Time envelopment analysis: A new method for effectively incorporating time series in data envelopment analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F25%3A10257595" target="_blank" >RIV/61989100:27510/25:10257595 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0957417425014137?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0957417425014137?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.eswa.2025.127791" target="_blank" >10.1016/j.eswa.2025.127791</a>
Alternative languages
Result language
angličtina
Original language name
Time envelopment analysis: A new method for effectively incorporating time series in data envelopment analysis
Original language description
Data envelopment analysis (DEA) is a non-parametric tool for empirically evaluating the relative efficiency of homogeneous organizational units, i.e., decision-making units, by estimating the production frontiers. Time series analysis is a statistical technique that considers a series of data collected chronologically over time intervals. This study introduces a three-stage method, Time Envelopment Analysis (TEA), to effectively integrate time series analysis into DEA. The three-stage method includes a first-order autoregressive (AR(1)) model followed by DEA and ordinary least squares (OLS). The performance of the TEA method with four different values for the AR(1) parameters is compared with the DEA-OLS procedure using extensive Monte Carlo simulations. The simulation results show that the TEA method outperforms the DEA-OLS procedure. We further demonstrate that TEA is more accurate when the autoregressive parameter is smaller, particularly in scenarios defined by a progressive decrease in the impact of technical inefficiencies. We evaluate the proposed TEA method using a realworld healthcare dataset from 63 countries by estimating the effect of contextual variables on each country’s productivity.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50200 - Economics and Business
Result continuities
Project
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Continuities
O - Projekt operacniho programu
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Expert Systems with Applications
ISSN
0957-4174
e-ISSN
1873-6793
Volume of the periodical
282
Issue of the periodical within the volume
July
Country of publishing house
GB - UNITED KINGDOM
Number of pages
15
Pages from-to
127791
UT code for WoS article
001482119700001
EID of the result in the Scopus database
2-s2.0-105003567120