scholarly journals The efficiency of major container terminals in China: super-efficiency data envelopment analysis approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Liu-Liu Li ◽  
Young-Joon Seo ◽  
Min-Ho Ha
Keyword(s):  
Data Envelopment Analysis ◽  
Container Terminal ◽  
Container Terminals ◽  
Policy Implications ◽  
Terminal Branch ◽  
Data Envelopment ◽  
Content Type ◽  
Super Efficiency ◽  
Dea Model ◽  
Efficiency Data

Purpose Seaports are a signifier for the world economy and international trade. Notwithstanding the considerable role of Chinese ports in global trade, only few studies have explored the efficiency of Chinese container terminals. Furthermore, studies on Chinese port efficiency has typically centered on port-level analysis, not terminal level. Therefore, this study aims to examine the operation efficiency of Chinese container terminals. Design/methodology/approach This study uses super-efficiency data envelopment analysis (SE-DEA) approach. SE-DEA is superior than basic DEA model because it is feasible for categorizing and ranking the efficiency of container terminals more accurately and comprehensively. In the basic model, if the several decision-making units (DMUs) are efficient, the efficiency value of them is “1.” However, in the SE-DEA model, the most efficient DMU is over “1.” Based on the level of container throughput in 2018, the top 20 Chinese container terminal companies were selected. Various production quotas were selected as inputs, while the container throughput was considered output. Findings The findings show that Terminal Shanghai Mingdong Container Terminal Co., Ltd. was ranked 1, followed by Shanghai Shengdong International Container Terminal Co., Ltd., Shanghai International Port (Group) Co., Ltd. and Yidong Container Terminal Branch. Originality/value This study contributes to providing some insights into Chinese container terminal industry to augment the efficiency. This study also provides practical and policy implications (e.g. better terminal operations) for container terminals.

A cross evaluation-based measure of super efficiency in DEA with interval data

Kybernetes ◽  
2016 ◽  
Vol 45 (4) ◽  
pp. 666-679 ◽  
Author(s):  
Qian Yu ◽  
Fujun Hou
Keyword(s):  
Data Envelopment Analysis ◽  
Practical Method ◽  
Interval Data ◽  
Data Envelopment ◽  
Imprecise Data ◽  
Content Type ◽  
Super Efficiency ◽  
Dea Model ◽  
Model Based ◽  
Proposed Model

Purpose – The traditional data envelopment analysis (DEA) model as a non-parametric technique can measure the relative efficiencies of a decision-making units (DMUs) set with exact values of inputs and outputs, but it cannot handle the imprecise data. The purpose of this paper is to establish a super efficiency interval data envelopment analysis (IDEA) model, an IDEA model based on cross-evaluation and a cross evaluation-based measure of super efficiency IDEA model. And the authors apply the proposed approach to data on the 29 public secondary schools in Greece, and further demonstrate the feasibility of the proposed approach. Design/methodology/approach – In this paper, based on the IDEA model, the authors propose an improved version of establishing a super efficiency IDEA model, an IDEA model based on cross-evaluation, and then present a cross evaluation-based measure of super efficiency IDEA model by combining the super efficiency method with cross-evaluation. The proposed model cannot only discriminate the performance of efficient DMUs from inefficient ones, but also can distinguish between the efficient DMUs. By using the proposed approach, the overall performance of all DMUs with interval data can be fully ranked. Findings – A numerical example is presented to illustrate the application of the proposed methodology. The result shows that the proposed approach is an effective and practical method to measure the efficiency of the DMUs with imprecise data. Practical implications – The proposed model can avoid the fact that the original DEA model can only distinguish the performance of efficient DMUs from inefficient ones, but cannot discriminate between the efficient DMUs. Originality/value – This paper introduces the effective method to obtain the complete rank of all DMUs with interval data.

scholarly journals A Range Adjusted Measure of Super-Efficiency in Integer-Valued Data Envelopment Analysis with Undesirable Outputs

2021 ◽  
Vol 9 (4) ◽  
pp. 378-398
Author(s):  
Chunhua Chen ◽  
Haohua Liu ◽  
Lijun Tang ◽  
Jianwei Ren
Keyword(s):  
Data Envelopment Analysis ◽  
Transportation Systems ◽  
Decision Makers ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Super Efficiency ◽  
Dea Model ◽  
Dea Models ◽  
Analysis Models ◽  
Transport Accidents

Abstract DEA (data envelopment analysis) models can be divided into two groups: Radial DEA and non-radial DEA, and the latter has higher discriminatory power than the former. The range adjusted measure (RAM) is an effective and widely used non-radial DEA approach. However, to the best of our knowledge, there is no literature on the integer-valued super-efficiency RAM-DEA model, especially when undesirable outputs are included. We first propose an integer-valued RAM-DEA model with undesirable outputs and then extend this model to an integer-valued super-efficiency RAM-DEA model with undesirable outputs. Compared with other DEA models, the two novel models have many advantages: 1) They are non-oriented and non-radial DEA models, which enable decision makers to simultaneously and non-proportionally improve inputs and outputs; 2) They can handle integer-valued variables and undesirable outputs, so the results obtained are more reliable; 3) The results can be easily obtained as it is based on linear programming; 4) The integer-valued super-efficiency RAM-DEA model with undesirable outputs can be used to accurately rank efficient DMUs. The proposed models are applied to evaluate the efficiency of China’s regional transportation systems (RTSs) considering the number of transport accidents (an undesirable output). The results help decision makers improve the performance of inefficient RTSs and analyze the strengths of efficient RTSs.

Efficiency Comparison in Chinese Construction Industry Based on Data Envelopment Analysis and Super Efficiency Data Envelopment Analysis

2013 ◽  
Vol 275-277 ◽  
pp. 2788-2792
Author(s):  
You Min Gao ◽  
Xiao Wen Wang
Keyword(s):  
Data Envelopment Analysis ◽  
Construction Industry ◽  
Empirical Analysis ◽  
National Economy ◽  
Statistical Data ◽  
Data Envelopment ◽  
Super Efficiency ◽  
Efficiency Comparison ◽  
Efficiency Data

Construction industry is a main industry in national economy, Chinese construction industry has made huge achievement, but the developments between different provinces in China are imbalanced. To compare the different efficiencies between them, data envelopment analysis and an important extended means of DEA were introduced, compared and applied in empirical analysis of Chinese construction industry efficiency between different provinces based on statistical data. Then some conclusions and advices were reached in the end.

scholarly journals Research on Sustainable Development of Resource-Based Cities Based on the DEA Approach: A Case Study of Jiaozuo, China

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Li Li ◽  
Yalin Lei ◽  
Dongyang Pan ◽  
Chunyan Si
Keyword(s):  
Sustainable Development ◽  
Data Envelopment Analysis ◽  
Quantitative Evaluation ◽  
Future Development ◽  
Economic Transformation ◽  
Policy Implications ◽  
Data Envelopment ◽  
The Sustainable Development ◽  
Dea Model

Jiaozuo is a typical resource-based city, and its economic transformation has been an example of success in China. However, quantitative evaluation of the city’s development has scarcely been performed, and future development is not clear. Because of this, using the relevant data from 1999 to 2013, this paper uses the data envelopment analysis (DEA) model to evaluate development after the transformation of Jiaozuo with the aim of providing a basis for its future developing plan. The results show that DEA was effective in 2000, 2004, 2006, 2010, and 2012, was weakly effective in 1999, 2001, 2002, 2003, and 2013, and was ineffective in 2005, 2007, 2008, 2009, and 2011. By evaluating the development of Jiaozuo, this paper provides policy implications for Jiaozuo’s sustainable development, and it may serve as a reference for the sustainable development of China’s other resources-based cities.

scholarly journals Forecasting Models Evaluation Using A Slacks-Based Context-Dependent DEA Framework

2014 ◽  
Vol 30 (5) ◽  
pp. 1477 ◽  
Author(s):  
Jamal Ouenniche ◽  
Bing Xu ◽  
Kaoru Tone
Keyword(s):  
Data Envelopment Analysis ◽  
Methodological Issue ◽  
Oil Prices ◽  
Performance Measure ◽  
Data Envelopment ◽  
Super Efficiency ◽  
Forecasting Models ◽  
Ranking Models ◽  
Context Dependent ◽  
Efficiency Data

Xu and Ouenniche (2012a) proposed an input-oriented radial super-efficiency Data Envelopment Analysis (DEA) based model to address a common methodological issue in the evaluation of competing forecasting models; namely, ranking models based on a single performance measure at a time, which typically leads to conflicting ranks. However, their approach suffers from a number of issues. In this paper, we overcome these issues by proposing a slacks-based context-dependent DEA framework and use it to rank forecasting models of oil prices volatility.

Data envelopment analysis with interactive variables

2015 ◽  
Vol 53 (10) ◽  
pp. 2390-2406 ◽  
Author(s):  
Aibing Ji ◽  
Hui Liu ◽  
Hong-jie Qiu ◽  
Haobo Lin
Keyword(s):  
Data Envelopment Analysis ◽  
Special Form ◽  
Design Methodology ◽  
Data Envelopment ◽  
Content Type ◽  
Dea Model ◽  
Proposed Model ◽  
Choquet Integrals ◽  
Practical Implications ◽  
Decision Making Units

Purpose – The purpose of this paper is to build a novel data envelopment analysis (DEA) model to evaluate the efficiencies of decision making units (DMUs). Design/methodology/approach – Using the Choquet integrals as aggregating tool, the authors give a novel DEA model to evaluate the efficiencies of DMUs. Findings – It extends DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form. At last, the authors use the numerical examples to illustrate the performance of the proposed model. Practical implications – The proposed DEA model can be used to evaluate the efficiency of the DMUs with multiple interactive inputs and outputs. Originality/value – This paper introduce a new DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form.

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