Estimating Efficient Marginal Resource Levels Using Data Envelopment Analysis

1998 ◽  
Vol 15 (2) ◽  
pp. 29-52 ◽  
Author(s):  
Emmanuel Thanassoulis
2019 ◽  
Author(s):  
Jeffrey A. Shero ◽  
Sara Ann Hart

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.


Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 469
Author(s):  
Chia-Nan Wang ◽  
Thi-Ly Nguyen ◽  
Thanh-Tuan Dang ◽  
Thi-Hong Bui

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.


SAGE Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 215824402198925
Author(s):  
Isidoro Guzmán-Raja ◽  
Manuela Guzmán-Raja

Professional football clubs have a special characteristic not shared by other types of companies: their sport performance (on the field) is important, in addition to their financial performance (off the field). The aim of this paper is to calculate an efficiency measure using a model that combines performance (sport and economic) based on data envelopment analysis (DEA). The main factors affecting teams’ efficiency levels are investigated using cluster analysis. For a sample of Spanish football clubs, the findings indicate that clubs achieved a relatively high efficiency level for the period studied, and that the oldest teams with the most assets had the highest efficiency scores. These results could help club managers to improve the performance of their teams.


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