Performance Measurement Using Data Envelopment Analysis (DEA)

2014 ◽  
pp. 15-47 ◽  
Author(s):  
Yasar A. Ozcan
Keyword(s):  
Data Envelopment Analysis ◽  
Performance Measurement ◽  
Data Envelopment ◽  
Using Data

Performance Measurement of Indian Banks using Data Envelopment Analysis

2014 ◽  
Vol 2 (3) ◽  
Author(s):  
Nikita Agarwal ◽  
Banhi Guha ◽  
Avijan Dutta ◽  
Gautam Bandyopadhyay
Keyword(s):  
Data Envelopment Analysis ◽  
Performance Measurement ◽  
Data Envelopment ◽  
Using Data ◽  
Indian Banks

scholarly journals Sustainable Agri-Food Supply Chain Performance Measurement Model for GMO and Non-GMO Using Data Envelopment Analysis Method

2019 ◽  
Vol 9 (6) ◽  
pp. 1199
Author(s):  
Virda Saputri ◽  
Wahyudi Sutopo ◽  
Muhammad Hisjam ◽  
Azanizawati Ma’aram
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Performance Measurement ◽  
Food Supply ◽  
Measurement Model ◽  
Assessment Method ◽  
Supply Chain Performance ◽  
Data Envelopment ◽  
Food Supply Chain ◽  
Using Data

The increase in food demand in Indonesia is one of the consequences of the imbalance between population growth and declining food products. One of alternative technologies that can be used in plant breeding programs to increase agricultural production, in order to meet food demands, is genetically modified organism (GMO) technology. This technology presents a lot of pros and cons among the public-related impacts that will be accepted by consumers. The purpose of this study was to determine the level of sustainability between GMO and non-GMO foods. The performance measurement model for GMO and non-GMO foods was considered according to the seven issues of sustainability that represented environmental, social, and economic aspects. The assessment method was conducted by using Adjusted Profit (AP) with Total Price Recovery (TPR) indicators and Total Factor Productivity (TFP) by utilizing the Data Envelopment Analysis (DEA) Method. Assessments made on each supply chain component included agriculture, processing, and transport to wholesalers/retailers. This study used numerical examples of rice production in Indonesia. The research results found that the performance of non-GMO rice chain is better than GMO rice. It indicates that non-GMO rice is more sustainable. The results show that the proposed model can be applied to measure the sustainability of GMO and Non-GMO agri-food supply chain performance.

Data Envelopment Analysis (DEA) in the Psychological Sciences

2019 ◽  
Author(s):  
Jeffrey A. Shero ◽  
Sara Ann Hart
Keyword(s):  
Data Envelopment Analysis ◽  
Aggressive Behavior ◽  
Personality Traits ◽  
Educational Administration ◽  
Latent Variable ◽  
Organizational Management ◽  
Data Envelopment ◽  
Targeted Interventions ◽  
Component Skills ◽  
Using Data

Using methods like linear regression or latent variable models, researchers are often interested in maximizing explained variance and identifying the importance of specific variables within their models. These models are useful for understanding general ideas and trends, but often give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method with roots in organizational management that make such insights possible. Unlike models mentioned above, DEA does not explain variance. Instead, it explains how efficiently an individual utilizes their inputs to produce outputs, and identifies which input is not being utilized optimally. This paper provides readers with a brief history and past usages of DEA from organizational management, public health, and educational administration fields, while also describing the underlying math and processes behind said model. This paper then extends the usage of this method into the psychology field using two separate studies. First, using data from the Project KIDS dataset, DEA is demonstrated using a simple view of reading framework identifying individual efficiency levels in using reading-based skills to achieve reading comprehension, determining which skills are being underutilized, and classifying and comparing new subsets of readers. Three new subsets of readers were identified using this method, with direct implications leading to more targeted interventions. Second, DEA was used to measure individuals’ efficiency in regulating aggressive behavior given specific personality traits or related skills. This study found that despite comparable levels of component skills and personality traits, significant differences were found in efficiency to regulate aggressive behavior on the basis of gender and feelings of provocation.

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