Mahjoub, A. Ridha ; Laghrib, A. ; Metrane, A.(éd.)
In this paper, we introduce a novel multi-period data envelopment analysis (MDEA) model that attempts to circumvent the limitations of the existing MDEA models. The proposed global MDEA model is essentially based on major modifications of fundamental DEA axioms to enable a decision making unit (DMU), defined with inputs and outputs of period t, to be evaluated within the production possibility set (PPS) of another period l, t ≠ l. Building on the properties of the global MDEA model, we also introduce a global productivity index, identified as Global Progress and Regress index (GPRI), that render possible the evaluation of a DMU’s extent of progress or regress over multi-period time horizons under variable returns to scale (VRS) production technologies. This lifts the restrictions to two successive periods and constant returns to scale (CRS) of existing productivity indices. The most salient features of the new MDEA model as well as the GPRI are highlighted using an application that involves a real-life sample of 25 bank branches considered over 4 years.
Keywords: Data envelopment analysis, Multi-period production systems, Global efficiency, Productivity index
@article{RO_2022__56_3_1503_0,
author = {Moghaddas, Zohreh and Oukil, Amar and Vaez-Ghasemi, Mohsen},
editor = {Mahjoub, A. Ridha and Laghrib, A. and Metrane, A.},
title = {Global multi-period performance evaluation {\textendash} {New} model and productivity index},
journal = {RAIRO. Operations Research},
pages = {1503--1521},
year = {2022},
publisher = {EDP-Sciences},
volume = {56},
number = {3},
doi = {10.1051/ro/2022065},
mrnumber = {4438000},
zbl = {1492.90079},
language = {en},
url = {https://www.numdam.org/articles/10.1051/ro/2022065/}
}
TY - JOUR AU - Moghaddas, Zohreh AU - Oukil, Amar AU - Vaez-Ghasemi, Mohsen ED - Mahjoub, A. Ridha ED - Laghrib, A. ED - Metrane, A. TI - Global multi-period performance evaluation – New model and productivity index JO - RAIRO. Operations Research PY - 2022 SP - 1503 EP - 1521 VL - 56 IS - 3 PB - EDP-Sciences UR - https://www.numdam.org/articles/10.1051/ro/2022065/ DO - 10.1051/ro/2022065 LA - en ID - RO_2022__56_3_1503_0 ER -
%0 Journal Article %A Moghaddas, Zohreh %A Oukil, Amar %A Vaez-Ghasemi, Mohsen %E Mahjoub, A. Ridha %E Laghrib, A. %E Metrane, A. %T Global multi-period performance evaluation – New model and productivity index %J RAIRO. Operations Research %D 2022 %P 1503-1521 %V 56 %N 3 %I EDP-Sciences %U https://www.numdam.org/articles/10.1051/ro/2022065/ %R 10.1051/ro/2022065 %G en %F RO_2022__56_3_1503_0
Moghaddas, Zohreh; Oukil, Amar; Vaez-Ghasemi, Mohsen. Global multi-period performance evaluation – New model and productivity index. RAIRO. Operations Research, Tome 56 (2022) no. 3, pp. 1503-1521. doi: 10.1051/ro/2022065
[1] , and , Investigating the efficiency of greenhouse production in Oman: A two-stage approach based on Data Envelopment Analysis and double bootstrapping. J. Clean. Prod. 247 (2020) 119160. | DOI
[2] and , Gangless cross-evaluation in DEA: An application to stock selection. RAIRO: OR 53 (2019) 645–655. | MR | Zbl | Numdam | DOI
[3] and , A procedure for ranking efficient units in data envelopment analysis. Manag. Sci. 39 (1993) 1261–1265. | Zbl | DOI
[4] , , and , Time-staged Outputs in DEA. Omega 55 (2015) 1–9. | DOI
[5] , and , Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag. Sci. 30 (1984) 1078–1092. | Zbl | DOI
[6] , and , Non-linear programming: Theory and algorithms. Published by John Wiley & Sons Inc., Hoboken, New Jersey. Published simultaneously in Canada, 3rd-ed. (2006). | MR | Zbl
[7] , and , The economic theory of index numbers and the measurement of input, output and productivity. Econometrica 50 (1982) 1393–1414. | Zbl | DOI
[8] , and , Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2 (1978) 429–444. | MR | Zbl | DOI
[9] , and , Evaluation of multi-period regional R&D effciency: An application of dynamic DEA to China’s regional R&D systems. Omega 74 (2017) 103–114. | DOI
[10] and , A super-efficiency model for measuring aggregative efficiency of multi-period production systems. Measurement 46 (2013) 3988–3993. | DOI
[11] and , A generalized malmquist productivity index. Sociedad de Estadistica e Investigacion Operative 7 (1999) 81–101. | MR | Zbl
[12] , , and , Evaluation progress and regress of balanced scorecards by multi-stage Malmquist Productivity Index. J. Ind Prod. Eng. 30 (2013) 345–354.
[13] , , and , Modified Malmquist Productivity Index Based on Present Time Value of Money. J. Appl. Math. 2013 (2013) 8. | Zbl | DOI
[14] , , and , Periodic efficiency measurement for achieving correct efficiency among several terms of evaluation. Int. J. Oper. Res. 18 (2013) 1–15. | Zbl | DOI
[15] , and , Two-stage Malmquist Productivity Index with Intermediate Products. Int. J. Ind. Math. 4 (2012) 31–40.
[16] and , Multi-period efficiency and Malmquist productivity index in two-stage production systems. Eur. J. Oper. Res. 232 (2014) 512–521. | MR | Zbl | DOI
[17] and , Multi-period efficiency measurement in data envelopment analysis: The case of Taiwanese commercial banks. Omega 47 (2014) 90–98. | DOI
[18] , , and , Measuring efficiencies of multi-period and multi-division systems associated with DEA: An application to OECD countries national innovation systems. Exp. Syst. Appl. 46 (2016) 494–510. | DOI
[19] and , A global optimization for sustainable multi-domain global manufacturing. Comp. Oper. Res. 89 (2018) 307–323. | MR | Zbl | DOI
[20] , and , A multi-period output DEA model with consistent time lag effects. Comp. Ind. Eng. 93 (2016) 267–274. | DOI
[21] , and , Dynamic Prediction of Financial Distress Using Malmquist DEA. Exp. Syst. Appl. 80 (2017) 94–106. | DOI
[22] , Index numbers and indifference surfaces. Trabajos de Estatistica 4 (1953) 209–242. | MR | Zbl | DOI
[23] and , Eco-efficiency change in power plants: using a slacks-based measure for the meta-frontier MalmquisteLuenberger productivity index. J. Clean. Prod. 105 (2015) 218–232. | DOI
[24] and , The impact of mismeasurement in performance benchmarking: A monte carlo comparison of SFA and DEA with different multi-period budgeting strategies. Eur. J. Oper. Res. 240 (2015) 518–527. | DOI
[25] , and , Cross-efficiency in DEA: A maximum resonated appreciative model. Measurement 63 (2015) 159–167. | DOI
[26] , Ranking via composite weighting schemes under a DEA cross-evaluation framework. Comput. Ind. Eng. 117 (2018) 217–224. | DOI
[27] , Embedding OWA under preference ranking for DEA crossefficiency aggregation: Issues and procedures. Int. J. Intell. Syst. 34 (2019) 947–965. | DOI
[28] , Exploiting value system multiplicity and Preference voting for Robust ranking. Omega Int. J. Manag. Sci. 94 (2020) 102048. | DOI
[29] and , Maximum appreciative cross-efficiency in DEA: A new ranking method. Comput. Ind. Eng. 81 (2015) 14–21. | DOI
[30] and , A systematic approach for ranking football players within an integrated DEA-OWA framework. Manage. Decis. Econ. 38 (2017) 1125–1136. | DOI
[31] and , Benchmarking the hotel industry in Oman through a three-stage DEA based procedure. J. Arts Soc. Sci. 9 (2018) 5–23. | DOI
[32] and , Investigating farming efficiency through a two stage analytical approach: Application to the agricultural sector in Northern Oman. Preprint (2021). | arXiv
[33] and , Ranking dispatching rules in multi-objective dynamic flow shop scheduling: a multi-faceted perspective. Int. J. Prod. Res. 59 (2022) 388–411. | DOI
[34] , and , Performance evaluation of the hotel industry in an emerging tourism destination: Case of Oman. J. Hosp. Tour. Manag. 29 (2016) 60–68. | DOI
[35] , , , , , and , A Surrogate Water Quality Index to assess groundwater using a unified DEA-OWA framework. Environ. Sci. Pollut. Res. 28 (2021) 56658–56685. | DOI
[36] , and , Energy-aware job scheduling in a multi-objective production environment: An integrated DEA-OWA model. Comput. Ind. Eng. 168 (2022) 108065. | DOI
[37] and , Measurement of multi-period aggregative efficiency. Eur. J. Oper. Res. 193 (2009) 567–580. | MR | Zbl | DOI
[38] and , A global Malmquist productivity index. Econ. Lett. 88 (2005) 266–271. | MR | Zbl | DOI
[39] and , A circular Malmquist-type index for measuring productivity. Aston University, UK Working Paper RP08-02 (2008).
[40] , , and , Multi-period data envelopment analysis based on Chebyshev inequality Bounds. Exp. Syst. Appl. 42 (2016) 7759–7767. | DOI
[41] and , Infeasibility of super-efficiency data envelopment analysis models. INFOR 37 (1999) 174–187. | Zbl
[42] and , DEA based multi-period evaluation system for research in academia. Exp. Syst. Appl. 39 (2012) 8274–8278. | DOI
[43] , , , and , A new methodology for assessing water quality, based on data envelopment analysis: Application to Algerian dams. Ecol. Indic. 121 (2021) 106952. | DOI
[44] , , and , Efficiency analysis of public transportation subunits using DEA and Bootstrap Approaches-Dakar Dem Dikk case study. J. Math. Res. 8 (2016) 114–127. | DOI
[45] , , and , A meta-frontier DEA approach to efficiency comparison of carbon reduction technologies on project level. Renew. Sustain. Energy Rev. 82 (2018) 2606–2612. | DOI
Cité par Sources :
