Situational crime prevention theory intends to be a practical way in crime prevention (Clarke, 1992; Clarke & Cornish, 1983). Crime can be prevented through reducing the opportunities latent within the situation (Clarke, 1983; Cornish & Clarke, 2003; G. R. Newman, Clarke & Shoham, 1997). Situational crime prevention is actually a combination of routine activity theory (Cohen & Felson, 1979), environmental criminology theory (Newman, 1973), and rational choice theory (Cornish & Clarke, 1986). There are some techniques related to reducing opportunity were advanced by this theory, including target hardening, target removal, natural surveillance, formal surveillance, and surveillance resulting in removing the means or opportunity to commit crime (Clarke & Mayhew, 1980).
The theory used in this research does not aim at changing the roots of crime, it has been widely criticized that crime displacement will occur when efforts taken to prevent crime in one context may cause an increase in crime in other contexts (Hayward, 2007). Crime displacement may happen in many conditions such as geographical displacement, temporal displacement, target displacement, tactical displacement, crime-type displacement (Felson & Clarke, 1998), or some combination of these (Guerette & Bowers, 2009; Hesseling, 1994).
Clarke (2009) and few others (Gabor, 1990; Hesseling, 1994) have found and rightly note is that crime displacement is never 100%. Many researchers have proved that situational measures may result in a diffusion of crime prevention benefits or the reverse of crime displacement (Clarke & Weisburd, 1994; Guerette & Bowers, 2009). Same results have been found for crime prone area in crime policing interventions (Braga, 2006; Weisburd et al., 2006). The project’s prevention benefits are diffused to the surrounding area instead of a crime prevention activities displacing crime. Clarke and Weisburd (1994) argued that this will only occur by affecting criminals’ assessment of risk (deterrence) or by affecting criminals’ assessment of effort and reward or discouragement.
In many comprehensive reviews on crime displacement and diffusion effects of situational prevention programs, Guerette and Bowers (2009) found that crime displacement is more exception rather than the rule and diffusion is somewhat more likely to take place than displacement. Their systematic review included 102 evaluations with more than 570 observations of situational crime prevention techniques. Guerette and Bowers (2009) found that when crime displacement did occur in a smaller group of evaluations that allowed for more detailed analyses. The effects were more often mitigated by the overall desirable treatment effect. Smith et al. (2002) argued that researchers should also investigate the anticipatory benefit whereby crime reduction occurs earlier than anticipated before implementation of an intervention. Smith et al. (2002) also found evidence of an anticipatory effect in 22 out of 52 studies conducted. There are also many more studies provided insufficient details to allow for its investigation. Guerette (2009) emphasis the important implications this issue holds for evaluations of situational crime prevention programs such as need to use time-series data to detect any crime reduction that precedes implementation.
4.2. Discussion on Statistical Analysis Result
4.2.1 Data Analysis
In order to develop a better understanding of crime displacement, research must be initiated that focus specifically on this phenomena. Such research could be designed to define how far and under what circumstances crime will be displaced. This could be done at the outset to identify problems and places that provide sufficient numbers of cases in target and affected areas for statistically powerful analyses. Because it would not be constrained by focus on direct effects, this could also design out problems of crime displacement contamination and differentiate potential crime displacement. Direct program impacts would not be problematic in this type of research and accordingly, researcher would examine crime displacement in a context in which it is already clear that there is an effect that is possible to displace the crime. The efforts would be invested in tracking and understanding the nature of that process and not in establishing the efficacy of interventions themselves. It is time to move crime displacement from a secondary to a primary focus of criminological study.
Descriptive statistics is being used to describe some of the characteristics of the distribution scores that were collected, such as average score on one variable or the degree that one scores varies from another. Finally, the data are organized in a way that they can be closely examined. Then researcher applied the set of tools called inferential statistics to help make decision about how the data collected relates to the original scenario and how these results might be able to generalize it to a larger number of subjects than those were tested. The one-way analysis of variance (ANOVA) is also used to determine whether there are any significant differences between the means of the independent (unrelated) groups. Bi-variate correlation is used to determine if two variables are linearly related to each other such as:
– Descriptive Statistics
– Inferential Statistics
o Correlation Test Result
– Measurement of Central Tendency
o Mode Median
o Standard Deviation
– ANOVA (Analysis of Variance)
o Measurement of Dispersion
o Range
o Testing Goodness of Data – Reliability Test Result
o Two-Sample t-Test for Equal Means
o t-Test
– MANOVA
o Chi-Square Test for the Variance
o Chi-Square Goodness-of-Fit Test
o F-Test for Equality of Two Variances
o Correlation Coefficient (Pearson’s r)
o Multiple Correlation and Regression
o Multi-factor Analysis of Variance
o Multiple Regression Analysis
4.2.2 Statistical Data Analysis Result
In this research the survey questions were designed to find out 2 categories of logistics and transportation companies in Malaysia whether it is foreign joint venture or local owned company. Information related to the respondent’s positions was gathered. Since this research is focusing in peninsular Malaysia, respondents were requested to identify which states in Malaysia they were operating. As these information is required to find out the different of security control measures implemented between local and foreign companies in Malaysia. Information related to the numbers of employees, types and total numbers of fleets, types of vehicles used, the types of cargo or goods transported and number of security incident in their companies were also collected. The questions were structured into 5 different sections related to security management of transportation and logistics operation as follows:
– Section A assessed security certification and regulatory requirements includes TAPA (Technology Asset Protection Association) Freight Security Requirements –FSR, TAPA TSR (Transport Security Requirements, ISO 28000, ISPS Code, Custom Trade Partnership against Terrorism (CTPAT), World Custom Organization (WCO) and ICAO;
– Section B assessed security budget allocation in security management;
– Section C assessed security administrative control implemented in the company;
– Section D assessed implementation on facility physical security control in the company;
– Section E assessed transportation operational control in the company and;
– Section F assessed trucking security control.
In each section, there are several questions related to the security management in the company were posed to gather information and assessing the level of security for that particular areas. In every section, the respondents were requested to identify the level of implementation from scale of 0 (no implementation) to 10 (fully implemented).
The statistical method used in this research is based on multivariate analysis techniques. All the statistical analyses have been carried out with SPSS v. 15.0 programmes. According to Hair et al. (2009) multivariate analyzed simultaneously analyzes multiple measurements on individuals or objects under investigation. The general structure of the statistical analysis performed includes the following steps:
– Descriptive statistics,
– Exploratory and Confirmatory Factor Analysis,
– Cluster analysis,
– MANOVA,
– Discriminator analysis
– Analysis to ensure the validity and reliability of the survey.
Before starting the analysis, the presence of common method bias was checked by performing an un-rotated factor analysis by using Kaiser Criterion (eigen value > 1). This analysis conducted found the existence of 12 distinct factors that accounted for 80 % of the variance. If a single factor didn’t appear in the analysis and the first factor didn’t account for the most of the variance, the absence of common method bias may be assumed (Paulray et al., 2008). Finally, the results of the analysis carried out are presented as mean values and proportions.
The reliability test of measurement was performed to ensure for both consistency and stability. Cronbach’s alpha is a reliability coefficient that indicates how well the items in a set are positively correlated with one another. Cronbach’s alpha is known as the average of inter correlations among the items. The closer Cronbach’s alpha to 1, the higher the internal consistency reliability will be. The test was performed on security control measures implemented by companies. The result of the Cronbach’s Alpha Based on Standardized Items is 0.946 which means the items are positively correlated to one another.