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The aim of this paper was to identify the determinants that influence vehicle theft by applying a negative binomial regression model. The identification of these determinants is very important to policy-makers

Transportation is a major factor in influencing our daily lives to become more efficient and productive. The taxi had become the favourite of people in choosing public transportation because it personally brings us to the exact location of our destination. Taxi has monopolized public transport from door to door for a long time ago until a company providing the same service known as the Grab entered the market recently. This study had been conducted to compare the services provided by taxi and Grab from the perception of their customers. This study can help service providers see which aspects they need to make improvements in the interests of both parties. The survey had been conducted at Kuala Lumpur because of the probability of taxi and Grab users are higher at a busier state as in the capital city. Descriptive statistics is mainly used in making simple summaries with the help of graphical representation. Mann Whitney U test had been used to compare the two service providers at each aspect which are accessibility, comfort of rides, safety and value for money. As a result, Grab has significantly higher user ratings than taxi for all aspects of services considered in the study.

This paper proposes the application of the two well known models of negative binomial regression, namely the NB-1 and the NB-2, and the functional form of negative binomial regression, namely the NB-P, for the analysis of vehicle theft crime. The advantage of using the NB-P is that it parametrically nests both the NB-1 and the NB-2, and allows statistical tests of the NB-1 and the NB-2 models against a more general alternative. In this study, the functional forms of negative binomial regression model were fitted to vehicle theft crime data obtained and compiled from ten insurance companies in Malaysia. The results of this study indicate that the risks of vehicle theft are higher for vehicles above eight years, vehicles above 1800 c.c., local vehicles and vehicles located in the central area of Malaysia.

Articles you may be interested inTemporal changes and variability in temperature series over Peninsular Malaysia AIP Conf.Abstract. Vehicle theft is classified as property crime and is considered as the most frequently reported crime in Malaysia. The rising number of vehicle thefts requires proper control by relevant authorities, especially through planning and implementation of strategic and effective measures. Nevertheless, the effort to control this crime would be much easier if there is an indication or index which is more specific to vehicle theft. This study aims to build an index crime which is specific to vehicle theft. The development of vehicle theft index proposed in this study requires three main steps; the first involves identification of criteria related to vehicle theft, the second requires calculation of degrees of importance, or weighting criteria, which involves application of correlation and entropy methods, and the final involves building of vehicle theft index using method of linear combination, or weighted arithmetic average. The results show that the two methods used for determining weights of vehicle theft index are similar. Information generated from the results can be used as a primary source for local authorities to plan strategies for reduction of vehicle theft and for insurance companies to determine premium rates of automobile insurance.