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Integer data in DEA: Illustrating the drawbacks and recognizing congestion
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DOI：10.1016/j.cie.2019.06.046.png)
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Abstract
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Congestion is one of the most important phenomena in the production processes that reducing (increasing) one or more inputs can increase (decrease) one or more outputs. Recently, Karimi, Khorram, and Moeini (2016) presented a data envelopment analysis (DEA) procedure to identify congestion of decision-making units (DMUs) in integer-valued DEA. This study first provides two counterexamples and shows that their procedure may not be capable of identifying congestion, correctly; and then proposes an integer-valued slack-based DEA approach for recognizing the right- and left-hand congestion status of the DMUs who are all characterized by the technology dealing with both negative and/or non-negative continuous and integer data. Finally, a numerical example is provided to make a comparison between our proposed approach and the Karimi et al.'s (2016) approach, and then an illustrative empirical application regarding Japanese banking is presented to demonstrate the applicability of our proposed approach.
Keywords:
Data envelopment analysis (DEA)
Integer DEA (IDEA)
Congestion
Slack variables
Mixed integer linear programming (MILP) model
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