scholarly journals Evaluation of Decision-making Units in Reducing Traffic Accidents Using Data Envelopment Analysis

2020 ◽  
Vol 5 (2) ◽  
pp. 105-114
Author(s):  
Mohammad Reza Omidi ◽  
◽  
Nabi Omidi ◽  
Asad Mahmoudian Azar Sharabiani ◽  
◽  
...  
Keyword(s):  
Data Envelopment Analysis ◽  
Traffic Accidents ◽  
Returns To Scale ◽  
Economic Consequences ◽  
Type Model ◽  
Fars Province ◽  
Data Envelopment ◽  
Variable Model ◽  
Traffic Police ◽  
Using Data

Background: Road accidents are one of the most important causes of death and severe bodily injuries and financial damages, and its social, cultural, and economic consequences have severely threatened human societies. The purpose of this study was to use Data Envelopment Analysis (DEA) to measure the efficiency of provincial traffic police in reducing accidents in 2018 and determining the amount of optimal input resources of each provincial unit. Materials and Methods: The model used in this research had three inputs, including the level of equipment at the disposal, the level of the approved provincial budget, and the level of manpower at the disposal. It also had two outputs, including the score of reduction of casualties and the score of reduction of deaths in traffic accidents. The “returns to scale” was considered as a variable model, and the input model was an axial-type model. The DEAP software was used for data analysis. Results: The highest decrease in deaths in traffic accidents (in 2018) was related to Fars Province with 119 people, and the highest decrease in the number of injured cases was related to Khorasan Razavi Province with 1495 people. The RAHVAR Police (Traffic Police of Iran) in Tehran Province had the highest level of input resources, including manpower, equipment, and approved budget. Performance measurement for 2018 showed that out of 31 provinces studied, 10 provinces had a good performance and 21 provinces had acted inefficiently. The research results showed that the proper allocation of resources could push all units to the brink of efficiency. Conclusion: The trend of accidents in Iran is declining. Most of the RAHVAR Police units operate at an inefficient level, which by increasing their efficiency, the number of accidents can be reduced with a greater slope.

scholarly journals Pengukuran Efisiensi Kinerja Sekolah Dasar lewat Model Data Envelopment Analysis

2017 ◽  
Vol 36 (2) ◽  
Author(s):  
Siti Fatimah ◽  
Umi Mahmudah
Keyword(s):  
Elementary Schools ◽  
Data Envelopment Analysis ◽  
Parametric Method ◽  
Returns To Scale ◽  
Scale Model ◽  
Data Envelopment ◽  
Public Elementary Schools ◽  
Crs Model ◽  
Using Data ◽  
Constant Returns To Scale

This study aims to measure the performance efficiency of elementary schools in Special Capital Region of Jakarta, especially Central Jakarta district in the period 2014/2015 by using data envelopment analysis (DEA) approach. DEA is a non-parametric method to measure efficiency of decision making units (DMUs). DEA compares several homogeneous DMUs based on a number of inputs to produce the expected outputs. This study uses descriptive method using DMU as many as 103 public elementary schools that are A-accredited with three inputs and four outputs. Data is analyzed using DEAP version 2.1 application by comparing CRS (Constant Returns to Scale) model and VRS (Variable Returns to Scale) model. Results show that: 1) in CRS model, there are 8 public elementary schools (7.77 percent) have efficient performances while in VRS model there are 14 public elementary schools (13.59 percent) have efficient performances; 2) VRS model is better than CRS model in measuring the efficiency performance of public elementary schools in Central Jakarta.

scholarly journals Measuring Tourism Efficiency of European Countries by Using Data Envelopment Analysis

2017 ◽  
Vol 13 (10) ◽  
pp. 31 ◽  
Author(s):  
Halenur Soysal-Kurt
Keyword(s):  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Returns To Scale ◽  
Tourism Industry ◽  
European Countries ◽  
Data Envelopment ◽  
Micro Level ◽  
Input Variables ◽  
Using Data ◽  
Constant Returns To Scale

This study aims to measure relative efficiency of 29 European countries with the data of the year 2013 using input-oriented and constant returns to scale Data Envelopment Analysis and to offer improvement suggestions for the countries found inefficient based on their measured relative efficiency scores. Three input and three output variables are used to assess relative performances of the countries. In this study, tourism expenses, number of employees and number of beds are used as input variables; tourism receipts, tourist arrivals and number of nights spent are used as output variables. As the result of the analysis, 16 countries are found relatively efficient and 13 countries are found relatively inefficient. This study is one of the few publications within the scope of European countries based on data envelopment analysis. Unlike most researches evaluating the efficiency of tourism establishments at the micro level, this paper is thought to contribute to the related literature as it evaluates relative efficiency of the countries at the macro level for tourism industry. Considering the variables used in the analysis, it is expected to give ideas to relatively inefficient European countries on efficiency improvement.

scholarly journals EVALUATION OF PLASTERING CREW PERFORMANCE IN BUILDING PROJECTS USING DATA ENVELOPMENT ANALYSIS

2014 ◽  
Vol 22 (6) ◽  
pp. 926-940 ◽  
Author(s):  
Ibrahim Halil GEREK ◽  
Ercan ERDIS ◽  
Gulgun MISTIKOGLU ◽  
Mumtaz A. USMEN
Keyword(s):  
Data Envelopment Analysis ◽  
Management Practices ◽  
Research Question ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Building Projects ◽  
Unit Costs ◽  
Using Data ◽  
A Company ◽  
Variable Returns To Scale

The research question addressed in this study was how the performance of construction crews working in a certain project or locality could be evaluated, ranked and improved. To develop and demonstrate the relevant framework, data envelopment analysis (DEA) was applied to establish the relative efficiency of plastering crews working in building projects located in different cities around Turkey. Data were collected from 40 crews of varying characteristics, and their technical efficiency scores were computed using the Banker, Charnes and Cooper (BCC) model, which is based on variable returns-to-scale (VRS). The model yields efficiency scores that range between 0 and 1, and a company or crew is considered efficient if its score is 1.0 (100%). Efficient and inefficient crews were identified and ranked on this basis in the study. Cross tabulation analyses were subsequently conducted to gain further insights into the relationships between the efficiency scores and input factors of numbers of skilled and unskilled laborers, daily labor unit costs, work hours, average age of crew members, total crew experience, plastering location, plastering technique, and plaster type. No discernible relationship could be identified between the efficiency scores and productivity outputs of the crews. It was found that plastering technique, plastering location, and total crew experience had a significant association with crew efficiency. Efficiency improvement strategies identified included training, hiring experienced plasterers, adopting more advanced plastering technology, implementing better jobsite management practices, and enhancing workers’ knowledge, skills and attitude towards productivity and quality.

Measurement of campaign efficiency in the 2020 elections using data envelopment analysis

2020 ◽  
pp. 5-15
Author(s):  
Tatiana Bencová
Keyword(s):  
Data Envelopment Analysis ◽  
Political Parties ◽  
Production System ◽  
Returns To Scale ◽  
The Political ◽  
Data Envelopment ◽  
Political Campaign ◽  
Dea Efficiency ◽  
The Government ◽  
Using Data

Data envelopment analysis (DEA) is used to analyze the efficiency of political parties campaign spending. DEA is a method to estimate a relative efficiency of decision making units (DMUs) performing similar tasks in the production system that consumes multiple inputs to produce multiple outputs. In this research paper DMUs represent 24 political parties and the production system represents the election campaign 2020. The input variable selected for the study is the cost for the political campaign. The output variables are the number of votes that the political party received in the election, number of points for the election program and the third output is the number of members of the government. For the efficiency analysis was used the BCC output oriented model which assumes variable returns to scale. The aim of the paper is twofold. The first task is to analyze input and output variables of individual political parties. The second aim is to point out and interpret the results of DEA analysis.Key words: Elections, Data Envelopment Analysis (DEA), Efficiency, Political Campaign

scholarly journals Estimation of The Efficiency of Different Academic Departments Using Data Envelopment Analysis: A Study in an Iranian Medical University

2019 ◽  
Author(s):  
R Askari ◽  
S Rafiei ◽  
M Ranjbar ◽  
M Pakdaman ◽  
F Sepase
Keyword(s):  
Data Envelopment Analysis ◽  
Returns To Scale ◽  
Academic Departments ◽  
Educational Systems ◽  
Data Envelopment ◽  
Reference Groups ◽  
Cross Sectional ◽  
Analysis Technique ◽  
Using Data ◽  
Constant Returns To Scale

Introduction: In every country, educational systems are regarded as the axes of development. Therefore, evaluating different academic departments as the main parts of educational systems is one of the most important responsibilities for university managers and authorities This study aimed at evaluating educational performance of all departments at the School of Health, a University of Medical Sciences using Data Envelopment Analysis technique in a time period of 2012-2015. Methods: This descriptive, cross-sectional study evaluated the performance of the School of Health departments from 2012 to 2015 using Data Envelopment Analysis technique and Deap version 2.1. Results: The study findings revealed that 57% of the academic departments were efficient and had constant returns to scale (CRS) while others (43%) had decreasing returns to scale (DRS). The Departments of Health Care Management, Nutrition, and Environmental Health were mentioned as reference groups for those inefficient ones. Conclusion: Improving the quality of universities' performance depends greatly on competent and well-organized academic departments. Thus inefficient departments should benchmark reference groups to increase their output and promote the 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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