Developing an Output-Oriented Super Slacks-Based Measure Model with an Application to Third-Party Reverse Logistics Providers

Azadi, Majid; Saen, Reza Farzipoor

doi:10.1002/mcda.483

Cited by 17 publications

(6 citation statements)

References 55 publications

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“…In terms of the study of input and output efficiency between different regions, some scholars used conventional DEA, which likely lead to the situation that the calculated value of many units is 1, and the efficiency value of some units has little difference, so it is not better to compare the efficiency values of different regions. This result is the same as study of some scholars [32,[54][55][56][57][58][59][60][61]. In contrast, the super efficiency SBM used in this paper can solve this problem well, which is also an advantage of efficiency comparison in this paper.…”

Section: Discussionsupporting

confidence: 82%

Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces

Chen

Yao

2021

Forests

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Forests play a very important role in carbon dioxide emissions and climate change, and the development of China’s forestry is of great significance to our citizens. However, it is an arduous task for us to improve forestry output at a high and good level while taking environmental factors into account. In this paper, the non-expected super-efficiency SBM (slacks-based measure) model was used to measure the forestry ecological efficiency (FEE) of 31 provinces in China from 2004 to 2018, and the spatial and temporal evolution of FEE in different regions of China was analysed by using spatial econometric method. Tobit regression and random forest algorithm were selected to analyze the influence on FEE. The results showed that, firstly, the average annual increase of the national total factor productivity change of China’s forestry was 1.2%, and that the average annual increase of the national total factor productivity change in the eastern region was lower than that in the central and western regions. Secondly, the distribution of China’s FEE of the northeast and the south was higher, and FEE of China’s middle regions was relatively lower in 2004, but then the FEE in Northeast China has decreased, and the FEE has increased gradually from north to south in 2018. The agglomeration of high-tech industries in most regions of China had obvious positive spatial correlation characteristics in 2018. Thirdly, there was a negative correlation between forestry fixed assets investment and FEE, environmental regulation was an important factor affecting the ecological efficiency of forestry in China, and the level of economic development and industrial structure also had a certain impact on FEE.

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Section: Discussionsupporting

confidence: 82%

Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces

Chen

Yao

2021

Forests

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“…The DEA is a mathematical model which determines the weight sets to optimize the performance score of a DMU (in this study, the faculty) under evaluation by benchmarking with other DMUs. Therefore, the DEA technique is suitable for the faculty's target setting because it can provide the comparison or benchmark of operational performance with multiple inputs and outputs between faculties (Azadi & Saen, 2011;Najadat et al, 2019).…”

Section: Dea Modeling For Faculty's Target Settingmentioning

confidence: 99%

Identifying an Efficiency Productivity Model for Faculties with DEA Benchmarking Technique

Jaijit

Piamsa-nga

Phisanbut

et al. 2022

IJMKL

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Purpose: Many universities in Thailand aim to raise their ranking; thus, university administrators set the target outputs for their institutions. However, the university-level targets may differ from those at the faculty levels because the inherent nature of academic fields and faculty capacity to produce outputs may not be considered. Therefore, we propose a model to determine possible target values for faculty outputs with weak efficiency by benchmarking the university under study with one of the leading universities in Thailand. As a result, the evidence-based target values allow inefficient faculties to know what outputs they need to improve under the assumption that "if each faculty improves their productivity to reach a target value, the university can rank higher." This can lead to a more realistic and achievable target instead of a single target across all faculties. Study design/methodology/approach: Due to inherent differences among faculties, they are clustered by subject areas with the hierarchical cluster analysis to reduce bias. Then an efficiency score of each faculty is computed via the Data Envelopment Analysis. Findings: The faculties of the university under study are clustered into three subject areas: 1) agricultural science and technology management, 2) engineering and ecology, and 3) social sciences and humanities. The DEA technique provides the slack values to be used in target settings that mitigate the bias from different capabilities on producing outputs across subject areas. For the faculties in agricultural science and technology management, social sciences, and humanities, the inadequacy of performed research and teaching operations are essential indicators, i.e., the percentage of the sum of slack values in both aspects is more than 80%. In engineering and ecology, the essential indicators (i.e., the percentage of the sum of slack values in both aspects is 91.10%) are related to teaching and international outlook operations. However, the teaching operation is the most critical aspect (i.e., the maximum value of the percentage sum of each subject area's slack values is 42.23%) that all subject areas should be focused on for improvement. Originality/value: Our approach can provide a quantitative decision support tool that allows university administrators to set realistic operational policies according to evidence-based target values tailored for each subject area.

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“…The reverse logistics provider was also measured using traditional DEA by an Indian apparel manufacturer [27] and once by [28] using the SBM-DEA model. In this study, only desired inputs and outputs were selected.…”

Section: Literature Reviewmentioning

confidence: 99%

An Integrated Analytic Hierarchy Process—Slack Based Measure-Data Envelopment Analysis Model for Evaluating the Efficiency of Logistics Service Providers Considering Undesirable Performance Criteria

Bajec

Tuljak-Suban

2019

Sustainability

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Sustainable concerns are reputed to be of the utmost priority among governments. Consequently, they have become more and more of a concern among supply chain partners. Logistics service providers (LPs), as significant contributors to supply chain success but also one of the greatest generator of emissions, play a significant role in reducing the negative environmental impact. Thus, the performance evaluations of LPs should necessarily involve such a measure which, firstly, represents a balance between all three pillars of sustainability and, secondly, consider the desirable and undesirable performance criteria. This paper proposes an integrated analytic hierarchy process (AHP) and slack-based measure (SBM) data envelopment analysis (DEA) model, based on the assumption of a variable return to scale (VRS). An AHP pairwise comparison enables selecting the most influential input/output variables. Output-oriented SBM DEA provides simultaneously evaluation of both the undesirable and desirable outputs. The proposed model was tested on a numerical example of 18 LPs. The comparison of output Charnes, Cooper and Rhodes (CCR) and SBM DEA models resulted in a higher number of inefficient LPs when the SBM DEA model was applied. Moreover, efficiency scores of inefficient LPs were lower in SBM DEA model. The proposed model is fair to those LPs that are environmentally friendly.

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Developing an Output-Oriented Super Slacks-Based Measure Model with an Application to Third-Party Reverse Logistics Providers

Cited by 17 publications

References 55 publications

Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces

Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces

Identifying an Efficiency Productivity Model for Faculties with DEA Benchmarking Technique

An Integrated Analytic Hierarchy Process—Slack Based Measure-Data Envelopment Analysis Model for Evaluating the Efficiency of Logistics Service Providers Considering Undesirable Performance Criteria

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