Statistical analysis of vehicle theft crime in peninsular Malaysia using negative binomial regression model

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

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, car-makers and car owners, as they can be used to establish practical steps for preventing or at least limiting vehicle thefts. In addition, this paper also proposed a crime mapping application that allows us to identify the most risky areas for vehicle theft. The results from this study can be utilized by local authorities as well as management of internal resource planning of insurance companies in planning effective strategies to reduce vehicle theft. Indirectly, this paper has built ingenuity by combining information obtained from the database of Jabatan Perangkaan Malaysia and insurance companies to pioneer the development of location map of vehicle theft in Malaysia.

Original languageEnglish
Pages (from-to)1363-1370
Number of pages8
JournalSains Malaysiana
Volume44
Issue number9
Publication statusPublished - 1 Sep 2015

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Crime
Statistical methods
Insurance
Railroad cars
Planning
Industry
Identification (control systems)

Keywords

  • Crime
  • Mapping
  • Negative binomial
  • Spatial analysis
  • Vehicle theft

ASJC Scopus subject areas

  • General

Cite this

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title = "Statistical analysis of vehicle theft crime in peninsular Malaysia using negative binomial regression model",
abstract = "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, car-makers and car owners, as they can be used to establish practical steps for preventing or at least limiting vehicle thefts. In addition, this paper also proposed a crime mapping application that allows us to identify the most risky areas for vehicle theft. The results from this study can be utilized by local authorities as well as management of internal resource planning of insurance companies in planning effective strategies to reduce vehicle theft. Indirectly, this paper has built ingenuity by combining information obtained from the database of Jabatan Perangkaan Malaysia and insurance companies to pioneer the development of location map of vehicle theft in Malaysia.",
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