Most Recent Publication

Using HLM to investigate the relationship between traffic accident risk of private vehicles and public transportation 

Publish at Transportation Research Part A: Policy and Practice 119, pp. 148-161. (SSCI, SCI) (Impact factor 2017: 3.026)

https://doi.org/10.1016/j.tra.2018.11.005

Public transportation is relatively safe and secure, although less convenient than private modes of transport. However, current trends indicate that, by 2030, road traffic injuries will be the fifth leading cause of death globally. This study proposes an approach for identifying hidden contributors to traffic risk in the major metropolitan cities of Taiwan. Our purpose is to offer a comprehensive econometrical framework, using Hierarchical Linear Modelling (HLM), which highlights important contributors to traffic accident risk at different levels of injuries for public transportation. Four models underlying HLM are used to characterize the traffic accident risk. Our empirical results indicate that random intercept and random slope with interaction of HLM (model 4) is the best model. In addition, there are significant regional differences in traffic accident risk depending on the use of public and private transportation, the length of bus routes, daily average number of bus frequency per route, gender, driving habits, and behaviour. Results show that, when the length of bus routes increases by 50% in a city with well-developed infrastructure, such as Taipei, the accident risk would reduce the crash risk from 1.66 to 1.43 (decreases by 0.23), corresponding to 3450 casualties, and the total accident expense can be reduced by NT$13 billion. If daily average number of bus frequency per route in Taichung increases by 50%, there are almost 3000 fewer casualties, and the accident expense decreases by NT$9.6 billion. The results of this study provide suggestions to the government that developing public transportation can effectively decrease road traffic accident risk and accident expense.

Analysis the Drunk-Driving Recidivists under Different Administrative Area in Taiwan 

Publish at Accident Analysis & Prevention 119, pp. 16-22. (SSCI, SCI) (Impact factor 2017:2.584)

https://doi.org/10.1016/j.aap.2018.06.011 

Traffic violations, particularly drink driving, are a menace to the drivers themselves, and to other road users. Drink driving crashes often cause death or serious injury to the driver. Understanding the recidivism effect factor of drink driving is essential for designing effective countermeasures. This study is based on register-based data from the National Police Agency, Ministry of the Interior of Taiwan and monthly administrative area information from 2012 to 2015 for the entire population. Hence, this study not only focuses on the effect factor and violation differences between recidivists and non-recidivists, but discusses the entire regional characteristics effect for recidivism. The purpose of this study is to offer a comprehensive econometrical framework, using a multilevel random effect logistic model, which highlights important contributors to drink driving recidivism from regional attributes. As the study findings from our empirical results indicate, there are statistically significant differences with drink driving in administrative areas, depending on the number of report on drink driving by police, divorce rate of the population, alcohol consumption, number of community security patrol teams, number of bus trips, and level of education. The results of this study provide suggestions to the government for enhancing community security and developing public transportation, both of which can effectively decrease drink driving recidivism and improve public road safety.