To Örebro University

In environmental criminology, various methods exist to forecast unsafety. Some are more complex than others. To determine their practicality, we must compare the accuracy of simple, transparent, and functional methods with slightly more complex methods and those requiring more data collection.

The overall aim of the current dissertation was to examine the relationship between crime history, environmental and neighborhood characteristics in forecasting unsafety, both crime and fear of crime, in various geographical locations. Study I compared the predictive accuracy of two methods using historical crime exposure and different crime-time-periods for violent and property crimes. Study II compared the predictive accuracy of prior crime, place attributes, ambient population, and community structural and social characteristics for various crime types. Study III examined the relationship between violent and property crime, as well as community structural and social characteristics, and different types of fear of crime.

The findings of the current dissertation suggest that, overall, a one-size-fits-all approach is not effective. Simpler methods are generally comparable to more complex ones in long-term crime forecasting at the micro-level. However, at the neighborhood level, social integration plays a significant role in determining levels of perceived safety and fear of crime.