Effective measures for combating drink-driving offenses: An attitudinal model for Hong Kong

Y. C. Li, Nang Ngai Sze, S. C. Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

12 Citations (Scopus)

Abstract

In Hong Kong, legal limits on the concentration of alcohol permitted in drivers' blood, urine, and breath were introduced in 1995. Later legislation empowered the police to conduct random breath tests (RBTs) without the need for suspicion. Although drink-driving accounts for a relatively small portion of the traffic accidents in Hong Kong, the average killed and seriously injured rate for drink-driving accidents is higher than that for overall traffic accidents. From time to time, there are calls for heavier penalties such as longer prison sentences and driving disqualification periods for drink drivers, particularly those who cause severe injury and death. However, no consensus has been reached on the actual effectiveness of severe penalties in combating drink-driving offenses. In this study, a self-administrated, mail-back questionnaire including six stated preference games was conducted to evaluate drivers' perceptions of the current levels of penalties against drink-driving offenses. The game measured the associations between the propensity to drive after drinking and penalty levels. The results of a mixed logistic regression model revealed that the presence of an RBT checkpoint and an increase in driving-offense points and the durations of licence disqualification and imprisonment correlated positively with an increase in the deterrent effects of measures taken to combat drink driving.
Original languageEnglish
Pages (from-to)722-739
Number of pages18
JournalTransportmetrica A: Transport Science
Volume10
Issue number8
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

Keywords

  • drink driving
  • mixed logistic regression
  • random breath test
  • stated preference survey
  • traffic safety

ASJC Scopus subject areas

  • Transportation
  • Engineering(all)

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