Evaluation of Decision-making Units in Reducing Traffic Accidents Using Data Envelopment Analysis (original) (raw)
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A Perspective Analysis of Road Accident Using Data Envelopment Analysis
Journal of the Society of Automotive Engineers Malaysia, 2021
The rapid growth of the economy has led to the increased in road traffic networks and had indirectly led to the rapid cases of road accidents in Malaysia. Road accidents are one of the main contributors to human deaths in Malaysia. This paper attempts to measure road accidents in Malaysia by looking at the road accidents of 13 states and a federal territory. The aim is to measure the numbers and causes of road accidents by using Data Envelopment Analysis (DEA). Due to that, the input and output are identified to compute the efficiency level of road accidents. Apart of that, the trends in the number of road accidents in Malaysia is also depicted. For this study, the data from 2008 to 2011 for each Decision Making Unit (DMU) is analyzed. The result shows that the efficiency level did not determined by the number of vehicles on the road and the size of the state but it is determined by the utilization of resources by the authorities. It shows that managing input is important when the level of efficiency for the Decision-Making Unit (DMU) for the output is concerned. The outcome of this study supports the government measures to level up road maintenance in order to improve the efficiency level and curb the numbers of road accidents in Malaysia.
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The intense economic growth experienced by Brazil in recent decades and its consequent explosive motorization process have generated an undesirable impact: the increasing and unbroken trend in road traffic fatalities. In order to contribute to road safety diagnosis, this study presents a research on two main available indicators in Brazil: mortality rate (represented by fatalities per inhabitants); and fatality rate (represented by two sub-indicators, i.e., fatalities per vehicle and fatalities per vehicle kilometers traveled). These indicators were aggregated into a composite indicator (CI) through a multiple layer data envelopment analysis CI model (ML DEA-CI), in which the optimum combination of indicators' weights is searched for each decision-making unit (DMU), in this case, the 27 Brazilian states (BR-27). The composite indicator represents the road safety performance on which a ranking of states can be made. As a result, valuable differences associated to DMU's socioeconomic attributes were outlined after calibrating the model.
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Road safety performance indicators (SPI) have recently been proposed as a useful instrument in comparing countries on the performance of different risk aspects of their road safety system. In this respect, SPIs should be actionable, i.e. they should provide clear directions for policymakers about what action is needed and which priorities should be set in order to improve a country's road safety level in the most efficient way.
DAAAM Proceedings, 2019
This paper deals with the survey and assessment of traffic safety in Federation of Bosnia and Herzegovina (F B&H) and compares it to the traffic safety in Republic of Srpska (RS), Brcko District (BD) and EU countries. The assessment and comparison of traffic safety in this study is based on data collected from various referential statistical sources, the same being related to the period 2015-2016. For the analysis, a Data Envelopment Analysis (DEA) method has been selected, which enables a comparative assessment of the traffic safety of certain regions (cities, cantons, states) based on multiple indicators, such as number of traffic accidents, number of deaths, number of seriously injured compared to the number of inhabitants, road lengths, etc. DEA, as an objective and nonparametric method, does not favor any of the selected criteria, but provides equal chances to all units whose performances are being evaluated. Paper gives a brief theoretical overview of DEA method, brief survey of literature related to application of DEA method in analysis of traffic safety, data and sources of collected data, as well as developed DEA model. Conducted analysis enabled estimation of traffic safety efficacy, identification of countries/entities/districts with traffic safety not at the level of the relatively most secure countries, and estimation of possible improvements related to reduction of the total number of traffic accidents and number of people died in traffic accidents, for all countries/entities/districts. Based on the conducted analysis it can be concluded that there is a significant difference in the efficiency of traffic safety in EU countries. At the level of all EU countries, including B&H (F B&H, RS and BD), the total number of traffic accidents can be reduced by 458.142,9 or by 42% per year, while the total number of people died can be reduced by 10.674,42 or by 38% per year. The analysis has shown that the highest level of traffic safety is in Denmark, Finland, the Netherlands and Sweden, while traffic safety is the lowest in F B&H, Romania, RS and BD.
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Journal of Transportation Engineering, 2009
Data envelopment analysis ͑DEA͒ is a mathematical method based on production theory and the principles of linear programming. It enables one to assess how efficiently a firm, organization, agency, or such other unit uses the resources available ͑inputs͒ to generate a set of outputs relative to other units in the data set. Recent papers by different writers present different applications of DEA in the transportation engineering domain. All of these papers are published in transportation journals. These papers are mainly aimed at addressing the transportation-related issues and thus do not focus too much on the DEA concept itself. It can be asserted that DEA is very likely to be used more and more in the transportation engineering domain. Given this, there is a need for the transportation professionals to fully understand the DEA concept. It is essential for such a community to identify cases where the application of this innovative and powerful method can be useful to help the decision-making process, to accurately apply DEA in a particular setting, to derive meaningful conclusions from the obtained results, and to acknowledge the limitations of DEA in certain cases so as to approach the results with caution. The purpose of this paper is to illustrate to the civil engineering, more specifically to the transportation engineering community the use of this powerful approach in performing comparative performance measurement. Within this context, this paper will address a transportation-related problem by using the DEA approach. Different from the other papers containing transportation-related DEA applications ͑as mentioned above͒, this paper will discuss, in detail, the steps that need to be taken to generate the DEA model and solve it.
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The data envelopment analysis (DEA) based Malmquist productivity index measures the productivity change over time. It can be further decomposed into two components: the change in efficiency and the technical change. In this study, a specific road safety outputoriented DEA-based Malmquist productivity index is introduced to assess the changes in road safety performance of 26 EU countries from 2000 to 2007. The results show a considerable road safety progress in most of the member states during this period. The decomposition into the two components further reveals that the bulk of the improvement was attained through the adoption of new road safety technologies or strategies, i.e., the technical change, rather than through the relatively inefficient countries catching up with those efficient ones, known as the efficiency change.
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Trauma management (TM) concerned with the medical treatment of injuries resulting from road crashes is considered key in avoiding preventable death and disability and in reducing the severity and suffering caused by the injury. To understand the concept of TM better and to evaluate the level of overall performance in different countries, a hierarchical set of TM indicators is developed and subsequently combined into an overall index. Data envelopment analysis (DEA) is explored, and a multiple-layer DEA model is developed to reflect the hierarchical structure of the indicators. With 17 TM performance indicators related to emergency medical services and permanent medical facilities, the most optimal TM index score is computed for 21 European countries. The weights assigned to the indicators of each layer of the hierarchy are deduced, to provide insight into the critical aspects of the prevalent TM system. In addition, country groups in accordance with the index score are evaluated, an...
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