DEA based production planning considering technology heterogeneity with undesirable outputs

2020 ◽  
Vol 54 (2) ◽  
pp. 325-339
Author(s):  
Changyong Liang ◽  
Binyou Wang ◽  
Tao Ding ◽  
Yinchao Ma
Keyword(s):  
Data Envelopment Analysis ◽  
Production Planning ◽  
Industrial Development ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Planning Approach ◽  
Technology Heterogeneity ◽  
Using Data ◽  
Planning Problems ◽  
Decision Making Units

Many researchers have concentrated on production planning issues by using data envelopment analysis (DEA). However, the assumption made by existing approaches that all decision making units (DMUs) are equipped with the same level of production technology is not realistic. Additionally, with the development in the society, environmental factors have come to play important roles in the production process as well. Thus, undesirable outputs should be considered in production planning problems. Therefore, this paper considers the technology heterogeneity factors and undesirable outputs using the data envelopment analysis-based production planning approach. Two examples containing a numerical example that compare with other method and a real sample that concerns the industrial development of 30 provinces in China are used to validate the applicability of our approach.

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 Performance Evaluation of Fishery Enterprises Using Data Envelopment Analysis—A Malmquist Model

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 469
Author(s):  
Chia-Nan Wang ◽  
Thi-Ly Nguyen ◽  
Thanh-Tuan Dang ◽  
Thi-Hong Bui
Keyword(s):  
Performance Evaluation ◽  
Data Envelopment Analysis ◽  
Technological Progress ◽  
Data Envelopment ◽  
Domestic Economy ◽  
Factor Productivity ◽  
Sales Revenue ◽  
Business Efficiency ◽  
Using Data ◽  
Decision Making Units

In Vietnam, fishing is a crucial source of nutrition and employment, which not only affects the development of the domestic economy but is also closely related to exports, heavily influencing the economy and foreign exchange. However, the Vietnamese fishery sector has been facing many challenges in innovating production technology, improving product quality, and expanding markets. Hence, the fishery enterprises need to find solutions to increase labor productivity and enhance competitiveness while minimizing difficulties. This study implemented a performance evaluation from 2015 to 2018 of 17 fishery businesses, in decision making units (DMUs), in Vietnam by applying data envelopment analysis, namely the Malmquist model. The objective of the paper is to provide a general overview of the fishery sector in Vietnam through technical efficiency, technological progress, and the total factor productivity in the four-year period. The variables used in the model include total assets, equity, total liabilities, cost of sales, revenue, and profit. The results of the paper show that Investment Commerce Fisheries Corporation (DMU10) and Hoang Long Group (DMU8) exhibited the best performances. This paper offers a valuable reference to improve the business efficiency of Vietnamese fishery enterprises and could be a useful reference for related industries.

scholarly journals Evaluating Efficiency of Waqf Institutions: An Intermediation Approach Using Data Envelopment Analysis (DEA)

2019 ◽  
Vol 2 (2) ◽  
pp. 82-89
Author(s):  
Nor Tasik Misbahrudin
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Wealth Distribution ◽  
Scale Efficiency ◽  
Optimum Level ◽  
Data Envelopment ◽  
Input And Output ◽  
Distribution State ◽  
Using Data ◽  
Decision Making Units

Waqf is a voluntary charity that cannot be disposed of and the ownership cannot be transferred once it is declared as waqf assets. Waqf institutions play an important role in helping the development of Muslims ummah through wealth distribution. State Islamic Religious Councils (SIRCs) in Malaysia are the sole trustee that manage and develop waqf assets. Based on selected input and output, the intermediary approach assumes that cash waqf received as output while total expenditure of SIRCs as input. Under this approach SIRCs act as intermediary between waqif (giver) and beneficiaries. Thus, this paper attempts to analyze the efficiency of waqf institutions in Malaysia by using Data Envelopment Analysis (DEA) method under output-orientation using Variable Return to Scale (VRS) assumptions. Four SIRCs were selected as decision making units (DMU) for the period of 2011 to 2015. The result indicates that changes in average technical efficiency for every year is contributed by both pure technical and scale. However, inefficiency of Malaysian waqf institutions is mostly contributed by pure technical efficiency aspects rather than scale. 2012 showed the highest average technical efficiency with 73.9% as most of the institutions operated in optimum level of input to produce output. Thus, the result suggests that both technical and scale efficiency should be improved to achieve the most efficient and productive level of performance in order to fulfill objectives of the institutions as an intermediary between waqif and beneficiaries.

scholarly journals Evaluation of Car Performances Using Data Envelopment Analysis

2018 ◽  
Vol 22 ◽  
pp. 01051
Author(s):  
Yunus GÜRAL ◽  
Ayşe Turan BUĞATEKİN
Keyword(s):  
Data Envelopment Analysis ◽  
Maximum Speed ◽  
Data Envelopment ◽  
Automotive Sector ◽  
Nonparametric Method ◽  
Maximum Torque ◽  
Acceleration Time ◽  
Input Variables ◽  
Using Data ◽  
Decision Making Units

Data Envelopment Analysis (DEA) is a nonparametric method used to examine the relative efficiencies of Decision Making Units (DMUs) on conditions where there are multiple inputs and multiple outputs. As in all sectors, it is very important for the automotive sector to operate effectively. Therefore, it is also important to measure the efficiency and find the source of the inefficiency. In this study, the performances of the DMU of the automobiles will examine using Data Envelopment Analysis. In this direction, it is aimed to assist consumers in purchasing by calculating the relative efficiencies of automobile models, determining effective and ineffective DMUs according to the wishes of the consumers. Sales price and fuel consumption are determined as input variables; maximum speed, cylinder volume, horsepower, maximum torque, luggage volume, acceleration time from 0 to 100 km are determined as output variables.

A Common Set of Weights for Ranking Decision-Making Units with Undesirable Outputs: A Double Frontiers Data Envelopment Analysis Approach

2018 ◽  
Vol 35 (06) ◽  
pp. 1850039 ◽  
Author(s):  
Lei Chen ◽  
Fei-Mei Wu ◽  
Feng Feng ◽  
Fujun Lai ◽  
Ying-Ming Wang
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Optimal Solution ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Discrimination Power ◽  
Efficiency Optimization ◽  
Common Set Of Weights ◽  
Desirable And Undesirable Outputs ◽  
Decision Making Units

Major drawbacks of the traditional data envelopment analysis (DEA) method include selecting optimal weights in a flexible manner, lacking adequate discrimination power for efficient decision-making units, and considering only desirable outputs. By introducing the concept of global efficiency optimization, this study proposed a double frontiers DEA approach with undesirable outputs to generate a common set of weights for evaluating all decision-making units from both the optimistic and pessimistic perspectives. For a unique optimal solution, compromise models for individual efficiency optimization were developed as a secondary goal. Finally, as an illustration, the models were applied to evaluate the energy efficiency of the Chinese regional economy. The results showed that the proposed approach could improve discrimination power and obtain a fair result in a case where both desirable and undesirable outputs exist.

scholarly journals New Approach in Fixed Resource Allocation and Target Setting Using Data Envelopment Analysis with Common Set of Weights

Complexity ◽  
2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Marzieh Ghasemi ◽  
Mohammad Reza Mozaffari ◽  
Farhad Hosseinzadeh Lotfi ◽  
Mohsen Rostamy malkhalifeh ◽  
Mohammad Hasan Behzadi
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Target Setting ◽  
New Approach ◽  
Common Set Of Weights ◽  
Programming Techniques ◽  
Using Data ◽  
Decision Making Units

One of the mathematical programming techniques is data envelopment analysis (DEA), which is used for evaluating the efficiency of a set of similar decision-making units (DMUs). Fixed resource allocation and target setting with the help of DEA is a subject that has gained much attention from researchers. A new model was proposed by determining a common set of weights (CSW). All DMUs were involved with the aim of achieving higher efficiency in every DMU after the procedure. The minimum resources and targets allocated to each DMU were commensurate to the efficiency of that DMU and the share of DMU in the input resources and the output productions. To examine the proposed method, other methods in the DEA literature were examined as well, and then, the efficiency of the method was demonstrated through a numerical example.

scholarly journals Dimension-Specific Efficiency Measurement Using Data Envelopment Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Hongjun Zhang ◽  
Youliang Zhang ◽  
Rui Zhang
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
The Other ◽  
Data Envelopment ◽  
Input Output ◽  
Single Dimension ◽  
Measuring Efficiency ◽  
Using Data ◽  
The City ◽  
Decision Making Units

Data envelopment analysis (DEA) is a powerful tool for evaluating and improving the performance of a set of decision-making units (DMUs). Empirically, there are usually many DMUs exhibiting “efficient” status in multi-input multioutput situations. However, it is not appropriate to assert that all efficient DMUs have equivalent performances. Actually, a DMU can be evaluated to be efficient as long as it performs best in a single dimension. This paper argues that an efficient DMU of a particular input-output proportion has its own specialty and may also perform poorly in some dimensions. Two DEA-based approaches are proposed to measure the dimension-specific efficiency of DMUs. One is measuring efficiency in multiplier-form by further processing the original multiplier DEA model. The other is calculating efficiency in envelopment-form by comparing with an ideal DMU. The proposed approaches are applied to 26 supermarkets in the city of Nanjing, China, which have provided new insights on efficiency for the managers.

Slacks-Based Efficiency Measurements with Undesirable Outputs in Data Envelopment Analysis

2014 ◽  
Vol 16 (04) ◽  
pp. 1005-1021 ◽  
Author(s):  
Jie Wu ◽  
Xiang Lu ◽  
Dong Guo ◽  
Liang Liang
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Production Process ◽  
Environmental Performance ◽  
Decision Makers ◽  
European Countries ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Theoretical Justification ◽  
Decision Making Units

Data envelopment analysis (DEA) has recently gained great popularity in modeling environmental performance because it provides condensed information to decision makers when the production process includes undesirable outputs. In this paper, we develop a new slacks-based efficiency measurement for modeling environmental performance using the environmental DEA technology. The proposed index has more theoretical justification, and distinguishes among different decision making units (DMUs) better in practice. Then we further extend it to the nonoriented index with double aim of increasing desirable outputs and reducing undesirable outputs. Finally, we calculate the index for each of 25 OECD European countries in a model of CO2 emission performance from 2007 to 2009 and the results obtained are presented.

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