Arbeitspapier

Benchmarking with uncertain data: a simulation study comparing alternative methods

We consider efficiency measurement methods in the presence of uncertain input and output data, and without the (empirically problematic) assumption of convexity of the production technology. In particular, we perform a simulation study in order to contrast two well-established methods, IDEA and Fuzzy DEA, with a recently suggested extension of Fuzzy DEA in the literature (dubbed the HB method). We demonstrate that the HB method has important advantages over the conventional methods, resulting in more accurate efficiency estimates and narrower bounds for the efficiency scores of individual Decision Making Units (DMUs): thereby providing more informative results that may lead to more effective decisions. The price is computational complexity. Although we show how to significantly speed up computational time compared to the original suggestion, the HB method remains the most computationally heavy method among those considered. This may limit the use of the method in cases where efficiency estimates have to be computed on the fly, as in interactive decision support systems based on large data sets.

Language
Englisch

Bibliographic citation
Series: IFRO Working Paper ; No. 2019/05

Classification
Wirtschaft
Optimization Techniques; Programming Models; Dynamic Analysis
Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
Subject
data envelopment analysis
data uncertainty
fuzzy
imprecise data envelopment analysis
simulation

Event
Geistige Schöpfung
(who)
Hougaard, Jens Leth
Kerstens, Pieter Jan
Nielsen, Kurt
Event
Veröffentlichung
(who)
University of Copenhagen, Department of Food and Resource Economics (IFRO)
(where)
Copenhagen
(when)
2019

Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Arbeitspapier

Associated

  • Hougaard, Jens Leth
  • Kerstens, Pieter Jan
  • Nielsen, Kurt
  • University of Copenhagen, Department of Food and Resource Economics (IFRO)

Time of origin

  • 2019

Other Objects (12)