Robustness of Farrell cost efficiency measurement under data perturbations: Evidence from a US manufacturing application

Hatami-Marbini, Adel; Arabmaldar, Aliasghar

doi:10.1016/j.ejor.2021.03.019

Cited by 14 publications

(6 citation statements)

References 77 publications

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“…Together with the widespread use of the RO approach in diverse fields, several studies have been carried out to tackle the problems of uncertainty in DEA (see e.g. Shokouhi et al 2010 , 2014 ; Sadjadi et al 2011 ; Omrani 2013 ; Lu 2015 ; Arabmaldar et al 2017 ; Tavana et al 2021 ; Arabmaldar et al 2021 ; Hatami-Marbini and Arabmaldar 2021 ;). This strand of DEA models is generally based on the three RO approaches proposed by Mulvey et al ( 1995 ), Ben-Tal and Nemirovski ( 2000 ) and Bertsimas and Sim ( 2004 ).…”

Section: Uncertain Data In the Malmquist Indexmentioning

confidence: 99%

“…Due to the complexity and computational aspects of the analysis of parametric programming problems, we assume that , , and are decision variables in this study resulting in non-linear programming problems. BARON as one of the fastest and most robust solvers is used in this study to solve these non-linear programming models via general algebraic modelling systems (GAMS) to obtain a global optimal or near-global optimal solution (Hatami-Marbini and Arabmaldar 2021 ). Further, in large-scale problems, it is rationale to transform the developed parametric models to the linear optimisation forms and carry out a sensitivity analysis by giving different values to parameter , , and separately.…”

Section: Uncertain Data In the Malmquist Indexmentioning

confidence: 99%

“…Hatami-Marbini et al 2011 , 2017 ; Hatami-Marbini and Saati 2018 ), robust DEA approaches (see e.g. Shokouhi et al 2010 ; Hatami-Marbini and Arabmaldar 2021 ).…”

Section: Introductionmentioning

confidence: 99%

“… 3 The “budgeted uncertainty sets”, “polyhedral uncertainty sets” or “Bertsimas and Sim uncertainty sets” are interchangeably used terms by authors in the literature (Ben-Tal et al 2009 ; Hatami-Marbini and Arabmaldar 2021 ). …”

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confidence: 99%

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Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry

2022

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This paper aims to contribute to the contemporary and imperative research on the performance and productivity growth of the oil industry. Among cutting edge methods, frontier analysis is a successful approach that has been widely used to assess the efficiency and productivity of entities with multiple resources and multiple outputs. This study first develops a unique framework based upon data envelopment analysis (DEA) to measure efficiency and productivity in the way that it tackles the uncertainty in data and undesirable outputs and, in turn, provides useful information to decision-makers. An adaptive robust optimisation is utilised to combat uncertain data whose distributions are unknown and consider the nexus between the level of conservatism and decision-makers’ risk preference. The key advantage of the proposed robust DEA approach is that the results remain relatively unchanged when uncertain conditions exist in the problem. An empirical study on the oil refinery is presented in situations of data uncertainty along with considering CO 2 emissions as the undesirable output to conduct environmental efficiency and productivity analysis of the 25 countries over the period 2000–2018. The empirical results obtained from the proposed approach give some imperative implications. First, results show that the price of robustness does not affect identically for varying technologies when assessing productivity in a global oil market, and the USA oil industry is observed as the highest productivity growth in all cases confirming its efforts for the rapid rise in oil extraction and production at low costs. There may be practical lessons for other nations to learn from the USA oil industry to improve productivity. Findings also support a considerable regress during the 2008 Global Financial Crisis in the oil industry compared to the rest of the periods in question, and due to monetary and fiscal stimulus, there is a sharp productivity growth from 2009 to 2011. The other implication that can be drawn is that the GDP growth rate and technology innovation can more effectively improve the productivity of the oil industry across the globe. Supplementary Information The online version contains supplementary material available at 10.1007/s00291-022-00683-y.

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Section: Uncertain Data In the Malmquist Indexmentioning

confidence: 99%

Section: Uncertain Data In the Malmquist Indexmentioning

confidence: 99%

“…Hatami-Marbini et al 2011 , 2017 ; Hatami-Marbini and Saati 2018 ), robust DEA approaches (see e.g. Shokouhi et al 2010 ; Hatami-Marbini and Arabmaldar 2021 ).…”

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry

2022

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“…Cost efficiency is an important issue that has a critical role in achieving economic growth and sustainable development [6,15,28].The presented method by Cook and Zhu [7] assumes the capability of the ability DMU to produce the current output concerning its prices with minimal cost. These concepts are explored in the Farrell paper [12], which is the idea of evaluating the efficiency of many generating units.…”

Section: Introductionmentioning

confidence: 99%

Role of flexible data in evaluation productivity and cost efficiency using data envelopment analysis

et al. 2022

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In decision management science, recognizing the inputs and outputs of an organization is very important to evaluate its performance. In particular, it becomes more important when costs are incurred for the organization's inputs. In this paper, we evaluate the cost efficiency of a set of decision-making units (DMUs) so that some of its indices can appear as flexibly in the input or output role. Since, if flexible indices are evident in the input index, then they play an important role in costs, it will be important to identify the performance of the units. However, in this paper, using data envelopment analysis (DEA) models, we determine the cost efficiency and productivity of a set of decision-making units with multiple inputs and multiple outputs in the presence of flexible indices. Finally, we present an example that shows the effect of the flexible index on cost efficiency, and also with an application example, we will determine the cost efficiency and productivity of 40 branches of the banks. The obtained result is compared with one of the other methods.

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Evaluating and analyzing renewable energy performance in OECD countries under uncertainty: A robust DEA approach with common weights

Li,

Wu,

Zhu

et al. 2024

Applied Energy

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Robustness of Farrell cost efficiency measurement under data perturbations: Evidence from a US manufacturing application

Cited by 14 publications

References 77 publications

Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry

Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry

Role of flexible data in evaluation productivity and cost efficiency using data envelopment analysis

Evaluating and analyzing renewable energy performance in OECD countries under uncertainty: A robust DEA approach with common weights

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