The Hölder Distance Functions: Economic Inefficiency Decompositions

Jesús T. Pastor, Juan Aparicio and José Zofío
Additional contact information
Jesús T. Pastor: Universidad Miguel Hernandez de Elche

Chapter Chapter 9 in Benchmarking Economic Efficiency, 2022, pp 355-397 from Springer

Abstract: Abstract Data Envelopment Analysis can determine both a technical efficiency score and benchmarking information on how to change inputs and outputs to reach the efficient frontier if the firm under evaluation is technically inefficient. All measures studied in this book resort to the determination of benchmarking information through the calculation of the farthest targets for the evaluated DMU—“farthest” in the sense that the measure corresponds to the maximum value of the sum of slacks of the corresponding model or some variation. In the case of the (weighted) additive model discussed in Chap. 6 , for example, this is clearly shown in the objective function of program (6.1). The objective function of this mathematical model consists of the weighted sum of the slack in each dimension (input and output), i.e., the difference between the target located on the strongly efficient frontier and the evaluated unit. In the case of the radial measures, i.e., the Farrell measure of technical efficiency, the situation is not so evident. In DEA, it is not strange to apply a second stage when the radial model is utilized in order to determine Pareto-efficient targets from the projection point. This second stage exploits the additive model. Consequently, we are also maximizing slacks. This means that most of the traditional measures in DEA generate the farthest targets. In other words, they yield the targets that are the most difficult ones to be achieved for the firm/organization in the short run.

Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-030-84397-7_9

Ordering information: This item can be ordered from
http://www.springer.com/9783030843977

DOI: 10.1007/978-3-030-84397-7_9

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla (sonal.shukla@springer.com) and Springer Nature Abstracting and Indexing (indexing@springernature.com).