Eliminating congestion by increasing inputs in R&amp;D activities of Chinese universities

Ren, Xian-tong; Fukuyama, Hirofumi; Yang, Guo-liang

doi:10.1016/j.omega.2022.102618

Cited by 11 publications

(4 citation statements)

References 57 publications

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“…The focus of our paper in Journal of Productivity Analysis (Ren and Yang 2023) is different compared to the previously published paper (Ren et al 2022). However, the authors accept that there is important overlap and duplication between the two papers which should have been acknowledged in Ren and Yang (2023).…”

mentioning

confidence: 80%

Correction to: Eliminating congestion in China’s papermaking and paper products industry: from both the perspective of increasing and decreasing inputs

Ren,

Yang

2024

J Prod Anal

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mentioning

confidence: 80%

Correction to: Eliminating congestion in China’s papermaking and paper products industry: from both the perspective of increasing and decreasing inputs

Ren,

Yang

2024

J Prod Anal

Self Cite

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“…By placing the parameters of Model ( 21) according to Table 1, this model can be rewritten as Model (22): Model ( 22) is a linear programming problem that can be easily solved in a fraction of a second by using the LP Solver of GAMS software. By solving Model (22), it is concluded that…”

Section: Plos Onementioning

confidence: 99%

“…In the context of resources saving and climate change, Chen [ 21 ] extended the Cooper-family model by using a range adjusted measure (RAM) approach to incorporate carbon emissions under the DEA framework. Xian-ton Ren et al [ 22 ] tried to eliminate congestion by increasing input on research and development activities at Chinese universities. They also analyzed the relationship between congestion and overinvestment.…”

Section: Introductionmentioning

confidence: 99%

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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“…Since the method of data envelopment analysis (DEA) was proposed by Charnes et al (1978), identifying congestion has become an important research topic. The concept of congestion in DEA was first discussed and defined by Färe and Svensson (1980), and the congestion identification method was continuously improved by Cooper et al (1996), Tone and Sahoo (2004), Wei and Yan (2004), Sueyoshi and Sekitani (2009), Fang (2015), Mehdiloozad et al (2018), Ren et al (2022), etc. However, there are two problems can be further studied.…”

Section: Introductionmentioning

confidence: 99%

Measuring the degree of congestion in two-stage DEA: A case of Chinese textile, wearing apparel, and accessories industry

Ren,

Song,

Yang

2024

Preprint

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This paper develops a method to identify congestion and measure the degree of congestion in two-stage data envelopment analysis (DEA). First, the congestion in the two-stage DEA is defined. Next, based on the definition, a slack-based method is proposed to identify congestion and measure the degree of congestion in the two-stage DEA. We compare our method with the congestion identification method in one-stage DEA and find that the two-stage DEA can provide more accurate congestion information than treating the production process as a black box. The method we propose is used to assess congestion in the Chinese textile, wearing apparel, and accessories industry. The empirical results show that the degree of congestion in the Chinese textile, wearing apparel, and accessories is getting worse, although it has been weakening from 2013–2014. The information can be used to support the corresponding policymaking for the managers of both government and enterprises.

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Eliminating congestion by increasing inputs in R&D activities of Chinese universities

Cited by 11 publications

References 57 publications

Correction to: Eliminating congestion in China’s papermaking and paper products industry: from both the perspective of increasing and decreasing inputs

Correction to: Eliminating congestion in China’s papermaking and paper products industry: from both the perspective of increasing and decreasing inputs

Congestion in multi-function parallel network DEA

Measuring the degree of congestion in two-stage DEA: A case of Chinese textile, wearing apparel, and accessories industry

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