Benchmarking Shipbuilders’ Turnover of Main Assets

2009 ◽  
Vol 25 (04) ◽  
pp. 175-181
Author(s):  
Emerson C. Colin ◽  
Marcos M. O. Pinto
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Lifting Capacity ◽  
Current Asset ◽  
Asset Turnover ◽  
Physical Assets ◽  
Inputs And Outputs

This paper presents an analysis of the historical and current asset turnover of several shipbuilding companies and regions, such being responsible for more than 50% of global production. Several turnover measures are used including, as inputs, main physical assets such as dock area, berth length, and lifting capacity; and as outputs, compensated gross tonnage (CGT), and the number of different ships produced. Data Envelopment Analysis is used to gauge the inputs and outputs of the companies in order to define their efficiency and identify the benchmarks in terms of asset usage. Results consolidated by region indicate that there are efficient companies producing in all of the regions studied: China, Europe, Japan, and Korea.

scholarly journals Finding the Most Preferred Decision-Making Unit in Data Envelopment Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-8
Author(s):  
Shirin Mohammadi ◽  
S. Morteza Mirdehghan ◽  
Gholamreza Jahanshahloo
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Utility Function ◽  
Decision Maker ◽  
Programming Models ◽  
Data Envelopment ◽  
Production Possibility ◽  
Decision Making Unit ◽  
Inputs And Outputs

Data envelopment analysis (DEA) evaluates the efficiency of the transformation of a decision-making unit’s (DMU’s) inputs into its outputs. Finding the benchmarks of a DMU is one of the important purposes of DEA. The benchmarks of a DMU in DEA are obtained by solving some linear programming models. Currently, the obtained benchmarks are just found by using the information of the data of inputs and outputs without considering the decision-maker’s preferences. If the preferences of the decision-maker are available, it is very important to obtain the most preferred DMU as a benchmark of the under-assessment DMU. In this regard, we present an algorithm to find the most preferred DMU based on the utility function of decision-maker’s preferences by exploring some properties on that. The proposed method is constructed based on the projection of the gradient of the utility function on the production possibility set’s frontier.

Empirical Analysis of Operational Efficiency of China’s Telecommunication Industry: Based on DEA Approach

2013 ◽  
Vol 291-294 ◽  
pp. 3019-3023
Author(s):  
Chang Jian Qi ◽  
Ting Jie Lv
Keyword(s):  
Data Envelopment Analysis ◽  
Technological Progress ◽  
Evaluation Model ◽  
Indicator System ◽  
Telecommunication Industry ◽  
Data Envelopment ◽  
Resource Allocation Efficiency ◽  
Major Factors ◽  
Infinite Model ◽  
Inputs And Outputs

By combining the Data Envelopment Analysis (DEA) method, from the view of time and district, this paper carries out a dynamic evaluation of resource allocation efficiency of China’s telecommunication industry from 1973 to 2008. The results show that technical efficiency indicator and technological progress indicator are the major factors of resources allocation of China’s telecommunication industry. It analyzed and studied all previous reorganization and regulation effects to the telecom with the reference to the efficiency changes of the telecom industry. Based on the non-Archimedean infinite model C2R of the Data Envelopment Analysis, combined with characteristics of inputs and outputs of China’s telecommunication industry, the paper sets up an indicator system of inputs and outputs as well as an overall efficiency evaluation model China’s telecommunication industry.

scholarly journals A full investigation of the directional congestion in data envelopment analysis

2019 ◽  
Author(s):  
somayeh khezri ◽  
Akram Dehnokhalaji ◽  
Farhad Hosseinzadeh Lotfi
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Input Output ◽  
Input And Output ◽  
Dea Models ◽  
Systems Of Inequalities ◽  
Full Investigation ◽  
Decision Making Units ◽  
Inputs And Outputs

One of interesting subjects in Data Envelopment Analysis (DEA) is estimation of congestion of Decision Making Units (DMUs). Congestion is evidenced when decreases (increases) in some inputs re- sult in increases (decreases) in some outputs without worsening (im- proving) any other input/output. Most of the existing methods for measuring the congestion of DMUs utilize the traditional de nition of congestion and assume that inputs and outputs change with the same proportion. Therefore, the important question that arises is whether congestion will occur or not if the decision maker (DM) increases or de- creases the inputs dis-proportionally. This means that, the traditional de nition of congestion in DEA may be unable to measure the con- gestion of units with multiple inputs and outputs. This paper focuses on the directional congestion and proposes methods for recognizing the directional congestion using DEA models. To do this, we consider two di erent scenarios: (i) just the input direction is available. (ii) none of the input and output directions are available. For each scenario, we propose a method consists in systems of inequalities or linear pro- gramming problems for estimation of the directional congestion. The validity of the proposed methods are demonstrated utilizing two nu- merical examples.

scholarly journals Evaluation of Operation Efficiency of High-Tech Industry with Application of Data Envelopment Analysis

2019 ◽  
Vol 64 ◽  
pp. 130-139
Author(s):  
Li WEI ◽  
Thomas WARD
Keyword(s):  
Data Envelopment Analysis ◽  
Product Life Cycle ◽  
Product Diversification ◽  
High Tech ◽  
Data Envelopment ◽  
Competitive Situation ◽  
High Tech Industry ◽  
Customer Needs ◽  
Operation Efficiency ◽  
Inputs And Outputs

High-tech industry is facing the globally competitive situation that the development strategy for technology industry to integrate national power, combine international resources, and conform to the market trend is required for developing the internationally competitive high-tech industry in China. Following high customization and the development of product diversification to conform to various customer needs as well as short product life cycle, it becomes more important to understand the relative business performance of high-tech companies to the industry in China and evaluate the strengths and weaknesses in order to rapidly respond to customer needs and maintain high-quality products. Modified Delphi Method is utilized in this study for selecting inputs and outputs. The variable data used in this study are acquired from open statistical data of enterprises. Data Envelopment Analysis (DEA) is further used for evaluating the efficiency. The research results conclude that 1 DMU shows strong efficiency, with better operation efficiency, 4 DMUs present the operation efficiency between 0.9 and 1 that the operation efficiency can be more easily enhanced, and 5 DMUs appear the operation efficiency lower than 0.9, with obvious inefficiency. Furthermore, inputs and outputs are gradually removed in DEA for understanding the sensitivity to efficiency. Finally, suggestions are proposed according to the results, expecting to assist high-tech industry in China in the business development.

Sign in / Sign up

Export Citation Format

Share Document