Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters 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.

Estimation urban railway demand in Yogyakarta using Bivariate Ordered Probit Model

The urban railway system is believed to solve transportation problems caused by the high growth of private vehicles and urbanization. This study is going to analyze the potential demand for the urban railway in Yogyakarta, Indonesia based on bivariate ordered probit model. The survey of preference stated with 120 samples conducted in Yogyakarta. The model of train demand is distinguished between public transport users and private vehicle users using seven scenarios. In-train travel time, waiting time, tariff, and ticketing discount for students are four factors considered in the model. The demand model shows that in-train travel time is the most important factor influence for train demand. Meanwhile, the scenario result reveals that respondents except student are willing to pay more to obtain shorter travel time, students who use private vehicle are reluctant to shift into the train, and ticketing discount brings no effect to stimulate them to use the train.

Migration and Subjective Poverty in sending countries: An analysis of the Egyptian case

Migration has traditionally been used as a survival strategy in times of financial crisis; however, a debate exists as to whether migration influences poverty on the individual level. The current study analyses the influence of past subjective poverty on migration choice and to determine the impact of migration on current subjective poverty perception. Using a simultaneous bivariate ordered probit model, we found that poorer individuals in Egypt tend to migrate more than others. Migration was found to be a significant determinant of current poverty in Egypt. Finally, migration improved migrant’s financial situation.

Strategic and Organizational Considerations Related to an E-Learning Model

The aim of this chapter is to assess the impact of different organizational factors on the success of e-learning programs, in terms of both self-reported satisfaction and the level of learning. Hence, this study adds to the analysis of the efficacy of e-learning models from an organizational perspective by providing some useful insights, which may help to improve decision-making related to employee’s continuing education and satisfaction. This simulation, using a bivariate ordered probit model, shows that economic and indirect economic incentives play a key role in augmenting the level of both satisfaction and learning. This analysis also considers how efficacy of learning programs may thus improve by linking the human resources development policy with results obtained in e-learning courses.

Strategic and Organizational Considerations Related to an E-Learning Model

The aim of this chapter is to assess the impact of different organizational factors on the success of e-learning programs, in terms of both self-reported satisfaction and the level of learning. Hence, this study adds to the analysis of the efficacy of e-learning models from an organizational perspective by providing some useful insights, which may help to improve decision-making related to employee’s continuing education and satisfaction. This simulation, using a bivariate ordered probit model, shows that economic and indirect economic incentives play a key role in augmenting the level of both satisfaction and learning. This analysis also considers how efficacy of learning programs may thus improve by linking the human resources development policy with results obtained in e-learning courses.