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Classifying inputs and outputs in data envelopment analysis - ScienceDirect
Source: sciencedirect.com
Article summary:
1. Data envelopment analysis (DEA) is a nonparametric methodology for evaluating the efficiency of decision making units (DMUs).
2. In some cases, it can be difficult to determine whether certain measures should be classified as inputs or outputs.
3. This article presents a methodology for deciding the status of flexible variables when such ambiguity is present.
Article analysis:
The article “Classifying inputs and outputs in data envelopment analysis” provides an overview of the use of data envelopment analysis (DEA) to evaluate the efficiency of decision making units (DMUs). The article discusses how in some cases it can be difficult to determine whether certain measures should be classified as inputs or outputs, and presents a methodology for deciding the status of flexible variables when such ambiguity is present.
The article is well-written and provides a clear overview of DEA and its application in various settings. It also provides an explanation of how to decide the input/output status of flexible variables when ambiguity is present. The article does not appear to have any biases or one-sided reporting, and all claims are supported by evidence from previous studies. There are no missing points of consideration or unexplored counterarguments, nor does it contain any promotional content or partiality. Possible risks are noted, and both sides are presented equally throughout the article.
In conclusion, this article appears to be trustworthy and reliable, providing an accurate overview of DEA and its application in various settings while presenting both sides equally without bias or one-sided reporting.