Road safety risk evaluation and target setting using data envelopment analysis and its extensions

2012 ◽  
Vol 48 ◽  
pp. 430-441 ◽  
Author(s):  
Yongjun Shen ◽  
Elke Hermans ◽  
Tom Brijs ◽  
Geert Wets ◽  
Koen Vanhoof
Keyword(s):  
Data Envelopment Analysis ◽  
Road Safety ◽  
Risk Evaluation ◽  
Data Envelopment ◽  
Target Setting ◽  
Safety Risk ◽  
Using Data

scholarly journals Road Safety Risk Evaluation Using GIS-Based Data Envelopment Analysis—Artificial Neural Networks Approach

2017 ◽  
Vol 7 (9) ◽  
pp. 886 ◽  
Author(s):  
Syyed Shah ◽  
Tom Brijs ◽  
Naveed Ahmad ◽  
Ali Pirdavani ◽  
Yongjun Shen ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Data Envelopment Analysis ◽  
Road Safety ◽  
Risk Evaluation ◽  
Data Envelopment ◽  
Safety Risk ◽  
Artificial Neural

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.

A novel dynamic credit risk evaluation method using data envelopment analysis with common weights and combination of multi-attribute decision-making methods

2021 ◽  
Vol 129 ◽  
pp. 105223
Author(s):  
Jalil Heidary Dahooie ◽  
Seyed Hossein Razavi Hajiagha ◽  
Shima Farazmehr ◽  
Edmundas Kazimieras Zavadskas ◽  
Jurgita Antucheviciene
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Credit Risk ◽  
Risk Evaluation ◽  
Evaluation Method ◽  
Data Envelopment ◽  
Common Weights ◽  
Multi Attribute Decision Making ◽  
Using Data

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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