The temporal stability of factors affecting driver injury severity in run-off-road crashes: A random parameters ordered probit model with heterogeneity in the means approach

2020 ◽  
Vol 144 ◽  
pp. 105677
Author(s):  
Miao Yu ◽  
Changjiang Zheng ◽  
Changxi Ma ◽  
Jinxing Shen
Keyword(s):  
Injury Severity ◽  
Temporal Stability ◽  
Probit Model ◽  
Ordered Probit ◽  
Ordered Probit Model ◽  
Random Parameters ◽  
Factors Affecting ◽  
Road Crashes ◽  
Run Off

scholarly journals Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model

2019 ◽  
Vol 16 (14) ◽  
pp. 2632 ◽  
Author(s):  
Chen ◽  
Song ◽  
Ma
Keyword(s):  
Injury Severity ◽  
Unobserved Heterogeneity ◽  
Seat Belt ◽  
Probit Model ◽  
Ordered Probit ◽  
Ordered Probit Model ◽  
Random Parameters ◽  
Factors Affecting ◽  
Bivariate Ordered Probit ◽  
Bivariate Ordered Probit Model

The existing studies on drivers’ injury severity include numerous statistical models that assess potential factors affecting the level of injury. These models should address specific concerns tailored to different crash characteristics. For rear-end crashes, potential correlation in injury severity may present between the two drivers involved in the same crash. Moreover, there may exist unobserved heterogeneity considering parameter effects, which may vary across both crashes and individuals. To address these concerns, a random parameters bivariate ordered probit model has been developed to examine factors affecting injury sustained by two drivers involved in the same rear-end crash between passenger cars. Taking both the within-crash correlation and unobserved heterogeneity into consideration, the proposed model outperforms the two separate ordered probit models with fixed parameters. The value of the correlation parameter demonstrates that there indeed exists significant correlation between two drivers’ injuries. Driver age, gender, vehicle, airbag or seat belt use, traffic flow, etc., are found to affect injury severity for both the two drivers. Some differences can also be found between the two drivers, such as the effect of light condition, crash season, crash position, etc. The approach utilized provides a possible use for dealing with similar injury severity analysis in future work.

scholarly journals Consumers’ Buying Behavior Towards Online Shopping During The Covid-19 Pandemic: An Empirical Study In Malaysia

2021 ◽  
Vol 7 (2) ◽  
pp. 1-7
Author(s):  
Nurul Sima Mohamad Shariff ◽  
Nur Hayani Izzati Abd Hamid
Keyword(s):  
Online Shopping ◽  
Probit Model ◽  
Product Variety ◽  
Marketing Strategies ◽  
Ordered Probit ◽  
Ordered Probit Model ◽  
Buying Behavior ◽  
Factors Affecting ◽  
The Relationship ◽  
Insight Into

The world has been affected by the COVID-19 outbreak recently, affecting the economy worldwide. Due to the booming of online activities, especially online shopping, this study is interested in finding the relationship between factors affecting consumers’ buying behavior on online shopping in Malaysia during the COVID-19 pandemic. The least studies related to this issue is needed in Malaysia to further understand the behavior of the consumers on online shopping. Based on available literatures, the factors of interest were trust, convenience, price, product variety and promotion on consumers’ buying behavior in Malaysia. The study employed survey procedures to collect the data, whereby online questionnaires were disseminated and recorded from a total of 335 respondents. The data was then analysed using several statistical analyses, namely pilot test, descriptive statistics and an ordered probit model.  The result from an ordered probit model indicated that convenience, product variety, trust and promotion affected the Malaysian consumers’ buying behavior during the pandemic. Only price showed an insignificant impact on online shopping. This gave the sellers insight into understanding the consumers’ buying behavior on the online platform by planning marketing strategies to fascinate more customers.

Examining the factors affecting the severity of run-off-road crashes in Abu Dhabi

2016 ◽  
Vol 43 (2) ◽  
pp. 132-138 ◽  
Author(s):  
Mohamed Shawky ◽  
Hany M. Hassan ◽  
Atef M. Garib ◽  
Hussain A. Al-Harthei
Keyword(s):  
Traffic Safety ◽  
Surface Condition ◽  
Probit Model ◽  
Abu Dhabi ◽  
Factors Affecting ◽  
Environment Factors ◽  
Crash Data ◽  
Road Crashes ◽  
Run Off ◽  
Road Type

Recently, the severity of injuries resulting from traffic crashes has been extensively investigated in numerous studies. However, the number of studies that addressed the severity of the run-off-road (ROR) crashes is relatively low. In the Emirate of Abu Dhabi (AD), approximately 22% of the total serious crashes and fatalities that occurred from 2007 to 2013 were ROR crashes. Despite these facts and the uniqueness of the composition of licensed drivers in AD (approximately 87% of them are non-Emiratis), the factors affecting the occurrence and severity of ROR crashes in AD have not been explicitly addressed in any prior studies. Therefore, this study aims to investigate the characteristics of at-fault drivers involved in ROR crashes in AD, the nature and main causes of those crashes. In this regard, conditional distribution and two-way contingency tables were developed. In addition, this study aims to identify and quantify the factors affecting the severity of ROR crashes such as driver, road, vehicle and environment factors. To achieve this goal, ordered probit model approach was employed. Crash data for a total of 3819 ROR crashes that occurred in AD were employed in the analysis. The results indicated that driver factors (carelessness, speeding, and nationality), vehicle characteristics (vehicle type), and road and environment factors (road type, crash location and road surface condition) were the significant factors influencing the severity of ROR crashes in AD. Countermeasures to improve traffic safety and reduce numbers and severity of ROR crashes in AD were discussed.

scholarly journals Exploring Risk Factors with Crash Severity on China Two-Lane Rural Roads Using a Random-Parameter Ordered Probit Model

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Shikun Xie ◽  
Xiaofeng Ji ◽  
Wenchen Yang ◽  
Rui Fang ◽  
Jingjing Hao
Keyword(s):  
Risk Factors ◽  
Injury Severity ◽  
Random Parameter ◽  
Probit Model ◽  
Ordered Probit ◽  
Ordered Probit Model ◽  
Crash Severity ◽  
Critical Factors ◽  
Traffic Crashes ◽  
Rural Roads

Understanding the factors that contribute to traffic crashes can help provide a fundamental basis to plan and develop appropriate countermeasures for road safety issues emerging in particular on two-lane rural roads. However, most of the studies have focused on urban roadways and freeway systems, and few studies have investigated the issue of heterogeneity on two-lane rural roads. The purpose of this study is to uncover the risk factors influencing crash severity on two-lane rural roads in China. A sample of 1490 traffic crashes occurring on two-lane rural roads between 2012 and 2017 was collected from the Mouding County Highway Bureau in Yunnan, China. A random-parameter ordered probit model was estimated using these data to capture underlying unobserved characteristics in personal traits, vehicle attributes, roadway conditions, environmental factors, and crash attribute. To better understand the effect of critical factors on crash severity outcome probability, an elasticity analysis was then introduced. The results show that six factors such as driver’s attribution, illegal driving behaviour, access segment, day of week, vehicle type, and crash form have a significant impact on the injury severity, and the impacts of driving behaviours, access segment, and vehicle-fixed object crashes had significant variation across observations. Besides, the correlations between critical factors and the probability of serious injury sustained in traffic crashes are identified and discussed. The local driver indicator has more positive impact on the crash severity than nonlocal driver, and nonaccess segment appears a higher probability of serious or vicious collisions. It is worth mentioning that motorcycle-involved crashes do show an obvious correlation with crash injury severity. As for crash forms, vehicle-vehicle crashes are more likely to lead to severe crash injury. Besides, high-risk driving behaviour (e.g., fatigue driving, speeding, and converse driving), weekends, and holidays are found to have significant contribution to increasing the probability of traffic crash injuries and fatalities on two-lane rural roads.

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