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Few criticisms of situational crime‐prevention (SCP) efforts are as frequent or prevalent as claims of displacement. Despite emerging evidence to the contrary, the prevailing sentiment seems to be that crime displacement is inevitable. This study examined 102 evaluations of situationally focused crime‐prevention projects in an effort to determine the extent to which crime displacement was observed. The results indicate that of the 102 studies that examined (or allowed for examination of) displacement and diffusion effects, there were 574 observations. Displacement was observed in 26 percent of those observations. The opposite of displacement, diffusion of benefit, was observed in 27 percent of the observations. Moreover, the analysis of 13 studies, which allowed for assessment of overall outcomes of the prevention project while taking into account spatial displacement and diffusion effects, revealed that when spatial displacement did occur, it tended to be less than the treatment effect, suggesting that the intervention was still beneficial. Implications for theory and future research are discussed.

Research demonstrates that certain crime prevention techniques work. Accordingly, current evaluations focus on what works and where. One of the key elements in assessing crime prevention success is determining the number of crimes prevented. This allows the cost-effectiveness of schemes to be assessed and different schemes to be meaningfully compared. Evaluation studies of what works include a variety of different approaches, some more robust than others. The current article presents two methods for calculating the outcomes of crime prevention interventions. The basic principle behind both approaches involves subtracting the observed number of crimes from an estimate of the number of crimes that would have occurred had the scheme not existed. Importantly, it is acknowledged that area crime rates are influenced both by general trends and more random factors. Thus, each approach produces a range of estimates to attempt to assess the impact of more random influences.