Two-stage DEA models with undesirable input-intermediate-outputs

Liu, Wenbin; Zhou, Zhongbao; Ma, Chaoqun; Liu, Debin; Shen, Wanfang

doi:10.1016/j.omega.2015.03.009

Cited by 136 publications

(61 citation statements)

References 46 publications

(83 reference statements)

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“…As mentioned before, Constraint (16) can be obtained by summation of Constraints (17) and (18), so it is redundant. Besides, Constraint (18) can be obtained by summation of two constraints summarized in Constraint (19), so this one is redundant, too. Li utilized Bellman and Zadeh's max-min operator and proposed a two-phase approach [29] using max-min operator as phase I; The optimal solution obtained by phase I was supplemented with the constraints of the problem as the minimum solution value in phase II.…”

Section: Multi-objective Methodology For Ndeamentioning

confidence: 99%

“…Li et al modeled a two-stage structure by assuming the inputs to the second stage, including both the outputs from the rst stage and additional inputs to the second stage [18]. Recently, Liu et al tried to systematically examine two-stage DEA models with undesirable input-intermediate-outputs [19]. Besides, Matin and Azizi introduced a uni ed general model for e ciency evaluation of network production systems when arbitrary relations between individual subprocesses were allowed [20].…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Efficiency assessment of Iranian Handmade Carpet Company by network DEA

Zegordi

Omid

2017

Scientia Iranica

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Abstract. Di erent categories of Iranian handmade carpet are produced each year. Due to resource limitation, it is so important for managers to allocate more resources to the most e cient categories. Therefore, the main purpose of this illustration is to consider most e cient types of carpet in production and sales stages. To do so, di erent categories of Iranian handmade carpet are considered as DMUs. This study utilizes network DEA for constructing a model to analyze total and partial e ciencies of Iranian Handmade Carpet Company (IHCC), simultaneously. IHCC consists of three main departments that are working jointly to maximize productivity of the rm; therefore, the case of IHCC is a multi-stage system with shared intermediate variables, extra inputs to the second stage, and undesired outputs. The novelty of this paper is the methodology used for calculating the e ciency, which is based on multi-objective programming. Results of experimental data of IHCC are summarized in order to prepare some brilliant management strategies based on partial and total e ciency scores of di erent carpet categories. Because of the lack of familiar researches in the area of carpet industry e ciency measurement, this research will provide valuable information for decision makers.

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Section: Multi-objective Methodology For Ndeamentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Efficiency assessment of Iranian Handmade Carpet Company by network DEA

Zegordi

Omid

2017

Scientia Iranica

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“…We also would like to point out that other DEA methodologies have been used to assess the efficiency of banks; for example, Network DEA (e.g., Matthews 2013; Grigoroudis et al 2013;Akther et al 2013;Fukuyama and Matousek 2017;Gulati and Kumar 2017), Network DEA with undesirable variables (e.g., An et al 2015;Liu et al 2015), Dynamic DEA (e.g., Avkiran and Goto 2011;Fukuyama andWeber 2015, 2017), Dynamic Network DEA (e.g., Avkiran 2015;Chao et al 2015;Fukuyama andWeber 2015, 2017;Zha et al 2016;Wu et al 2016;Fukuyama and Weber 2017b), Fuzzy DEA (e.g., Wang et al 2014;Wanke et al 2016;Hatami-Marbini et al 2017), DEA with Bootstrapping (e.g., Ferrier and Hirschberg 1997), Fuzzy DEA with Bootstrapping (e.g., Wanke et al 2016), and Stochastic DEA (e.g., Kao and Liu 2009). For a recent survey, we refer the reader to Kaffash and Marra (2017).…”

Section: Landscape Of Research On Efficiency Assessment In Bankingmentioning

confidence: 99%

Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback

Ouenniche

Carrales

2018

Ann Oper Res

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Data envelopment analysis (DEA) has witnessed increasing popularity in banking studies since 1985. In this paper, we propose a new DEA-based analysis framework with a regression-based feedback mechanism, where regression analysis provides DEA with feedback that informs about the relevance of the inputs and the outputs chosen by the analyst. Unlike previous studies, the DEA models used within the proposed framework could use both inputs and outputs, only inputs, or only outputs. So far, the UK banking sector remains relatively under researched despite its crucial importance to the UK economy. We use the proposed framework to address several research questions related to both the efficiency of the UK commercial banking sector and DEA analyses with and without regression-based feedback. Empirical results suggest that, on average, the commercial banks operating in the UK-whether domestic or foreign-are yet to achieve acceptable levels of overall technical efficiency, pure technical efficiency, and scale efficiency. On the other hand, DEA analyses with and without a linear regression-based feedback mechanism seem to provide consistent findings; however, in general DEA analyses without feedback tend to over-or under-estimate efficiency scores depending on the orientation of the analyses. Furthermore, in general, a linear regression-based feedback mechanism proves effective at improving discrimination in DEA analyses unless the initial choice of inputs and outputs is well informed.Keywords Data envelopment analysis · Efficiency · UK commercial banks · DEA models without explicit inputs · DEA models without explicit outputs

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“…However, in some real applications, production process may also use undesirable inputs and generate undesirable outputs [69], like smoke pollution or waste [78,79]. Consequently, authors of [80,81] have stated that in that production process both desirable and undesirable factors may be presented within the models of DEA methodology.…”

Section: Description Of Non-radial Dea Modelmentioning

confidence: 99%

Application of Multicriteria Decision-Making Methods in Railway Engineering: A Case Study of Train Control Information Systems (TCIS)

Djordjević¹,

Krmac²

2018

Modern Railway Engineering

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In order to improve its position in the transport market railway, as a complex system, it has to fulfill a number of objectives such as increased capacity and asset utilization, improved reliability and safety, higher customer service levels, better energy efficiency and fewer emissions, along with increased economic viability and profits. Some of these objectives call for the implementation of maximum values, while some of them require minimum values. Additionally, some can be expressed quantitatively, while some, for example, customer service, can be described qualitatively through a descriptive scale of points. The application of MCDM in railway engineering can play a significant role. Therefore, the major objective of this chapter is the review of the application of MCDM methods in railway engineering. As one of the means in achieving the objectives of railways and above all the utilization of capacity are Train Control Information Systems (TCIS). Based on that, the aim of this chapter is the evaluation of the efficiency of TCIS in the improvement of railway capacity utilization through defined technical-technological indicators. The non-radial Data Envelopment Analysis (DEA) model for the evaluation of TCIS efficiency in improvement of utilization of railway capacity using the selected indicators is proposed. The proposed non-radial DEA model for TCIS efficiency evaluation in using railway capacity could be applied to an overall network or for separate parts of railway lines.

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Two-stage DEA models with undesirable input-intermediate-outputs

Cited by 136 publications

References 46 publications

Efficiency assessment of Iranian Handmade Carpet Company by network DEA

Efficiency assessment of Iranian Handmade Carpet Company by network DEA

Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback

Application of Multicriteria Decision-Making Methods in Railway Engineering: A Case Study of Train Control Information Systems (TCIS)

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