis with minimum information: combining DEA with MAVT
Computers and Operations Research
Computers and Operations Research
Ranking of units on the DEA frontier with common weights
Computers and Operations Research
An integrated decision making approach for ERP system selection
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Improving the discrimination power and weights dispersion in the data envelopment analysis
Computers and Operations Research
Data envelopment analysis for weight derivation and aggregation in the analytic hierarchy process
Computers and Operations Research
Evaluation of information technology investment: a data envelopment analysis approach
Computers and Operations Research
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This article seeks to enhance acceptance of the profile distance method (PDM) in decision support systems. The PDM is a multiple attributive-based decision making as well as a multiple method approach to support complex decision making and uses a heuristic to avoid computationally complex global optimization. We elaborate on the usability of the method and question the heuristic used. We present a bi-section algorithm, which efficiently supports the discovery of transition profiles needed in a user-friendly and practical application of the method. Additionally, we provide empirical evidence showing that the proposed heuristic is efficient and delivers results within 5% of the global optimizer for a wide range of datasets.