Performance analysis of sustainable supply networks with bounded, discrete, and joint factors

Noveiri, Monireh Jahani Sayyad; Kordrostami, Sohrab; Amirteimoori, Alireza

doi:10.1007/s10668-021-01415-y

Cited by 8 publications

(3 citation statements)

References 66 publications

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“…(2018, 2019), Fathi Ajirlo et al . (2019), Jahani Sayyad Noveiri and Kordrostami (2020), Jahani Sayyad Noveiri et al . (2022) and Arana-Jiménez et al .…”

Section: Introductionmentioning

confidence: 98%

“…Therefore, models are needed that do not create optimal points beyond the production possibility set by rounding the number up or down if integer data is used or not lead to a weak and inefficient operating point (Lozano and Villa, 2006). Therefore, DEA models have been proposed to solve these problems, some of which are Lozano and Villa (2006), Kuosmanen and Kazemi Matin (2009), Du et al (2012), Chen et al (2012), Kordrostami et al (2018), Fathi Ajirlo et al (2019), Jahani Sayyad Noveiri and Kordrostami (2020), Jahani Sayyad Noveiri et al (2022 and Arana-Jim enez et al (2021). In the previous studies related to OSS, this type of data was not taken into consideration, and the main goal of this study is to calculate scales in the presence of integer data and undesirable outputs.…”

Section: Introductionmentioning

confidence: 99%

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Average-profit efficiency and optimal scale sizes with integer data and undesirable outputs

Omshi

Kordrostami

Amirteimoori

et al. 2023

JES

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PurposeData envelopment analysis (DEA) is a significant method for measuring the relative efficiency of decision making units (DMUs) that use the least inputs, produce the most desirable outputs and emit the least undesirable outputs in order to maximize their profits. In DEA, detecting an optimal scale size (OSS) is also vital and could be more applicable in economic activities when there are integer and undesirable measures. The purpose of this research is to measure average-profit efficiency (APE) and OSSs with integer data and undesirable outputs.Design/methodology/approachThis study presents an alternative concept of APE using the concepts of most productive scale size (MPSS), profit efficiency and scales, containing desirable and undesirable outputs along with integer and non-integer measures. In fact, the OSS minimizes APE as the optimal scale, which is the ratio of the profit efficiency to the radial average output. Considering the prices of the inputs and desirable outputs, as well as the lack of any specific weight for the undesirable outputs, a two-step model for the numerical calculation of OSS is presented. In addition, the proposed approach is applied to a real data set of Iranian gas companies while there are integer measures and undesirable outputs.FindingsThe results show the introduced approach is beneficial to estimate OSSs from the aspect of maximizing profits of firms with undesirable outputs and integer values.Originality/valueEstimating OSSs is the significant issue for managers, but its investigation in the presence of integer measures and undesirable outputs is presently under-considered.

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“…(2018, 2019), Fathi Ajirlo et al . (2019), Jahani Sayyad Noveiri and Kordrostami (2020), Jahani Sayyad Noveiri et al . (2022) and Arana-Jiménez et al .…”

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Average-profit efficiency and optimal scale sizes with integer data and undesirable outputs

Omshi

Kordrostami

Amirteimoori

et al. 2023

JES

Self Cite

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“…Data envelopment analysis (DEA), first developed by Charnes et al (1978), is a compelling and prevailing approach to assess the performance of entities accompanied by various inputs and outputs. After developing the basic DEA techniques (Banker et al , 1984; Charnes et al , 1978), different DEA studies, including network DEA (Färe and Grosskopf, 1996, 2000; Jahani Sayyad Noveiri et al , 2020; Jahani Sayyad Noveiri et al , 2019; Kao and Hwang, 2008; Lozano, 2015; Maghbouli et al , 2014; Noveiri et al , 2022), worst-practice-frontier DEA (Fathi et al , 2023; Rahimi et al , 2022), ranking DEA (Kordrostami et al , 2016; Mohaghar et al , 2013), interval DEA (Despotis and Smirlis, 2002; Wang et al , 2005) and inverse DEA (An et al , 2019; Emrouznejad et al , 2019; Ghiyasi, 2015; Ghiyasi and Zhu, 2020; Ghobadi, 2018; Lertworasirikul et al , 2011; Wei et al , 2000) were arisen and used to investigate the performance of decision-making units (DMUs) with disparate frameworks and various types of performance measures.…”

Section: Introductionmentioning

confidence: 99%

Inverse two-stage data envelopment analysis with interval measures for resource planning

Zibaei Vishghaei,

Kordrostami,

Amirteimoori

et al. 2023

JM2

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Purpose Assessing inputs and outputs is a significant aspect of taking decisions while there are complex and multistage processes in many examinations. Due to the presence of interval performance measures in various real-world studies, the purpose of this study is to address the changes of interval inputs of two-stage processes for the perturbations of interval outputs of two-stage systems, given that the overall efficiency scores are maintained. Design/methodology/approach Actually, an interval inverse two-stage data envelopment analysis (DEA) model is proposed to plan resources. To illustrate, an interval two-stage network DEA model with external interval inputs and outputs and also its inverse problem are suggested to estimate the upper and lower bounds of the entire efficiency and the stages efficiency along with the variations of interval inputs. Findings An example from the literature and a real case study of the banking industry are applied to demonstrate the introduced approach. The results show the proposed approach is suitable to estimate the resources of two-stage systems when interval measures are presented. Originality/value To the best of the authors’ knowledge, there is no study to estimate the fluctuation of imprecise inputs related to network structures for the changes of imprecise outputs while the interval efficiency of network processes is maintained. Accordingly, this paper considers the resource planning problem when there are imprecise and interval measures in two-stage networks.

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Sustainable Manufacturing Practices through Additive Manufacturing

Piso

Mohamed

Moharana³

et al. 2023

Intelligent Manufacturing Management Systems

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Performance analysis of sustainable supply networks with bounded, discrete, and joint factors

Cited by 8 publications

References 66 publications

Average-profit efficiency and optimal scale sizes with integer data and undesirable outputs

Average-profit efficiency and optimal scale sizes with integer data and undesirable outputs

Inverse two-stage data envelopment analysis with interval measures for resource planning

Sustainable Manufacturing Practices through Additive Manufacturing

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