Cooperation and Competition Strategy Analysis of Decision-Making Units Based on Efficiency Game

2020 ◽  
Vol 29 (2) ◽  
pp. 235-248
Author(s):  
Li Cao ◽  
Zhanxin Ma ◽  
Muren
Keyword(s):  
Decision Making ◽  
Competition Strategy ◽  
Strategy Analysis ◽  
Cooperation And Competition ◽  
Decision Making Units

Competition strategy and efficiency evaluation for decision making units with fixed-sum outputs

2011 ◽  
Vol 212 (3) ◽  
pp. 560-569 ◽  
Author(s):  
Feng Yang ◽  
Desheng Dash Wu ◽  
Liang Liang ◽  
Liam O’Neill
Keyword(s):  
Decision Making ◽  
Efficiency Evaluation ◽  
Competition Strategy ◽  
Decision Making Units

scholarly journals Business Strategy Analysis—Lenovo

2018 ◽  
Vol 6 (3) ◽  
pp. 245
Author(s):  
Yunli Guo
Keyword(s):  
Decision Making ◽  
Business Strategy ◽  
Swot Analysis ◽  
Strategy Choice ◽  
Competition Strategy ◽  
Current Position ◽  
Care Policy ◽  
Strategy Analysis ◽  
Customer Care ◽  
Plan Action

<em>Business Strategy is a set of decision-making and actions that help the company to gain competitive advantage and to win competition. Strategy Choice is to decide which best strategy to choose. In this paper, I would like to use SWOT analysis in order to identify Lenovo’s resource strength, weakness, opportunities and threats in PC marketing. A SWOT analysis is a method for assessing organization’s current position in order to plan action and resources appropriately. There are also certain researches on Lenovo’s Customer Care Policy, and through investigations and analysis to identify whether they have a good customer care policy and whether they meet the customers’ needs and satisfactions. Finally, identify the area need improve that can help company better meet customer needs and satisfactions, and help company have improvement on its operation and development.</em>

scholarly journals DEA-based competition strategy in the presence of undesirable products: An application to paper mills

2021 ◽  
Vol 31 (2) ◽  
Author(s):  
Alireza Amirteimoori ◽  
Simin Masrouri
Keyword(s):  
Decision Making ◽  
Efficient Frontier ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Competition Strategy ◽  
Paper Mills ◽  
Trade Off ◽  
Production Processes ◽  
Output Factors ◽  
Decision Making Units

In real applications of data envelopment analysis (DEA), there are cases in which undesirable outputs are produced along with desirable outputs in such a way that the total sum of the produced undesirable outputs over the production units must be fixed and constant. In this case, a trade-off between the decision making units (DMUs) is needed to balance the production of undesirable outputs. In a rational sight, this trade-off is done in such a way that all DMUs improve their relative performances. In this paper, a single DEA-based model is proposed to model fixed and variable-sum undesirable outputs in production processes. A common equilibrium efficient frontier is constructed and after reallocating the input/output factors, all decision making units (DMUs) prevail as efficient. A real case of 32 paper mills in China is given. The analysis results demonstrated that some economically developed paper mills have better performance than less developed paper mills; in particular, all efficient paper mills are the developed ones.

Relative Efficiency of Decision Making Units Producing Both Desirable and Undesirable Outputs: A Case of Textile Processing Units in Pakistan.

2011 ◽  
Vol 50 (4II) ◽  
pp. 685-698
Author(s):  
Samina Khalil
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Value Added ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Textile Processing ◽  
Decision Making Unit ◽  
Desirable And Undesirable Outputs ◽  
Decision Making Units

This paper aims at measuring the relative efficiency of the most polluting industry in terms of water pollution in Pakistan. The textile processing is country‘s leading sub sector in textile manufacturing with regard to value added production, export, employment, and foreign exchange earnings. The data envelopment analysis technique is employed to estimate the relative efficiency of decision making units that uses several inputs to produce desirable and undesirable outputs. The efficiency scores of all manufacturing units exhibit the environmental consciousness of few producers is which may be due to state regulations to control pollution but overall the situation is far from satisfactory. Effective measures and instruments are still needed to check the rising pollution levels in water resources discharged by textile processing industry of the country. JEL classification: L67, Q53 Keywords: Data Envelopment Analysis (DEA), Decision Making Unit (DMU), Relative Efficiency, Undesirable Output

scholarly journals Teaching and Learning Process of Decision-Making Units in Talented Young Players From U-10 to U-14

2020 ◽  
Vol 11 ◽  
Author(s):  
Juan Carlos Pastor-Vicedo ◽  
Alejandro Prieto-Ayuso ◽  
Onofre Ricardo Contreras-Jordán ◽  
Filipe Manuel Clemente ◽  
Pantelis Theo Nikolaidis ◽  
...  
Keyword(s):  
Decision Making ◽  
Learning Process ◽  
Teaching And Learning ◽  
Decision Making Units

scholarly journals Developing an approach for decision making units integration using multi objective particle swarm optimization

2014 ◽  
Vol 4 (1) ◽  
pp. 48 ◽  
Author(s):  
Abdorrahman Haeri ◽  
Kamran Rezaie ◽  
Seyed Morteza Hatefi
Keyword(s):  
Decision Making ◽  
Particle Swarm Optimization ◽  
Performance Measures ◽  
Particle Swarm ◽  
Final Decision ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Decision Making Unit ◽  
The Difference ◽  
Decision Making Units

In recent years, integration between companies, suppliers or organizational departments attracted much attention. Decision making about integration encounters with major concerns. One of these concerns is which units should be integrated and what is the effect of integration on performance measures. In this paper the problem of decision making unit (DMU) integration is considered. It is tried to integrate DMUs so that the considered criteria are satisfied. In this research two criteria are considered that are mean of efficiencies of DMUs and the difference between DMUs that have largest and smallest efficiencies. For this purpose multi objective particle swarm optimization (MOPSO) is applied. A case with 17 DMUs is considered. The results show that integration has increased both considered criteria effectively.  Additionally this approach can presents different alternatives for decision maker (DM) that enables DM to select the final decision for integration.

scholarly journals Measuring the Productivity of Energy Consumption of Major Industries in China: A DEA-Based Method

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Xishuang Han ◽  
Xiaolong Xue ◽  
Jiaoju Ge ◽  
Hengqin Wu ◽  
Chang Su
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Data Envelopment Analysis ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Data Envelopment ◽  
Policy Makers ◽  
Time Periods ◽  
Decision Making Units

Data envelopment analysis can be applied to measure the productivity of multiple input and output decision-making units. In addition, the data envelopment analysis-based Malmquist productivity index can be used as a tool for measuring the productivity change during different time periods. In this paper, we use an input-oriented model to measure the energy consumption productivity change from 1999 to 2008 of fourteen industry sectors in China as decision-making units. The results show that there are only four sectors that experienced effective energy consumption throughout the whole reference period. It also shows that these sectors always lie on the efficiency frontier of energy consumption as benchmarks. The other ten sectors experienced inefficiency in some two-year time periods and the productivity changes were not steady. The data envelopment analysis-based Malmquist productivity index provides a good way to measure the energy consumption and can give China's policy makers the information to promote their strategy of sustainable development.

Forecast of the efficiency confidence interval of decision-making units in data envelopment analysis

2020 ◽  
Vol 33 (02) ◽  
pp. 431-445
Author(s):  
Azarnoosh Kafi ◽  
Behrouz Daneshian ◽  
Mohsen Rostamy-Malkhalifeh ◽  
Mohsen Rostamy-Malkhalifeh
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Confidence Interval ◽  
Data Envelopment ◽  
Data Set ◽  
Interval Model ◽  
Time Period ◽  
Proposed Model ◽  
The Future ◽  
Decision Making Units

Data Envelopment Analysis (DEA) is a well-known method for calculating the efficiency of Decision-Making Units (DMUs) based on their inputs and outputs. When the data is known and in the form of an interval in a given time period, this method can calculate the efficiency interval. Unfortunately, DEA is not capable of forecasting and estimating the efficiency confidence interval of the units in the future. This article, proposes a efficiency forecasting algorithm along with 95% confidence interval to generate interval data set for the next time period. What’s more, the manager’s opinion inserts and plays its role in the proposed forecasting model. Equipped with forecasted data set and with respect to data set from previous periods, the efficiency for the future period can be forecasted. This is done by proposing a proposed model and solving it by the confidence interval method. The proposed method is then implemented on the data of an automotive industry and, it is compared with the Monte Carlo simulation methods and the interval model. Using the results, it is shown that the proposed method works better to forecast the efficiency confidence interval. Finally, the efficiency and confidence interval of 95% is calculated for the upcoming period using the proposed model.

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