scholarly journals Evaluating 3D Printers Using Data Envelopment Analysis

2021 ◽  
Vol 11 (9) ◽  
pp. 4209
Author(s):  
Theodore Papatheodorou ◽  
John Giannatsis ◽  
Vassilis Dedoussis
Keyword(s):  
Data Envelopment Analysis ◽  
Fused Deposition Modeling ◽  
Production Systems ◽  
Manufacturing Sector ◽  
Data Envelopment ◽  
Programming Technique ◽  
Fused Deposition ◽  
Efficiency Performance ◽  
3D Printers ◽  
Using Data

Data Envelopment Analysis (DEA) is an established powerful mathematical programming technique, which has been employed quite extensively for assessing the efficiency/performance of various physical or virtual and simple or complex production systems, as well as of consumer and industrial products and technologies. The purpose of the present study is to investigate whether DEA may be employed for evaluating the technical efficiency/performance of 3D printers, an advanced manufacturing technology of increasing importance for the manufacturing sector. For this purpose, a representative sample of 3D printers based on Fused Deposition Modeling technology is examined. The technical factors/parameters of 3D printers, which are incorporated in the DEA, are investigated and discussed in detail. DEA evaluation results compare favorably with relevant benchmarks from experts, indicating that the suggested DEA technique in conjunction with technical and expert evaluation could be employed for evaluating the performance of a highly technological system, such as the 3D printer.

Modeling Efficiency Performance of Malaysian Commercial Banks Using Data Envelopment Analysis

2018 ◽  
Vol 24 (6) ◽  
pp. 4612-4618
Author(s):  
Norsyuhada Johan ◽  
Zalina Zahid ◽  
Siti Aida Sheikh Hussin
Keyword(s):  
Data Envelopment Analysis ◽  
Commercial Banks ◽  
Data Envelopment ◽  
Efficiency Performance ◽  
Using Data

scholarly journals DINAMIKA TOTAL FACTOR PRODUCTIVITY INDUSTRI BESAR DAN SEDANG INDONESIA

2014 ◽  
Vol 16 (3) ◽  
pp. 277-308
Author(s):  
Ndari Surjaningsih ◽  
Bayu Panji Permono
Keyword(s):  
Data Envelopment Analysis ◽  
Total Factor Productivity ◽  
Technical Change ◽  
Manufacturing Sector ◽  
Jel Classification ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Catching Up ◽  
Using Data

This paper calculates and decomposes the Total Factor Productivity (TFP) for large and medium scale industry in Indonesia covering the period of 2000-2009. By using Data Envelopment Analysis (DEA)  method, the result shows there is a shift of the supporting factors on the growth of TFP on manufacturing sector within the 2 (two) sample period. In the period of 2000-2004, efficiency change becomes the main contributor on the growth of TFP. Whereas in the period of 2005-2009, technical change becomes the main supporting factor of TFP,however it goes along with the growth of negative efficiency change or the decline of the company’s catching-up effect ability to adapt with the more advance technology. The grouping of the sample across subsectors, technical change and also efficiency change shows the declining amount of manufacture industry with superior productivity. Furthermore, the number of low and weakening catching-up industry is increasing.  Keywords: Indonesian manufacturing, total factor productivity, technical change, efficiency change, economic scale change, Data Envelopment Analysis JEL Classification: L6, M11

Efficiency analysis of sugarcane production systems in Thailand using data envelopment analysis

2019 ◽  
Vol 238 ◽  
pp. 117877 ◽  
Author(s):  
Asmat Ullah ◽  
Thapat Silalertruksa ◽  
Patcharaporn Pongpat ◽  
Shabbir H. Gheewala
Keyword(s):  
Data Envelopment Analysis ◽  
Production Systems ◽  
Efficiency Analysis ◽  
Data Envelopment ◽  
Sugarcane Production ◽  
Using Data

scholarly journals ANALISIS KINERJA INDUSTRI MANUFAKTUR DI INDONESIA

2017 ◽  
Vol 17 (1) ◽  
pp. 183
Author(s):  
Etty Puji Lestari ◽  
Isnina WSU
Keyword(s):  
Data Envelopment Analysis ◽  
Market Share ◽  
Manufacturing Industry ◽  
Manufacturing Sector ◽  
Government Policies ◽  
Data Envelopment ◽  
Industry Development ◽  
Industry Sector ◽  
Using Data ◽  
Efficiency And Productivity

The problems on the manufacturing industry in Indonesia, among others, the disparity level of efficiency and productivity of each sub-sector of the manufacturing industry in Indonesian. This occurs due to the imbalance in the structure and dominant market share for some particular type of business in each sub-sector is in the manufacturing sector. The study will analyze the performance of the manufacturing industry in Indonesia using Data Envelopment Analysis. The study states that there is a difference of efficiency at every level of the industry. Therefore, government policies relating to industry development is absolutely necessary to improve the performance of the industry sector.

scholarly journals ANALISIS EFISIENSI BANK PEMBIAYAAN RAKYAT SYARIAH (BPRS) DI JAWA TIMUR MENGGUNAKAN DATA ENVELOPMENT ANALYSIS (DEA) PERIODE 2012-2018

2020 ◽  
Vol 7 (2) ◽  
pp. 294
Author(s):  
Nafilatul Khusnah ◽  
Irham Zaki ◽  
Lina Nugraha Rani
Keyword(s):  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Banking Sector ◽  
Performance Data ◽  
Maximum Output ◽  
Data Envelopment ◽  
Fixed Assets ◽  
Efficiency Performance ◽  
Efficient Level ◽  
Using Data

Efficiency is needed by Islamic Rural Bank (BPRS)to facing rivalry in the banking sector. Efficiency can show the performance of BPRS and make BPRS more productive. This study measures the efficiency of Islamic Rural Banks (BPRS) in East Jawa using data envelopment analysis (DEA). DEA is a non-parametric and deterministic methodology for determining relative efficiency. This study used the intermediation approach and output orientation to measure the efficiency of BPRS. Inputs in this study are deposits, labor, and fixed assets. Outputs in this study are financing and other income. The result shows that the inefficiency exists in the BPRS in East Java. From 21 BPRS, which were used as a sample, 17 BPRS are not efficient technically. The inefficiency of BPRS causes BPRS still can not manage its inputs optimally to producing maximum output. To achieve an efficient level, BPRS needs to increase its output and reduce its input.Keywords: Islamic Rural Banks (BPRS), Efficiency, Performance, Data Envelopment Analysis (DEA)

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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