Review of Input Congestion Estimating Methods in DEA

Khodabakhshi, Mohammad; Lotfı, Farhad Hosseinzadeh; Aryavash, Kourosh

doi:10.1155/2014/963791

Cited by 11 publications

(5 citation statements)

References 46 publications

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“…In this case, according to the constraints of Model ( 9) in the optimal solution, relation (17) holds: ¼ l j ðk ¼ 1; :::; q; j ¼ 1; :::; nÞ, Model (9) is clearly transformed to Model (2). This shows that any feasible solution of Model (2) is also a feasible solution of Model (9).…”

Section: Plos Onementioning

confidence: 99%

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Congestion in multi-function parallel network DEA

Kassaei,

Lotfi,

Amirteimoori

et al. 2023

PLoS ONE

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Congestion is an economic phenomenon of the production process in which the excessive values of inputs lead to a reduction of the outputs. As the existence of congestion makes to increase costs and decreases efficiency, this issue is not acceptable for decision makers. Hence, many methods have been proposed to detect the congestion in the Data Envelopment Analysis framework (DEA). Most of these methods are designed to deal with the decision making units (DMUs) that have no network structure. However, in most real-world applications, some units are composed of independent production subunits. Therefore, a new scheme is required to determine the congestion of such units. A multi-function parallel system is a more common case in the real world that is composed of the same number of subunits such that each subunit has specific functions. In this paper, considering the operation of individual components of each DMU, a new DEA model is proposed to identify and evaluate the congestion of the multi-function parallel systems. It is shown that the proposed method is highly economical in comparison with the existing black-box view from a computational viewpoint. Then, the proposed model is illustrated using a numerical example along with a real case study.

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Section: Plos Onementioning

confidence: 99%

“…Wie and Yan [ 16 ] studied the problems of congestion using the DEA output-oriented models. Further studies in this field can be found in the work of Khodabakhshi et al [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Congestion in multi-function parallel network DEA

Kassaei,

Lotfi,

Amirteimoori

et al. 2023

PLoS ONE

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“…Because the research program input scale, such as team size and grant size, does not change proportionally, the output of NSFC will not always increase with an increase in grant size input, and sometimes even output will be congested. Congestion is a special return to scale (Wei and Yan, 2004) [58] and in this paper it means that excessive amounts of an input lead to a reduction in the output (Khodabakhshi, et al (2014) [59]). Thus, on the basis of the directional RTS introduced by Yang et al [53] and the congestion research of Wei and Yan et al [58], we investigate the directional RTS under congestion.…”

Section: Directional Dea Model and The Determination Of Rts Under Con...mentioning

confidence: 99%

How large of a grant size is appropriate? Evidence from the National Natural Science Foundation of China

Duan

2022

PLoS ONE

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Under the current universal trend towards larger grant sizes in research funding systems, we focus on how large of a grant size is appropriate. We study the directional returns to scale (RTS) to assess whether current grant sizes are the most productive. We take the General Program of the National Natural Science Foundation of China (NSFC) as an example and select three samples of physics, geography and management for an empirical study. We find that the optimal input direction and the most productive grant size scale is different for the three disciplines; based on the current grant size, physics should not expand the grant size and team size input, geography should further increase the grant size to improve performance and management should further expand the team size rather than the grant size. In this paper, we demonstrate a new method to calculate the optimal direction, which is the lowest rate of congestion, according to the characteristics of the General Program. Based on these results, we also calculate the most productive scale size. This method has certain value for project management.

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“…Hosseinzadeh Lotfi et al [16] used the one-model approach to estimate the input congestion in five Iranian banks, with two stochastic inputs and two outputs. A review of the different approaches to identifying the input congestion of DMUs in DEA can be found in Khodabakhshi, Hosseinzadeh Lotfia, and Aryavash [24]. The aim of the present paper is to determine the input congestion of DMUs using a BCC input relaxation model with precise and imprecise data.…”

Section: Introductionmentioning

confidence: 99%

An input relaxation model for evaluating congestion in fuzzy DEA

Kheirollahi

Hessari

Charles

et al. 2017

Croat. Oper. Res. Rev.

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Abstract. This paper develops a BCC input relaxation model for identifying input congestion as a severe form of inefficiency of decision-making units in fuzzy data envelopment analysis. The possibility approach is presented to obtain the models equivalent to fuzzy models. We use a one-model approach to determine input congestion based on the BCC input relaxation model. A numerical example is given to illustrate the proposed model and identify the congestion with precise and imprecise data. The proposed model is also used to determine the congestion in 16 hospitals using four fuzzy inputs and two fuzzy outputs with a symmetrical triangular membership function.

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Review of Input Congestion Estimating Methods in DEA

Abstract: Congestion is an economic phenomenon in the production process where excessive amounts of the input cause a reduction of the output. The motivation of this paper is to investigate and compare the methods provided for estimating congestion in the DEA literature.

Cited by 11 publications

References 46 publications

Congestion in multi-function parallel network DEA

Congestion in multi-function parallel network DEA

How large of a grant size is appropriate? Evidence from the National Natural Science Foundation of China

An input relaxation model for evaluating congestion in fuzzy DEA

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