Skip to main content
SearchLoginLogin or Signup

Environmental criminology, design, and victimization: What we know, how we have failed, and where we need to go

Andresen, M.A., & Hodgkinson, T. (2021). Environmental criminology, design, and victimization: What we know, how we have failed, and where we need to go. In T.C. Pratt, & J.J. Turanovic (Eds.), Revitalizing victimization theory (pp. 104 – 128). New York, NY: Routledge.

Published onJan 01, 2021
Environmental criminology, design, and victimization: What we know, how we have failed, and where we need to go

Environmental criminology, design, and victimization: What we know, how we have failed, and where we need to go


Environmental criminology, and spatial-temporal criminology more generally, has the potential to contribute to the understanding of victimization. After reviewing the principle theoretical components of environmental criminology, we outline how environmental criminology has contributed to the understanding of victimization, where it has failed, and future directions for research and theory. Overall, we argue that despite the potential for environmental criminology to contribute to the study of victimization, little research is done on victimization within environmental criminology. Moreover, we discuss how certain crime prevention strategies have led to unintended consequences, such as further victimization of poor and marginalized groups. We conclude with recommendations of how to move the field of environmental criminology forward by considering victims and victimology more broadly.

Keywords: environmental criminology; victimization; routine activity approach; geometry of crime; rational choice


Victimization does not occur in a vacuum. It occurs in particular places and spaces. Unsurprisingly then, victimization concentrates in certain parts of the urban landscape. Environmental criminology is useful for understanding how and why victimization concentrates in some places and not others and for guiding policy and practice to reduce victimization and make these places safer.

The first wave of research that investigated the spatial and temporal (where and when) dynamics of crime and victimization date back almost 200 years to the work of Adolphe Quetelet (1831, 1842) and Andre-Michel Guerry (1832, 1833). They found that concentrations of crime varied across French departments (approximately the size of a US county), and differently for property versus violent crime; Quetelet (1842) also found that crime and victimization varied across the seasons.

The second wave of spatial criminology emerged out of the Chicago School. Here, local practitioners and academics investigated neighborhood level crime and victimization. Research in this second wave generally found that crime and victimization was highest in “socially disorganized” neighborhoods characterized by population turnover, ethnic heterogeneity, and low socio-economic status (Shaw & McKay, 1942). This formative work in social disorganization theory investigated juvenile delinquency, not crime or victimization but had important implications for the research of both.

The third wave of research that investigated spatial and temporal dynamics of crime is now referred to as environmental criminology, a term coined by Jeffrey (1971). According to Brantingham and Brantingham (1981a), this third wave differentiated itself from the first two by specifically having a geographical rather than a sociological imagination—the fundamental focus of the research changed. When discussing this shift, Brantingham and Brantingham (1981a) stated that there were four fundamental dimensions necessary for understanding the phenomena of crime: the legal dimension, the offender dimension, the victim dimension, and the place (or situational) dimension. The legal dimension is concerned with the creation, formation, and interpretations of laws; the offender dimension is concerned with understanding the motivation of offenders, how that motivation changes across time, and why different people may have different degrees of motivation to commit crime; the victimization dimension is concerned with understanding why particular people are victims of crime; and the place, or situational, dimension is dominantly concerned with the spatial and/or temporal aspects of crime.

This third wave led to notable theoretical and empirical advancements within criminology, discussed below, but they primarily focused on opportunity structures. We argue that focusing on opportunity structures had unintended consequences that, in some cases, led toincreased victimization particularly for marginalized populations. In this chapter, we outline the primary theoretical perspectives within environmental criminology (routine activity approach, geometry of crime, rational choice) and crime prevention through environmental design, discussing how victimization is accounted for, or more often ignored, by this research. We then discuss where environmental criminology has contributed to understanding victimization, where it has failed, and where it needs to go.

Theories and perspectives within environmental criminology

As noted above, there are three theories, or perspectives, within environmental criminology: routine activity approach, geometry of crime, and rational choice. Ironically, these theories or perspectives emerged almost a decade or more after C. Ray Jeffrey (1971) coined the term in the context of crime prevention.

Routine activity approach

The routine activity approach, Cohen and Felson (1979), originally emerged to investigate the sociological paradox: crime was increasing while the standard metrics of social well-being (unemployment, after-tax income, education, and so on) improved. . In their influential paper, Cohen and Felson (1979) stated that in order for a crime occur, there needed to be a motivated offender, a suitable target, and the lack of a capable guardian converging in time and space. They argued that if there were more opportunities for these three components to converge, crime rates would increase.

With regard to victimization, the routine activity approach directly refers to suitable targets. In fact, one of the primary interests of Cohen and Felson (1979) are the increases in target suitability in the post-1950s era, particularly in the development of (relatively) lightweight electronics that continues to impact crime patterns today (Mailley et al., 2008; Whitehead and Farrell, 2008; Brimicombe, 2012). However, in their empirical assessment, Cohen and Felson (1979) found that changes in routine activities were the drivers of increases in crime patterns. This relates to both property and personal victimization. Individuals, in particular women who had increasing opportunities to participate in the workforce, were spending more time outside of the relatively protective environment of the home and placing themselves and their property at greater risk of the above-mentioned convergences. Kennedy and Forde (1990) showed this more definitively measuring individual level activity patterns and self-report victimization data. Specifically, those who spent more time away from home had greater levels of victimization—bars and pubs for violent crime, and most other activities for property crime.

Most of the research within environmental criminology that has used the routine activity approach has operationalized suitable targets in an indirect manner. This has commonly been in the context of (spatial) regression analyses of crime in places (neighborhoods, census tracts, and other administrative units) using variables that measure the presence of suitable targets, relative to other areas: measures of income or housing value, single parent households, the presence of youth, and so on. Most often, strong support is found for these correlates, indicating that places with more suitable targets have more crime—see, for example, Andresen (2011). However, this empirical support for the routine activity approach, though instructive and useful in some crime prevention contexts, does not directly advance scholarship on victimization. From a victimization perspective, stating that places with more suitable targets, or people with particular routine activities, have higher rates of victimization is an empty statement that can be interpreted as victim-blaming, though that was not its intent.

Geometry of crime

The geometry of crime (Brantingham & Brantingham, 1981b, 1993a) is effectively a spatial version of the routine activity approach—it is important to distinguish the geometry of crime from crime pattern theory (Brantingham & Brantingham, 1993b), the latter being an attempt at meta-theory to bring together the various approaches within environmental criminology. In the geometry of crime, our routine activities are presented spatially by the concepts of activity and awareness spaces. Our activity space is the area we spend most of our time at particular places (nodes) and the pathways between those nodes. Our awareness space extends some (albeit small) distance beyond our activity space; because one must deviate from their traditional paths at times, they tend to learn about the immediate areas around the nodes and pathways we routinely travel. Because of the planned nature of our built environments we share a lot of our activity nodes and pathways with other people: central business districts, shopping centers, and entertainment zones.

The geometry of crime has a number of predictions regarding the locations of criminal events, based on the above (see Brantingham & Brantingham, 1981b), but the critical message from this perspective is that criminal victimization is neither randomly nor uniformly distributed: it is concentrated in both space and time. With regard to victimization, the geometry of crime does not state anything specifically. Rather, criminal events (victimization) will occur when the activity spaces of motivated offenders overlap with the activity spaces of suitable targets. Consequently, people are most often victims of criminal events when they are in places that they routinely spend our time.

These locations for criminal victimization become most apparent within this perspective from the concepts of crime generators and crime attractors (Brantingham & Brantingham, 1995). Crime generators are places that generate a lot of criminal events because there is the presence of a large number of motivated offenders and suitable targets converging in time and space. This convergence will be at an activity node, such as a transit station or transfer point. Crime attractors, on the other hand, attract motivated offenders because of their criminal opportunities. Therefore, motivated offenders will actually modify their activity and awareness spaces to take advantage of such opportunities.

Rational choice

Rationality is a assumed aspect of both the routine activity approach and the geometry of crime, but rational choice is also specifically used as a perspective within environmental criminology (Clarke & Cornish, 1985; Cornish & Clarke, 1986). Within the rational choice perspective, motivated offenders make a sequence of choices that effectively involve costs (probability of being caught and punished) and benefits (the value(s) of the outcome of the offense) when deciding if they should act at all, if a particular offense should be undertaken, and when they should desist from such behaviour. Most often, people do not contest property crimes as being the outcome of a “rational choice”, but violent crimes tend to be more difficult to be interpreted in that context. However, different people have different preferences, resources, and constraints and that lead to different choices. In other words, what is rational for one, might be irrational to another. What is important to understand is that people are making the best choices they can to reach their goals, while considering their constraints relating to time, money, and so on. And (violent) crime is simply another choice. Beauregard et al. (2007) has found this to be the case for violent sexual crimes with offenders making as many as nine (rational) choices for their being able to complete their criminal events.

One of the criticisms of this approach is that it is impossible to have enough information all the time to make decisions in a “rational” manner. Gathering and processing information is costly, particularly in a criminological context, and may not even be considered possible. In an effort to address this issue, the field of limited or bounded rationality emerged. Herbert Simon (1957, 1982) argued that we make our decisions heuristically by seeking out pleasure and avoiding pain, making rational choices based on the best available information.

The most common application of rational choice perspective within criminology is in the context of crime prevention and reduction. The rational choice perspective was used to show that different criminal opportunities were not functionally equivalent and that if the “easy” targets for criminal victimization were removed or reduced, the “second best” targets would not be worth the effort many motivated offenders. Consequently, though some criminal activities may be displaced, this was not an expectation en masse (Felson & Clarke, 1998). With regard to the displacement of crime, the expectations from this perspective is that it will be minimal, if it even exists. In a recent and sophisticated experimental analysis of the existence of crime displacement, Weisburd et al. (2006) found no evidence for this phenomenon. In fact, these authors found that the benefits of crime prevention initiatives diffused into surrounding areas—this was commonly found in other literature as well, but not using a sophisticated experimental methodology—see Barr and Pease (1990), Eck (1993), Hesseling (1994), and Guerette and Bowers (2009) for reviews of this literature that find very little evidence for crime displacement. However, Hodgkinson et al. (2020) found that crime displacement can occur further away than originally expected by previous research and can lead to more violent and detrimental victimizations.

As such, the rational choice literature within criminology has had little to say with regard to victimization. From a prevention standpoint, it has highlighted many circumstances in which (situational) prevention has been successful (Clarke, 1992, 1997) that can then be inverted as advice to prevent victimization, but its focus is on changing opportunity structures that subsequently change offender behaviour with regard to criminal victimizations.

Crime prevention through environmental design and situational crime prevention

Crime prevention through environmental design, commonly referred to as CPTED, had its modern beginnings with the work of C. Ray Jeffrey (1969, 1971) and Oscar Newman (1972). The “environment” in this context is meant broadly, referring to not only the built/physical environment that much of CPTED practices follow today, but also the legal and social environment. These various environments influence both opportunities and motivations for criminal activity. As such, modifications to our environment can either facilitate or mediate opportunities for crime. For obvious reasons, crime prevention focuses on modifications to our various environments in order to reduce criminal occurrences and victimizations but has also been used to outline how environments can be built to reduce criminal victimizations, a priori rather than post hoc.

How and when CPTED is implemented is of particular importance in determining the timing of the expected reductions in criminal victimizations. Brantingham and Faust (1976) utilized the primary-secondary-tertiary (PST) model from public health to crime prevention: primary prevention is implemented before a problem emerges (good social service policies, for example, to reduce motivation), secondary prevention is implemented when a target (person, object, or place) is identified as being at a greater level of risk than expected, and tertiary prevention is implemented after some form of victimization has occurred and stakeholders act to (hopefully) reduce future victimizations.

Tertiary prevention is the most common form of CPTED implementation. Rather than creating detailed development plans that identify potential opportunities for crime and redesign to prevent these opportunities (City of Saskatoon, 2010), most developers simply wait until a problem has occurred. For example, if an apartment building is dealing with a rash of auto-theft from their underground parking lot, they will likely put in methods of access control (boom gates and key fobs) to prevent further victimizations. This is particularly true in a time of neoliberalism with the trend being the reduction of social service provision (development planning) corresponding with an increase in formal control mechanisms (security) (Harvey, 2010).

More often, tertiary prevention is framed in the context of situational crime prevention (Clarke, 1980, 1983, 2012). Situational crime prevention, as the term indicates, focuses its crime prevention techniques considering the situation within which crime is occurring. As such, situational crime prevention techniques vary across crime types, time of day, places, and victim; examples of these techniques, and their broader classification, can be organized under increasing the effort, increasing the risks, reducing the rewards, reducing provocations, and removing excuses.1 These techniques have been shown to have success (Clarke, 1992, 1997), but these successes are often viewed, we argue, from a rather myopic perspective reducing criminal victimization here and now without the consideration of increasing victimizations there and later.

Environmental criminology and victimization: what we know

As noted above, the field of environmental criminology has not significantly contributed to the understanding of victimization patterns. However, there are a handful of areas within environmental criminology with contributions that relate to the understanding of victimization. The contributions, often understood as empirical regularities in the patterns of victimization, relate to the journey to crime/victimization, mobility triangles, repeat victimization, near-repeat victimization, and the temporal patterns of victimization.

The journey to crime and victimization

The journey to crime actually includes two journeys: the journey of the motivated offender to the location of the criminal event and the journey of the target/victim to the location of the criminal event. We will refer to these as the journey to crime and the journey to victimization, respectively.2 The overall finding is that the journeys to crime and victimization are short, particularly for violent crime: though there are variations across studies, the journey to violent crime is typically 1 kilometer, whereas the journey to property crime is typically 2 kilometers. These journeys are explained within environmental criminology because the metric used to assess these journeys in distance (part of the spatial dimension).

Because people spend most of their time, by definition, undertaking their routine activities in activity nodes and the pathways between them, their journeys to crime and victimization are expected to be in those spaces and the times they are there. As such, given that we attempt to minimize the effort to undertake our activities (why go to a grocery store across town when there is one 2 blocks away?), following Zipf’s (1949) principle of least effort, our expectation for the journeys to crime and victimization are that these distances are relatively short. And this is precisely what has been found in the empirical research. Dating back almost 90 years, White (1932) found that the journey to crime was short, particularly for violent crime. This empirical regularity has been found repeatedly across a number if different property and violent crime types, national contexts, and ages of offender (Andresen et al., 2014; Costello & Wiles, 2001; and Wiles & Costello, 2000).

When considering specific details regarding the types of crime being committed, research has shown that distances to crime lengthen when the reward is greater (Morselli & Royer, 2008; Vandeviver et al., 2015) and when a higher degree of planning is necessary (Capone and Nichols, 1976; Gabor and Gottheil, 1984; van Koppen and Jansen, 1997; White, 1932). This is consistent with the rational choice perspective with regard to expected rewards. Andresen et al. (2014) and Ackerman and Rossmo (2015) both found that the journey to crime increases with age, peaking around 20 and then declining; this is consistent with changes in activity spaces for individuals as they age—Drawve et al. (2015) also showed this increase with juveniles, but had no data for adult offenders to confirm or deny the subsequent decrease found in these other studies. Additionally, Ackerman and Rossmo (2015) found that the journeys to crime in lower socio-economic neighborhoods has shorter than higher socio-economic neighborhoods—Costello and Wiles (2001) found similar results within the context of the journeys to crime and victimization.

With regard to the journey to victimization, specifically, we are only aware of two studies. Costello and Wiles (2001) compared both the journey to crime and the journey to victimization within the context of property crime. They found that the journey to crime was relatively short, consistent with previous and subsequent research. However, they also found that the journey to victimization was even shorter, often half the distance for the journey to crime. Moreover, they found that areas with lower socio-economic status had high levels of in-area victimization with, as one would expect, shorter journey to that victimization. Block et al. (2007) also found that the journey to victimization is shorter than the journey to crime for robbery and aggravated assault, but the journey is longer for sexual assault. Clearly, the victimization component of these journeys is different from the offending component. However, there is a clear lack of research in this area. The most fruitful applications with regard to distance travelled in the context of victimization is in the mobility triangle subfield of research.

Mobility triangles

A mobility triangle refers to the three geographic points that are necessary for a criminal event to occur: the starting point of the offender’s journey, the starting point of the victim’s journey, and the point at which they meet. As such, this research brings the journey to crime and the journey to victimization together in one construct. As a social construct, it was first put forth by Burgess (1925), when writing about sexual promiscuity. Using more criminological terms, Burgess put forth three types of triangles: delinquency triangles (offenders’ residence, victim’s residence, and crime location all in the same neighborhood/community), mobility triangles (offender’s and victim’s residence in the same neighborhood, but the crime location is elsewhere), and promiscuity triangles (all points are in different neighborhoods)—Lind (1930) was the first to apply this construct to crime, finding that the delinquency triangle (the least amount of travel for both parties) was the most common in lower socio-economic neighborhoods and that the mobility of offenders increased with age—this is consistent with the journey to crime literature, discussed above.

Close to 40 years later, Normandeau (1968) expanded this typology to include five types of triangles that have been used by most researchers since this publication: crime neighborhood triangle (all in the same neighborhood), offender mobility triangle (victim and event in same neighborhood), victim mobility triangle (offender and event in same neighborhood), offence mobility triangle (offender and victim in same neighborhood), and total mobility triangle (all locations in different neighborhoods). The early work in this area found that victims were often victimized close to their home or the home of the offender (Normandeau, 1968; Amir, 1971; Groff & McEwen, 2007)—hence the short journey to crime and victimization. However, it is important to note that these patterns do vary across crime types (Rand, 1986), characteristics of the criminal event such as offender-victim relationship and the characteristics of the offender and victim (Tita & Griffith, 2005; Cosaro et al., 2017), and when there is more than one offender and/or victim involved in the criminal event (Andresen et al., 2012; Frank et al., 2012).

Collectively, the journey to crime/victimization and mobility triangle literature have shown that, more often than not victimization occurs close to the home of the victim. This is also useful information about offenders because they tend to live close to the criminal event location as well. Such knowledge can be used by investigators (police or otherwise) in order to identify suspect lists. For victimization, the implications are less clear. Effectively, with this knowledge in hand, suitable targets/victims only know that their risk of criminal victimization only increases as they get closer to their home, that should be a safe place. The situational crime prevention literature, discussed above, would state that modifications in routine activities or the provision of guardianship in these spaces (if possible) could reduce the risk of their victimization, but is not likely to provide much solace for those at risk of victimization for the first time or if they are repeatedly victimized where they should feel safest.

Repeat and near-repeat victimization

Repeat victimization is quite simply the phenomenon of repeatedly being a target of criminal victimization. One can be the repeated victim of the same crime type (e.g. domestic violence or hate crimes) or repeatedly a victim of different crime types. Using the International Crime Victims Survey, scholars have found that, overall, 41.5 percent of victims are re-victimized (Farrell & Bouloukos, 2001; van Dijk, 2001).3 Probably the most important aspect of repeat victimization to grasp here is that the vast majority of people are not victims of crime, but once an individual has been victimized, their odds of being victimized again are quite high. As such, this is probably one of the most applicable aspects of environmental criminology for understanding the victimization aspects within criminology.

With regard to the characteristics of repeat victimization of property crimes, Johnson et al. (1997) and Trickett et al. (1992) found that residential burglary victimizations tended to occur in neighborhoods with lower socio-economic status. As such, the costs of repeat victimization tend to be borne by those who are more likely to be marginalized in society and have more to lose. When repeat victimization does occur, it usually occurs with 4 weeks of the initial victimization (Johnson et al., 1997; Melo et al., 2018).

An obvious question to ask at this point is: why do repeat victimizations happen? Farrell et al. (1995) outlined a number of specific examples of why repeat victimizations occur, but there are two general explanations that are important to consider: the flag effect and the boost effect. The flag effect, sometimes referred to as risk heterogeneity, simply states that some targets are more suitable than others, leading to repeat victimization. This is a common explanation in the repeat victimization of residential burglary such that some neighborhoods are more suitable than others so the number of potential targets is actually quite small. The boost effect states that once a target is victimized. Once an offender has completed a victimization. They have learned what worked in that particular context. As such, they may return to victimize that person/target again. The flag effect has been shown to be constant, whereas the boost effect has shown to dissipate over time (Pease, 1998). This is unsurprising for property victimization, as the victim would only be able to replace their stolen items so many times. However, as shown by Johnson (2008) in a computer simulation, both effects were necessary to generate the repeat victimization patterns found in the empirical research.

The implications from this research for understanding, and reducing, victimization is much more direct and practical than other research in environmental criminology. Specifically, if risk heterogeneity is present then those areas with a higher risk profile should be identified and provided with crime prevention initiatives. The costs of crime are greater than the costs of providing crime prevention (Waller, 2014), Because victimization risk tends to be highest in lower socio-economic status neighborhoods, investments in crime prevention using public funds in those places simply make sense. Also using an argument regarding the efficient allocation of resources, Farrell and Pease (1993) argued for crime prevention initiatives to put in place for those who have already been a victim of a criminal event in order to prevent their subsequent victimization that is a much high probability than someone in the general public—Grove et al. (2012) found that crime prevention techniques reduced repeat victimization upwards of 15 percent. However, there are moral implications of this approach. In order to implement prevention against repeat victimization, the strategies have to allow for the victim to be victimized first to be able to be identify them for intervention.

An interesting spatial twist to repeat victimization is the phenomenon of near-repeat victimization: when a target is victimized (usually in the context of residential burglary) not only is that same target at greater risk of re-victimization within a short period of time, but so are other similar targets nearby (Morgan, 2001; Townsley et al., 2003; Johnson et al., 2007). The most commonly test of near-repeat victimization is in the context of residential burglary; this is primarily because the (at least once) suitable target does not move so the identification of “near” repeat victimization is relatively easy to test.

Interestingly, Townsley et al. (2003) found that near-repeat victimization only occurred in certain places. Namely, they found that places with a high degree of housing homogeneity led to increases in the risk of near-repeat victimization—they also found that the presence of more motivated offenders led to increases in the probability of near-repeat victimization, but we are focusing on spatial factors that impact victimization here. As such, in neighborhoods that had similar types of homes, such as more recent suburban housing developments that are completed by one builder, have been found to have higher rates of near-repeat victimization. Bowers and Johnson (2005) investigated the characteristics of near-repeat victimization in residential burglary further, finding that near-repeats are more likely in more affluent areas of the city, homes particularly close to the original victim (literally the next door neighbor was at the greatest risk), homes on the same side of the street, and homes with similar floorplans that are a common feature in more recent large-scale residential developments, as mentioned above.

Despite most of this research being centered on residential burglary, primarily for pragmatic reasons, there has been research investigating near-repeat victimization in other context, but this research tends to investigate near-repeat victimization at places than victimization of persons. This research has investigated shootings (Ratcliffe & Rengert, 2008), street robberies (Haberman & Ratcliffe, 2012; Melo et al., 2018), insurgent activity (Townsley et al., 2008), as well as motor vehicle theft (Melo et al., 2018). In these various contexts, the risk of near-repeat victimization is greatest within a relatively short timeframe (often up to 4 weeks, but as short as 1 week) and within a relatively short distance (often up to only a few hundred meters).

With regard to explanations for near-repeat victimizations, they are similar to those regarding repeat victimization, discussed above, but tend to focus on the boost effect. Bowers and Johnson (2004) found that near-repeat residential burglaries tended to have similar modus operandi, indicating near-repeat victimization by the same offender—this is further developed with the concept of optimal foraging strategies (minimizing effort while maximizing gain from criminal events) by Johnson et al. (2009). And Bernasco (2008) was able to show that near-repeat victimizations for residential burglary were committed by the same offender in a substantial portion of those criminal events.

Temporal dimensions of victimization

Lastly, we will discuss the temporal dynamics of criminal events that relate to victimization. However, most of the results from this research relates to providing (potential) victims of crime with information on when they are at greatest risk. Though important, this type of “victimization” study places the onus of victimization prevention on the (potential) victims themselves.

Seasonal patterns has a history in spatial criminology that dates back close to 200 years. The temporal dynamics of criminal victimization date back to the beginning of spatial criminology with the work of Quetelet (1842) and continues today. Overall, it has been found that criminal victimizations peak in the summer and are at their lowest in the winter, particularly for violent crime types (Andresen, 2020). However, it is important to note that these general patterns do have some variations in different geographies. Research undertaken in England (Field, 1992; Farrell & Pease, 1994), Isreal (Landau & Fridman, 1993), the United States (Cohn & Rotton, 2000; Rotton & Cohn, 2003), Brazil (Ceccato, 2005), The Netherlands (van Koppen & Jansen, 1999), and Scotland (Semmens et al., 2002) found that this seasonal pattern emerges most of the time, but its magnitude varies from place to place and crime type to crime type.

Perhaps more interesting, in the context of seasonal crime patterns, is where these victimizations occur. For example, notable research has found that areas with lower socio-economic status tend to be disproportionately impacted by seasonal fluctuations in the context of homicide (Ceccato, 2005; Harries & Stadler, 1983; Harries et al., 1984) and assaults (Breetzke & Cohn, 2012). This result has been explained by noting that those with lower socio-economic status have fewer resources to escape summer heat through air conditioning—increases in temperature lead to increases in aggression. Additionally, Andresen and Malleson (2013) not only found that many crime types exhibit this seasonal pattern, but the spatial pattern of victimization shifts during the summer months to those places more frequented during those months: parks, popular beaches, and the summer fair. Similarly, Brunsdon et al. (2009) found that victimizations tended to occur outside of the central business district during the summer months.

Temporal research of crime has also been undertaken over longer time periods such as the international crime drop (Farrell et al., 2014), and weekly and daily temporal dynamics of criminal victimization. Weekly patterns of crime most often indicate that criminal events are at their greatest frequencies on Friday and Saturday (Andresen & Malleson, 2015; Corcoran et al., 2019). This is most common for violent crime types, particularly assaults, but also for thefts from vehicle and criminal victimizations in commercial districts. However, it is also important to note that some crime types peak during the week when there is less guardianship present due to peoples’ routine activities leaving homes unguarded for many hours of each work day—Andresen & Malleson (2015) found this to be the case for residential burglary and theft. Perhaps most interesting in their research was the change in spatial patterns of particular crime types for different days of the week.

These researchers found that assaults not only had a peak on Saturdays, but had a spatial concentration in the entertainment district that bordered on the central business district in Vancouver, Canada; a similar spatial result was found in the context of theft from vehicle within or close to parks and shopping centers. Though this information is not particularly surprising, it is predictable given these crime types, providing (potential) victims information as to not only which day is most likely to lead to a victimization, but where that victimization is most likely to take place, similar to the result for seasonal patterns of crime.

Lastly, research on daily temporal crime patterns brings forth an interesting measurement issue (Felson & Poulsen, 2003; Tompson & Townsley, 2010)—this would measure weekly and seasonal effects as well, but not to the same degree. That issue is the arbitrary cut-off of midnight as the change of a day. With “Friday night” and “Saturday night” running over to the next day, this could give a false sense of the risk of victimization. Friday may come across as less risky than Saturday because it does not include a few hours of that night; Saturday likely comes across at a risk level that is appropriate because it misses the last few hours of Saturday night, but does include those hours from Friday night; and Sunday may come across as greater risk than is should because any victimization counts include part of the “night” before. As such, because of this measurement issue, (potential) victims of crime may have incorrect information to base their judgements on with regard to actual risk.

Regardless of this measurement issue, there has been notable consistency in the research that has investigated daily crime patterns. Generally speaking, both property and violent crime tend to peak on Friday and Saturday nights, particularly in the context of violence that is alcohol-related (Andresen & Malleson, 2015; Newton & Hirschfield, 2009). This is the case for both street level crime and crime on transit systems (Ceccato & Uittenbogaard, 2014; Uittenbogaard & Ceccato, 2012). However, it is important to note that police interactions with the public do not always increase on Friday and Saturday nights. For example, Vaughan et al. (2019) found that police interactions with the mentally ill peaked during the middle of the week (Wednesday) and in the middle of the afternoon.

Though instructive for understanding patterns of crime and victimization, this literature does not tell us much about the consequences and costs of victimization. Rather, it focusses on what victims can do to reduce/minimize the risk of (further) victimization. This advice is not framed in the context of victim-blaming, but providing information for people to make “better” choices, such as the ability to alter routine activities, change the places and pathways individuals move through, and purchase safer places to live/work. However, these are not options for all. In this way, the field of environmental criminology has indirectly failed to further scholarship on victimization.

Environmental criminology and victimization: how we have failed

Much of the environmental criminology scholarship focuses on the spatial and temporal nature of crime in order to reduce crime. However, many of these strategies that label themselves as “crime prevention” can actually victimize already victimized and marginalized populations. This is what Cozens and Love (2017) call the “dark side of CPTED,” or “Crime Prevention through EXCLUSIONARY Design.” They explain that these types of crime prevention strategies focus on over target hardening while not considering local context or people. These strategies create a “fortress mentality” in which crime can be controlled by keeping out all potential threats through the use of increasingly advanced security technologies. Examples include the proliferation of CCTV in the downtown of almost any city, which increases control and surveillance of poor and powerless peoples in those spaces who supposedly threaten the safety and security of downtown businesses and “upstanding citizens”. Local associations like Downtown Business Improvement Districts (BIDs) will use the logic of CPTED to implement private security services (Sleiman and Lippert, 2007) or new technologies that are essentially employed to remove “undesirable” people who are bad for business (Wood and McKinnon. 2019). Raymen (2016) argues that these strategies effectively “design-in” crime by creating places that focus solely on consumption and are devoid of humanity and social efficacy, further propagating offender motivation.

Never is the dark side of CPTED more evident than in the treatment of the homeless in the name of crime prevention. Target hardening strategies, which largely emerge from situational crime prevention, and not CPTED, have produced horrific outcomes such as homelessness spikes (spikes in entryways and under bridges) and public bench bars (bars in the middle of public benches) to discourage rough sleeping. Petty (2016) refers to this as “spatialized violence” in which target hardening serves to victimize already victimized and marginalized populations by literally attacking the places where the homeless sleep.

Second and Third generation CPTED have emerged in response to the unintended consequences of the over emphasis on target hardening. The work of Saville and Cleveland (2013) reemphasizes the social and contextual nature of CPTED. They argue that in its original conception, people, not technologies, provided natural surveillance, provided territorial control and created cohesive neighbourhoods in which neighbors know each other and will intervene if someone is behaving problematically. Second generation CPTED focuses on integrating first generation techniques (natural surveillance, access control, territoriality and image/maintenance) with those that incorporate context and the social including culture, cohesion, connectivity and capacity. Mihinjac and Saville (2019) extend this notion into third-generation CPTED which acknowledges that these strategies need to create inclusive and liveable spaces that meet higher order needs such as belonging, esteem and self-actualization.

If the focus of environmental criminology is to create specific and effective prevention strategies, these strategies need to be inclusive of all people. Thus, the use of target hardening alone, while ignoring local context and social needs can not only lead to spatialized victimization (Petty, 2016), but spaces that discourage connection and encourage further offending (Raymen, 2016). For example, planning methodologies such as SafeGrowth® integrate the learnings of environmental criminology with social and contextual concerns to create inclusive strategies with and by local residents that shift away from crime control for the few and towards inclusion, safety and most importantly liveability for the many (Saville, 2017).

Environmental criminology and victimization: where we need to go

Having reviewed the spatial and temporal patterns of criminal victimization and how a myopic application of environmental criminology and crime prevention through environmental design can lead to subsequent victimization, particularly of marginalized people, we now turn to where we believe the field needs to go in order to move forward, particularly in the context of the study of victimization.

First and foremost, the focus on offenders and places clearly needs to be supplemented with victim studies. As outlined above, victimization is rarely the sole focus of study within environmental criminology, often only being tangential in the research. The research on the journey to victimization and mobility triangles, for examples, tell us how far and in which areas people are victimized, but what is the impact of these spatial and temporal dynamics? Repeat and near-repeat victimization identifies the spatial and temporal patterns of re-victimization, likely explanations for these patterns, and strategies to reduce this re-victimization, but what is the impact of these repeat victims? How does this impact fear and what are the implications of changes to routine activities if they are even possible? These types of directions for future research are necessary to move the field of environmental criminology forward.

In the context of crime prevention, environmental criminologists need to move beyond considering places without considering their broader social context. Not only is the broader social context consistent with the original work on crime prevention through environmental design (Jeffrey, 1971; Newman, 1972), but the empirical literature has shown that we must consider areas larger than micro-places to truly understand spatial patterns of crime (O’Brien et al., 2017; Schnell et al., 2017; Steenbeek & Weisburd, 2016)—this latter empirical result is not directly related to crime prevention but shows that focussing solely on places means valuable information is lost regarding these patterns. As we have discussed, there are already efforts to integrate the social context into crime prevention research (Saville & Cleveland, 2013), however this needs to be expanded in environmental criminology more broadly.

Additionally, in the context of crime displacement that may result from a crime prevention initiative, much of the literature in this area shows that crime does not displace or that any displaced crime is less than the volume of crime reduced in other places (Weisburd et al., 2006). However, as shown by Hodgkinson et al. (2020), crime displacement may occur further away than originally thought or measured, and that displaced crime may lead to more harmful victimizations. Clearly, more work is necessary in this area.

Lastly, research within environmental criminology and crime prevention focuses on urban settings. Patterns of crime in rural areas are different than urban areas (Donnermeyer, 2016) and need to be understood to reduce victimization in those contexts. Though populations in most countries continue to move into urban spaces, even in the United States approximately 20 percent (60 million people) live in rural areas.4 This is an area of research that could have implications for millions of people even in the small number of countries typically analysed in the field of environmental criminology—billions globally.

Finally, to move forward in expanding victimological research within environmental criminological theories, this research requires better data and rigorous methodologies. Most of the research in spatial-temporal criminology uses some form of police data because these data contain spatial and temporal information for relatively larger (urban) areas such that spatial and temporal crime patterns can be identified. However, in order to generate better research within these areas on the topic of victimization, environmental criminologists need to gather data from individuals again. In the context of victimization, this means talking to, listening to, and advocating for the victims of crime generating knowledge from spatial and temporal perspectives to reduce (the impacts of) victimization. The field of environmental criminology has a lot to offer victimization studies, but in order to do so we must shift our focus to “suitable targets.”


Ackerman, J. M., & Rossmo, D. K. (2015). How far to travel? A multilevel analysisof the residence-to-crime distance. Journal of Quantitative Criminology, 31(2),237 – 262.

Amir, M. (1971). Patterns of forcible rape. Chicago, IL: University of Chicago Press.

Andresen, M.A. (2011). The ambient population and crime analysis. ProfessionalGeographer, 63(2), 193 – 212.

Andresen, M.A. (2020). Environmental criminology: Evolution, theory, and practice (2nded.). New York, NY: Routledge.

Andresen, M. A., & Malleson, N. (2013). Crime seasonality and its variations acrossspace. Applied Geography, 43, 25-35.

Andresen, M. A., & Malleson, N. (2015). Intra-week spatial-temporal patterns of crime.Crime Science, 4(1), 1-11.

Andresen, M. A., Felson, M., & Frank, R. (2012). The geometry of offending andvictimization. Canadian Journal of Criminology and Criminal Justice, 54(4), 495 - 510.

Andresen, M. A., Frank, R., & Felson, M. (2014). Age and the distance to crime. Criminology & Criminal Justice, 14(3), 314 - 333.

Barr, R., & Pease, K. (1990). Crime placement, displacement and deflection. Crime and Justice: A Review of Research, 12, 277 – 318.

Beauregard, E., Rossmo, D. K., & Proulx, J. (2007). A descriptive model of the hunting process of serial sex offenders: A rational choice perspective. Journal of Family Violence, 22(6), 449 – 463.

Bernasco, W. (2008). Them again? Same offender involvement in repeat and near repeat burglaries. European Journal of Criminology, 5(4), 411 – 431.

Block, R., Galary, A., & Brice, D. (2007). The journey to crime: Victims and offenders converge in violent index offences in Chicago. Security Journal, 20(2), 123 –137.

Bowers, K. J., & Johnson, S. D. (2004). Who commits near repeats? A test of the boost explanation. Western Criminology Review, 5(3), 12 – 24.

Bowers, K. J., & Johnson, S. D. (2005). Domestic burglary repeats and space-time clusters: The dimensions of risk. European Journal of Criminology, 2(1), 67 – 92.

Brantingham, P. J. and Brantingham. P. L. (1981a). Introduction: The dimensions of crime. In Brantingham, P. J., & Brantingham, P. L. (eds), Environmental criminology (pp. 7 – 26). Prospect Heights IL, Waveland Press.

Brantingham, P. L., & Brantingham, P. J. (1981b). Notes on the geometry of crime. In Brantingham, P. J., & Brantingham, P. L. (eds), Environmental criminology (pp. 27 – 54). Prospect Heights IL, Waveland Press.

Brantingham, P. L., & Brantingham, P. J. (1993a). Nodes, paths and edges: Considerations on the complexity of crime and the physical environment. Journal of Environmental Psychology, 13(1), 3 – 28.

Brantingham, P. L., & Brantingham, P. J. (1993b). Environment, routine, and situation: Toward a pattern theory of crime. In Clarke, R. V., & Felson, M (eds), Routine activity and rational choice, volume 5 (pp. 259 – 294). New Brunswick, NJ: Transaction publishers.

Brantingham, P. L., & Brantingham, P. J. (1995). The criminality of place: Crime generators and crime attractors. European Journal on Criminal Policy and Research, 3(3), 5-26.

Brantingham, P. J., & Faust, F. L. (1976). A conceptual model of crime-prevention. Crime and Delinquency, 22(3), 284 – 296.

Breetzke, G. D., & Cohn, E. G. (2012). Seasonal assault and neighborhood deprivation in South Africa: Some preliminary findings. Environment & Behavior, 44(5), 641 – 667.

Brimicombe, A. (2012). Did GIS start a crime wave? SatNav theft and its implications for geo-information engineering. Professional Geographer, 64(3), 430 – 445.

Brunsdon, C., Corcoran, J., Higgs, G., & Ware, A. (2009). The influence of weather on local geographical patterns of police calls for service. Environment and Planning B: Planning and Design, 36(5), 906 – 926.

Burgess, E. W. (1925). Can neighborhood work have a scientific basis? In R.E. Park, E.W. Burgess, & R.D. McKenzie (Eds.), The City: Suggestions for investigation of human behaviors in the urban environment (pp. 142 – 155). Chicago, IL: University of Chicago Press.

Capone, D. L., & Nichols Jr., W. W. (1976). Urban structure and criminal mobility. American Behavioral Scientist, 20(2), 199 – 213.

Ceccato, V. (2005). Homicide in San Paulo, Brazil: Assessing spatial-temporal and weather variations. Journal of Environmental Psychology, 25(3), 307 – 321.

Ceccato, V., & Uittenbogaard, A. C. (2014). Space–time dynamics of crime in transport nodes. Annals of the Association of American Geographers, 104(1), 131-150.

Chopin, J., Caneppele, S., & Beauregard, E. (2019). An analysis of mobility patterns in sexual homicide. Homicide Studies, DOI: 10.1177/1088767919884601.

City of Saskatoon (2010). Safe growth and crime prevention through environmental design (CPTED). Saskatoon, SK: City of Saskatoon.

Clarke, R. V. G. (1980). Situational crime prevention: Theory and practice. British Journal of Criminology, 20(2), 136 – 147.

Clarke, R. V. (1983). Situational crime prevention: Its theoretical basis and practical scope. Crime and Justice: An Annual Review of Research, 4, 225 – 256.

Clarke, R. V. (1992). Situational crime prevention: Successful case studies. New York, NY: Harrow and Heston.

Clarke, R. V. (1997). Situational Crime Prevention: Successful case studies (2nd ed.). Monsey, NY: Criminal Justice Press.

Clarke, R. V. (2012). Opportunity makes the thief. Really? And so what? Crime Science, 1, Article 3.

Clarke, R. V., & Cornish, D. B. (1985). Modeling offenders’ decisions: A framework for research and policy. Crime and Justice: An Annual Review of Research, 6, 147 – 185.

Cohen, L. E., & Felson, M. (1979). Social change and crime rate trends: A routine activity approach. American Sociological Review, 44(4), 588 – 608.

Cohn, E. G., & Rotton, J. (2000). Weather, seasonal trends and property crimes in Minneapolis, 1987 – 1988: A moderator-variable time-series analysis of routine activities. Journal of Environmental Psychology, 20(3), 257 – 272.

Corcoran, J., Zahnow, R., Kimpton, A., Wickes, R., & Brunsdon, C. (2019). The temporality of place: Constructing a temporal typology of crime in commercial precincts. Environment and Planning B: Urban Analytics and City Science. DOI:

Cornish, D. B., & Clarke, R. V. (1986). The reasoning criminal: Rational choice perspectives on offending. New York, NY: Springer-Verlag.

Cosaro, N., Pizarro, J. M., & Shafer, J. (2017). The influence of planned aggression on the journey to homicide: An examination across typology classifications. Homicide Studies, 21(3), 179 – 198.

Costello, A, & Wiles, P. (2001). GIS and the journey to crime: An analysis of patterns in South Yorkshire. In A. Hirschfield & K. Bowers (eds), Mapping and analysing crime data: Lessons from research and practice (pp. 27 – 60). London, UK: Taylor and Francis.

Cozens, P., & Love, T. (2017, March 29). The dark side of Crime Prevention Through Environmental Design (CPTED). Oxford Research Encyclopedia of Criminology. Retrieved 02 April 2020, from

Donnermeyer, J. F. (2016). The Routledge international handbook of rural criminology.New York, NY: Routledge.

Drawve, G., Walker, J. T., & Felson, M. (2015). Juvenile offenders: an examination of distance-to-crime and crime clusters. Cartography and Geographic Information Science, 42(2), 122 – 133.

Eck, J. E. (1993). The threat of crime displacement. Criminal Justice Abstracts, 25(3), 527 – 546.

Farrell, G., & Bouloukos, A. C. (2001). International overview: A cross-national comparison of rates of repeat victimization. Crime Prevention Studies, 12, 5 – 25.

Farrell, G., & Pease, K. (1993). Once bitten, twice bitten: Repeat victimization and itsimplications for crime prevention. London, UK: Police Research Group, Home Office.

Farrell, G., & Pease, K. (1994). Crime seasonality: Domestic disputes and residential burglary in Mereyside 1988-90. British Journal of Criminology, 34(4), 487 – 498.

Farrell, G., Phillips, C., & Pease, K. (1995). Like taking candy: Why does repeat victimization occur? British Journal of Criminology, 35(3), 384 – 399.

Farrell, G., Tilley, N., Tseloni, A., & Mailley, J. (2014). Why the crime drop? Crime and Justice: A review of Research, 43(1), 421 – 490.

Felson, M., & Clarke, R. V. (1998). Opportunity makes the thief: Practical theory for crime prevention. London, UK: Home Office, Policing and Reducing Crime Unit Research, Development and Statistics Directorate.

Felson, M., & Poulsen, E. (2003). Simple indicators of crime by time of day. International Journal of Forecasting, 19(4), 595 – 601.

Field, S. (1992). The effect of temperature on crime. British Journal of Criminology, 32(3), 340 – 351.

Frank, R., Andresen, M. A., & Felson, M. (2012). The geodiversity of crime: evidence from British Columbia. Applied Geography, 34, 180 – 188.

Gabor, T., & Gottheil, E. (1984). Offender characteristics and spatial mobility: An empirical study and some policy implications. Canadian Journal of Criminology, 26(3), 267 – 281.

Groff, E. R., & McEwen, T. (2007). Integrating distance into mobility triangle typologies. Social Science Computer Review, 25(2), 210 – 238.

Guerette, R. T., & Bowers, K. J. (2009). Assessing the extent of crime displacement and diffusion of benefits: A review of situational crime prevention evaluations. Criminology, 47(4), 1331 - 1368.

Guerry, A-M. (1832). La statistique compare de l’état de l’instruction et du nombre des crimes. Revue Encyclopédique, 55, 414 – 424.

Guerry, A-M. (1833). Essai sur la statistique morale de la France. Paris: Crochard.

Harvey, D. (2010). A brief history of neoliberalism. New York, NY: Oxford University Press.

Haberman, C. P., & Ratcliffe, J.H. (2012). The predictive policing challenges of near repeat armed street robberies. Policing: A Journal of Policy and Practice, 6(2), 151 – 166.

Harries, K. D., & Stadler, S. (1983). Determinism revisited: Assault and heat stress in Dallas. Environment & Behavior, 15(2), 235 – 256.

Harries, K. D., Stadler, S., & Zdorkowski, R. (1984). Seasonality and assault: Explorations in inter-neighborhood variation, Dallas 1980. Annals of the Association of American Geographers, 74(4), 590 – 604.

Hesseling, R. B. P. (1994). Displacement: a review of the empirical literature. Crime Prevention Studies, 3, 197 – 230.

Hodgkinson, T., Saville, G., & Andresen, M.A. (2020). The diffusion of detriment: Tracking displacement using a city-wide mixed methods approach. British Journal of Criminology, 60(1), 198 – 218.

Jeffery, C. R. (1969). Crime prevention and control through environmental engineering. Criminologica, 7(3), 35 – 58.

Jeffery, C. R. (1971) Crime prevention through environmental design. Beverly Hills, CA: Sage Publications.

Johnson, S. D., Bernasco, W., Bowers, K. J., Elffers, H., Ratcliffe, J., Rengert, G., & Townsley, M. (2007). Space-time patterns of risk: A cross national assessment of residential burglary victimization. Journal of Quantitative Criminology, 23(3), 201 – 219.

Johnson, S. D., Summers, L., & Pease, K. (2009). Offender as forager? A direct test of the boost account of victimization. Journal of Quantitative Criminology, 25(2), 181 – 200.

Kennedy, L. W., & Forde, D. R. (1990). Routine activities and crime: an analysis of victimization in Canada. Criminology, 28(1), 137 – 152.

Landau, S. F., & Fridman, D. (1993). The seasonality of violent crime: The case of robbery and homicide in Israel. Journal of Research in Crime and Delinquency, 30(2), 163 – 191.

Lind, A. W. (1930). Some ecological patterns of community disorganization in Honolulu. American Journal of Sociology, 36(2), 206 – 220.

Mailley, J., Garciab, R., Whitehead, S., & Farrell, G. (2008). Phone theft index. Security Journal, 21(3), 212 – 227.

Melo, S. N., Andresen, M. A., & Matias, L.F. (2018). Repeat and near-repeat victimization in Campinas, Brazil: New explanations from the Global South. Security Journal, 31(1), 364 - 380.

Mihinjac, M., & Saville, G. (2019). Third-generation Crime Prevention Through Environmental Design (CPTED). Social Sciences, 8(6), 182.

Morgan, F. (2001). Repeat burglary in a Perth suburb: Indicator of short-term or long-term risk? Crime Prevention Studies, 12, 83 – 118.

Morselli, C., & Royer, M-N. (2008). Criminal mobility and criminal achievement. Journal of Research in Crime and Delinquency, 45(1), 4 – 21.

Newman, O. (1972) Defensible space: Crime prevention through urban design. New York, NY: Macmillan.

Newton, A., & Hirschfield, A. (2009). Measuring violence in and around licensed premises: The need for a better evidence base. Crime Prevention & Community Safety, 11(3), 171-188.

Normandeau, A. (1968). Patterns in robbery. Criminology, 6(3), 2 – 16.

O’Brien, D. T., & Winship, C. (2017). The gains of greater granularity: The presence and persistence of problem properties in urban neighborhoods. Journal of Quantitative Criminology, 33(3), 649 – 675.

Petty, J. (2016). The London spikes controversy: Homelessness, urban securitisation and the question of ‘hostile architecture’. International Journal for Crime, Justice and Social Democracy, 5(1), 67 – 81.

Quetelet, L. A. J. ([1831] 1984). Research on the propensity for crime at different ages (translated by S. F. Sylvester). Cincinnati, OH: Anderson Publishing.

Quetelet, L. A. J. (1842). A Treatise on man and the development of his faculties. Edinburgh: W. and R. Chambers.

Rand. A. (1986). Mobility triangles. In R. M. Figlio, S. Hakim, & G. F. Rengert (Eds.), Metropolitan crime patterns (pp. 117 – 126). Monsey, NY: Criminal Justice Press.

Ratcliffe, J. H., & Rengert, G. F. (2008). Near repeat patterns in Philadelphia shootings. Security Journal, 21(1-2), 58 – 76.

Raymen, T. (2016). Designing-in crime by designing-out the social? Situational crime prevention and the intensification of harmful subjectivities. British Journal of Criminology, 56(3), 497–514.

Rengert, G. F., Piquero, A., & Jones, P. (1999). Distance decay re-examined. Criminology, 37(2), 427 – 445.

Rotton, J., & Cohn, E. G. (2003). Global warming and U.S. crime rates: An application of routine activity theory. Environment & Behavior, 35(6), 802 – 825.

Saville, G. (2017). The missing link in CPTED theory. In Teasdale, B., & Bradley, M. S. (Eds.), Preventing crime and violence (pp. 297 – 307). Cham, Switzerland: Springer International Publishing.

Saville, G., & Cleveland, G. (2013). Second-generation CPTED: Rise and fall of opportunity theory. In Atlas, R. I. (Ed.), 21st century security and CPTED: Designing for critical infrastructure protection and crime prevention (pp. 91 – 106). Boca Raton, FL: CRC Press.

Schnell, C., Braga, A. A., & Piza, E. L. (2017). The influence of community areas, neighborhood clusters, and street segments on the spatial variability of violent crime in Chicago. Journal of Quantitative Criminology, 33(3), 469 – 496.

Semmens, N., Dillane, J., & Ditton, J. (2002). Preliminary findings on seasonality and the fear of crime: A research note. British Journal of Criminology, 42(4), 798 – 806.

Shaw, C. R., & McKay, H. D. (1942). Juvenile delinquency and urban areas: A study of rates of delinquency in relation to differential characteristics of local communities in American cities. Chicago, IL: University of Chicago Press.

Simon, H. A. (1957). Models of man, social and rational: Mathematical essays on rational human behavior in a social setting. New York, NY: John Wiley & Sons.

Simon, H. A. (1982). Models of bounded rationality (Three Volumes). Cambridge, MA: MIT Press.

Sleiman, M., & Lippert, R. (2010). Downtown ambassadors, police relations and ‘clean and safe’ security. Policing & Society, 20(3), 316-335.

Steenbeek, W., & Weisburd, D. (2016). Where the action is in crime? An examination of variability of crime across different spatial units in The Hague, 2001–2009. Journal of Quantitative Criminology, 32(3), 449 – 469.

Tita, G., & Griffiths, E. (2005). Traveling to violence: the case for a mobility-based spatial typology of homicide. Journal of Research in Crime and Delinquency, 42(3), 275 – 308.

Tompson, L., & Townsley, M. (2010). (Looking) back to the future: Using space-time patterns to better predict the location of street crime. International Journal of Police Science & Management, 12(1), 23 – 40.

Townsley, M., & Sidebottom, A. (2010). All offenders are equal, but some are more equal than others: Variation in journeys to crime between offenders. Criminology, 48(3), 897 – 917.

Townsley, M., Homel, R., & Chaseling, J. (2003). Infectious burglaries: A test of the near repeat hypothesis. British Journal of Criminology, 43(3), 615 – 633.

Townsley, M., Johnson, S. D., & Ratcliffe, J. H. (2008). Space time dynamics of insurgent activity in Iraq. Security Journal, 21(3), 139 – 146.

Trickett, A., Osborn, D. Seymour, J., & Pease, K. (1992). What is different about high crime areas? British Journal of Criminology, 32(1), 81 – 90.

Uittenbogaard, A., & Ceccato, V. (2012). Space-time clusters of crime in Stockholm, Sweden. Review of European Studies, 4(5), 148.

van Koppen, P. J., & de Keijser, J. W. (1997). Desisting distance decay: On the aggregation of individual crime trips. Criminology, 35(3), 505 – 515.

van Koppen, P. J., & Jansen, R. W. J. (1999). The time to rob: Variations in time of number of commercial robberies. Journal of Research in Crime and Delinquency, 36(1), 7 – 29.

Vandeviver, C., van Daele, S., & vander Beken, T. (2015). What makes long crime trips worth undertaking? Balancing costs and benefits in burglars’ journey to crime. British Journal of Criminology, 55(2), 399 – 420.

Vaughan, A. D., Hewitt, A. N., Hodgkinson, T., Andresen, M. A., & Verdun-Jones, S. (2019). Temporal patterns of Mental Health Act calls to the police. Policing: A Journal of Policy and Practice, 13(2), 172 – 185.

Waller, I. (2014). Smarter crime control: A guide to a safer future for citizens, communities, and politicians. Lanham, MD: Roman & Littlefield.

Weisburd, D., Wyckoff, L. A., Ready, J., Eck, J. E., Hinkle, J. C., & Gajewski, F. (2006). Does crime just move around the corner? A controlled study of spatial displacement and diffusion of crime control benefits. Criminology, 44(3), 549 – 591.

White, R. C. (1932). The relation of felonies to environmental factors in Indianapolis. Social Forces, 10(4), 498 – 509.

Whitehead, S., & Farrell, G. (2008). Anticipating mobile phone ‘smart wallet’ crime: Policing and corporate social responsibility. Policing: a Journal of Policy and Practice, 2(2), 210 – 217.

Wiles, P., & Costello, A. (2000). The ‘road to nowhere’: The evidence for traveling criminals. Home Office Research Study 207. London, UK: Research, Development and Statistics Directorate.

Wood, D. M., & Mackinnon, D. (2019). Partial platforms and oligoptic surveillance in the smart city. Surveillance & Society17(1/2), 176-182.

Zipf, G. (1949). Human behavior and the principle of least effort: An introduction to human ecology. Cambridge, MA: Addison-Wesley Press.

No comments here
Why not start the discussion?