TY - JOUR
T1 - Data Envelopment Analysis and hyperbolic efficiency measures
T2 - Extending applications and possibilities for between-group comparisons
AU - Öttl, Alexander
AU - Asmild, Mette
AU - Gulde, Daniel
N1 - Funding Information:
We would like to express our thanks to Takibur Rahmen and Rasmus Nielsen for providing exemplary data. Special appreciation goes to Lorenz Aigner and the anonymous reviewers for proofreading and offering helpful comments. Lastly, we are grateful to Sofia Lavin for her motivation in initiating the project.
Publisher Copyright:
© 2023 The Author(s)
PY - 2023
Y1 - 2023
N2 - Data Envelopment Analysis (DEA) is a widely used tool to estimate relative efficiencies. However, this methodology encounters issues when between-group comparisons with variable returns of scale (VRS) are of interest. In this specification efficiency scores can be undefined when the projection of the efficiency estimation of an observation from one group does not have an intersection with the frontier of the other group. To address this issue, a hyperbolic efficiency estimation can be used. Up to now, the literature lacks consideration of weight restrictions and non-discretionary variables in the hyperbolic DEA method. Weight restrictions allow redefining the production possibility set (PPS), while non-discretionary variables adjust the model's orientation. Considering these factors, it is possible to incorporate prior knowledge, substitution effects, and increase discriminatory power. This paper introduces the respective mathematical formulations and the practical implementation in statistical software. The estimation methods have been combined in an R-package called hyperbolicDEA in order to facilitate the application of hyperbolic DEA with weight restrictions, non-discretionary variables, and additional functionalities. An empirical example of fish farms illustrates the advantages of the introduced methodologies and the functionalities of the R-package.
AB - Data Envelopment Analysis (DEA) is a widely used tool to estimate relative efficiencies. However, this methodology encounters issues when between-group comparisons with variable returns of scale (VRS) are of interest. In this specification efficiency scores can be undefined when the projection of the efficiency estimation of an observation from one group does not have an intersection with the frontier of the other group. To address this issue, a hyperbolic efficiency estimation can be used. Up to now, the literature lacks consideration of weight restrictions and non-discretionary variables in the hyperbolic DEA method. Weight restrictions allow redefining the production possibility set (PPS), while non-discretionary variables adjust the model's orientation. Considering these factors, it is possible to incorporate prior knowledge, substitution effects, and increase discriminatory power. This paper introduces the respective mathematical formulations and the practical implementation in statistical software. The estimation methods have been combined in an R-package called hyperbolicDEA in order to facilitate the application of hyperbolic DEA with weight restrictions, non-discretionary variables, and additional functionalities. An empirical example of fish farms illustrates the advantages of the introduced methodologies and the functionalities of the R-package.
KW - DEA software
KW - Efficiency analysis
KW - Hyperbolic Data Envelopment Analysis
KW - Non-discretionary variables
KW - Weight restrictions
U2 - 10.1016/j.dajour.2023.100343
DO - 10.1016/j.dajour.2023.100343
M3 - Journal article
AN - SCOPUS:85181888928
VL - 9
JO - Decision Analytics Journal
JF - Decision Analytics Journal
SN - 2772-6622
M1 - 100343
ER -