Effective Crime Prevention Research Articles

Cascades: war, crime, peace, and crime prevention: reaction essay

ABSTRACT In “Cascades: War, crime, peace and crime prevention,“ Braithwaite has offered a significant theoretical contribution. As in his prior work, this theory integrates several theoretical perspectives. He draws upon theory and research in war and peace, crime causation, and crime prevention. He also offers insights ranging from macro to micro levels. This paper responds to “Cascades” by noting the issues the theory seeks to explain. Particular emphasis is placed on crime prevention with the hope that research and practice can build upon Cascades to make more substantial and sustained crime prevention effects. The paper highlights a number of issues for future scholars to address within the Cascades framework.

Awareness of crime prevention effects associated with a wall removal project in Seoul

ABSTRACTThis study investigated Groups' awareness of how wall removal affects crime prevention. Group 1 comprised of burglars, Group 2 of non-residents who have not removed walls, and Group 3 of residents who have removed walls and are living in wall removal project areas. First, we examine differences in awareness between Groups 1 and 2 regarding ease of crime in relation to the presence or absence of a wall. Second, we examined the awareness levels of Groups 1 and 2 in relation to important factors considered by intruders when committing a burglary. Finally, we examined how wall removal reduces the fear of crime in Groups 2 and 3. Group 1 believed a house with a wall was an easier target for crime, but Group 2, comprised of residents who did not perform wall removal, had contrary opinions. Group 2 believed that wall removal did not reduce the fear of crime, unlike Group 3. These results indicate that Group 2 has negative perceptions of wall removal in the context of crime prevention, which stems from the common belief that a wall will protect a house from outside threats. Therefore, changes in mindset are needed to create safe environments in detached housing areas.

A winning BID? The effects of a BID-inspired property owner collaboration on neighbourhood crime rates in Malmö, Sweden

The business improvement district (BID) model has spread rapidly worldwide and has recently caught the eye of Swedish politicians and practitioners as a feasible approach to reduce crime in urban neighbourhoods. Research on the crime-preventive effects of BIDs is, however, limited to a handful of US studies, and there is a lack of research from European contexts. The aim of the present study is to fill gaps in knowledge by examining the crime-preventive effects of a BID-inspired property owner collaboration (BID-Malmo) implemented in a residential neighbourhood in Malmo, Sweden. Based on the use of a difference-in-difference estimator and weighted displacement quotients, our results demonstrate a significant reduction in crimes reported to the police in the intervention neighbourhood relative to control areas, with signs of spatial diffusion of benefits rather than displacement of crime to adjacent areas. This result is, however, mainly driven by a decrease in reported incidents of vandalism, while no effect is observed in regard to violent crime in public places. Implications of the findings and further research are discussed.

Artificial Intelligence Techniques and External Factors used in Crime Forecasting in Violence and Property: A Review

Crime forecasting is beneficial in providing useful information to authorities in planning effective crime prevention measures. The two types of analysis used in crime forecasting are univariate and multivariate. Comparatively, multivariate analysis provides better forecasting accuracy because of its ability to discover crime patterns not previously seen. Crime is strongly influenced by several external factors, including economic, social and demographic. Hence, an analysis is needed to identify and select relevant factors that influence crime and can later be used to improve forecasting accuracy. Neighborhood Component Analysis (NCA) is a reliable form of analysis for identifying significant relationships between factors and crime data. Several model types have been introduced in crime forecasting, including statistical and artificial intelligence models. Recently, the artificial intelligence model has come into favour because of its ability to handle nonlinearity patterns in crime data well. Within the artificial intelligence model, Gradient Tree Boosting (GTB) shows good performance as it produces a robust and reliable forecast result. GTB uses least square function as a loss function for error fitting during training. Findings show that, in addition to using least square function, implementing other standard mathematical functions that fit to the crime data increases forecasting accuracy. In other cases, both NCA and GTB are sensitive to parameters input. Dragonfly Algorithm (DA) is a promising, nature inspired metaheuristic algorithm that is capable of solving such problems.

Homicide as a function of city block layout: Mexico City as case study

ABSTRACTFocused on Mexico City, this article offers a seminal examination of the relationship between block layout and intentional homicide. The authors applied multilevel random-intercept negative binomial models to assess the contribution of block layout characteristics to homicide counts while controlling for other factors related to the physical environment and socioeconomic disadvantage. The assessment finds that container-type city blocks registered the highest likelihood of homicide incidence. It also shows that blocks with metro stations also had a statistically higher likelihood of homicide incidence. By contrast, building-type blocks exhibited the lowest likelihood of recording a homicide. Ultimately, the physical environment model provided a better fit to the data than the socioeconomic disadvantage model. The main conclusion is that homicide incidence in Mexico City may be more a function of block layout than socioeconomic composition. One implication is that urban planning may have more potent crime prevention effects than widely believed.

A forrónyomos felderítés vezetése, irányítása megújításának lehetséges irányai

A tanulmányom elkészítésére azért vállalkoztam, mivel közel 20 éves szakmai tapasztalattal és háttérrel rendelkezem ezen a területen, illetve az eltelt évek alatt sok olyan módszert és eljárást vezettek be ezen a kriminalisztikai területen, amelyek nagyban hozzájárulhatnak a felderítés e speciális formájának továbbfejlesztéséhez és korszerűsítéséhez. A korszerű forrónyomos felderítés ismerete és alkalmazása rendkívül fontos a hatékony bűnüldözés során. A felderítés első 24 órája kulcsfontosságú az elkövető beazonosítása, felderítése és esetleges elfogása szempontjából. Tanulmányomban megvizsgáltam a témához kapcsolódó legfontosabb rendszertani fogalmakat: felderítés, forrónyomos felderítés, üldözés, nyomon üldözés, nyomozás és körözés. A témával kapcsolatos jogi szabályozást és annak rendszerét is vizsgálat alá vontam, az egyes fontosabb vonatkozó hatályos jogszabályokat külön is részletesen áttekintettem. Végezetül a leírtak és személyes tapasztalataim alapján olyan javaslatokat fogalmaztam meg, amelyek a forrónyomos felderítést még hatékonyabbá és még inkább reagálókészebbé tehetik.

“Translational Criminology” in action: a national survey of TSA’s Playbook implementation at U.S. Airports

Security at U.S. airports has been a key priority since September 11, 2001. The Transportation Security Administration (TSA) was established shortly thereafter to oversee aviation security operations. However, there have been few rigorous evaluations of airport security strategies, and even less is known about how they are implemented in practice. As part of a larger study that used a “translational criminology” approach to map TSA’s “Playbook” security strategy onto effective policing and crime prevention practices, we conducted a first-of-its-kind survey of TSA personnel at U.S. airports to understand how the Playbook was implemented in practice. We found that while the Playbook was well implemented, adherence to its core components—targeted, focused prevention strategies and multi-agency collaboration—was varied. We conclude with research-informed recommendations for future program development.

Research on the Urban Spatial Crime Prevention Effect Analysis of CCTV Auxiliary Facilities through Citizen Perception Survey

Research on the Urban Spatial Crime Prevention Effect Analysis of CCTV Auxiliary Facilities through Citizen Perception Survey

Private Security and Closed-Circuit Television (CCTV) Surveillance: A Systematic Review of Function and Performance

Private security personnel play an important but largely overlooked role in the operation of closed-circuit television (CCTV) surveillance to prevent crime in public and private areas. This role can take a number of forms, including active monitoring of cameras. Drawing upon a global database of CCTV evaluations ( N = 165), this article examines the function and performance of private security personnel as related to the effectiveness of CCTV. Findings indicate that CCTV schemes operated by private security personnel generated larger crime prevention effects than those operated by police or those using a mix of police and security personnel. Policy and research implications are discussed.

Residential property and break-ins

PurposeThe purpose of this paper is to examine realtors and residents’ perceptions of the effectiveness of Crime Prevention through Environmental Design (CPTED) in reducing night-time and daytime break-ins in residential estate.Design/methodology/approachThe study adopted case study methods. Two residential estates (one at inner and the other at outer city) were selected as cases of the study. Data were collected from two sets of respondents: realtors and tenants. In the realtors’ cluster, all real estate and property development companies were sampled since the population is very small. Systematic sampling technique was used to select residents. Respondents were asked to answer closed-ended questions on socio-economic and demographic characteristics, perception of property crime, spending on CPTED and effectiveness of CPTED. Data were analyzed using the descriptive and inferential statistics.FindingsFindings disclose that more than half of the residents of inner and outer city had been victims of housebreaks and these incidences are expected to increase in the nearest future. To reduce break-ins, findings show that realtors and residents have spent on both formal and informal surveillance with emphasis on ensuring visual control over premises. Furthermore, respondents confirm the effectiveness of CPTED in deterring break-ins. The study establishes variation in the realtors and tenants’ perception of break-ins as spending on CPTED strategies vary between them, with locations and types of properties.Practical implicationsSocial and human factors remain very important as far as the prevention of break-ins is concerned. These should be taken into considerations when improving CPTED approach in the future. Besides, adequate attentions should be given to daytime break-in. Nonetheless, night-time break-ins should not be neglected. Furthermore, the study emphasizes the importance of visible, clean and well-lit premises as ways of reducing break-ins. It is therefore suggested that residential properties should be well lit at nights, while CCTV and security personnel be positioned in strategic places and within security viewing range so as to send fast alerts to the nearest police stations in the cases of break-in(s).Originality/valueVery few studies on effectiveness of CPTED have mainly concentrated on how CPTED works in residential estates. No study till date, have explored how realtors perceive CPTED in preventing break-ins. Besides, this study contributes to existing literature having revealed variation in the realtors and tenants’ spending on CPTED on the basis of property location and types of residential properties.

Hot spots policing of small geographic areas effects on crime.

In recent years, crime scholars and practitioners have pointed to the potential benefits of focusing crime prevention efforts on crime places. A number of studies suggest that there is significant clustering of crime in small places, or "hot spots," that generate half of all criminal events. Researchers have argued that many crime problems can be reduced more efficiently if police officers focused their attention to these deviant places. The appeal of focusing limited resources on a small number of high-activity crime places is straightforward. If crime can be prevented at these hot spots, then citywide crime totals could be reduced. To assess the effects of focused police crime prevention interventions at crime hot spots. The review also examined whether focused police actions at specific locations result in crime displacement (i.e., crime moving around the corner) or diffusion (i.e., crime reduction in surrounding areas) of crime control benefits. A keyword search was performed on 15 abstract databases. Bibliographies of past narrative and empirical reviews of literature that examined the effectiveness of police crime control programs were reviewed and forward searches for works that cited seminal hot spots policing studies were performed. Bibliographies of past completed Campbell systematic reviews of police crime prevention efforts were reviewed and hand searches of leading journals in the field were completed. Experts in the field were consulted and relevant citations were obtained. To be eligible for this review, interventions used to control crime hot spots were limited to police-led prevention efforts. Suitable police-led crime prevention efforts included traditional tactics such as directed patrol and heightened levels of traffic enforcement as well as alternative strategies such as aggressive disorder enforcement and problem-oriented policing. Studies that used randomized controlled experimental or quasiexperimental designs were selected. The units of analysis were limited to crime hot spots or high-activity crime "places" rather than larger areas such as neighborhoods. The control group in each study received routine levels of traditional police crime prevention tactics. Sixty-five studies containing 78 tests of hot spots policing interventions were identified and full narratives of these studies were reported. Twenty-seven of the selected studies used randomized experimental designs and 38 used quasiexperimental designs. A formal meta-analysis was conducted to determine the crime prevention effects in the eligible studies. Random effects models were used to calculate mean effect sizes. Sixty-two of 78 tests of hot spots policing interventions reported noteworthy crime and disorder reductions. The meta-analysis of key reported outcome measures revealed a small statistically significant mean effect size favoring the effects of hot spots policing in reducing crime outcomes at treatment places relative to control places. The effect was smaller for randomized designs but still statistically significant and positive. When displacement and diffusion effects were measured, a diffusion of crime prevention benefits was associated with hot spots policing. The extant evaluation research suggests that hot spots policing is an effective crime prevention strategy. The research also suggests that focusing police efforts on high-activity crime places does not inevitably lead to crime displacement; rather, crime control benefits may diffuse into the areas immediately surrounding the targeted locations.

A Study on the Crime Prevention Effect of Improved Street Lighting

연구의 목적은 셉테드에 대한 관심의 증가로 향후 많은 예산의 투입이 예상되므로, 범죄예방이라는 근본적인 목표의 효과적인 달성을 위해 전략별 효과요인에 대한 검증을 순차적으로 입증함으로써 투입전략의 기능과 효과를 체계화하여 효율적인 활용방안을 모색하고자 하는 것이다. 연구 방법은 셉테드의 기본원리와 전략에 관한 이론적 문헌조사를 진행하였다. 연구대상지역인 서울시 K구의 2014년부터 2017년까지의 조명개선 목록을 자치단체의 협조로 수집하였으며, 관할경찰서 관내 2013년부터 2015년 까지 발생한 5대 범죄의 유형, 발생일시, 발생장소 등 개인정보를 제외한 분석항목을 중심으로 수집하였다. 분석방법은 조명개선사업이 추진된 구역과 주변의 조명개선사업이 추진되지 않은 구역의 위치, 규모 등을 고려하여 총 7개 의 구역을 분석대상지역으로 선정한 후 GIS 프로그램과 Odds Ratio 분석방법 을 활용하여 사업 전ㆍ후 5대 범죄 전체 발생건수의 변화와 범죄유형별 발생 건수의 변화를 차례로 분석하여, 실험구역과 통제구역 간의 발생건수 변화를 비교하였다. 연구결과는 첫째, 개선된 조명이 5대 범죄를 종합적으로 예방하는데 효과가 있었다. 둘째, 조명개선 사업은 절도범죄에 대해서는 매우 효과가 큰 것으로 확인되었고, 폭력은 미미하지만 효과를 인정할 수 있으나, 성폭력은 구역 별 발생건수가 적어 예방효과에 대한 판단을 유보하였다. 셋째, 구역별로는 총 7개의 구역 중 5개 구역에서 범죄예방효과가 있음을 확인하였다. 특히 GIS를 이용한 범죄위치분석에서 사업이전과 사업이후의 범죄발생위치 분포가 대상구역의 중심지에서 가장자리 또는 통제지역과의 경계부로 이동되는 것을 확인할 수 있었다.In consideration of increasing interests in CPTED and enormous resources expected to invest for such strategies, this study mainly analyzed the effectiveness of one type of crime prevention strategies, improved street LED lighting. In particular, this study examined more cost-effective strategies to achieve the fundamental goal of crime prevention and to find ways to utilize them efficiently. Methodologically, this study reviewed a volume of literature on the basic principles and strategies of the CPTED. Then, this study collected the list of improved lighting between 2014 to 2017 and crime data (homicide, robbery, sexual assault, theft, violent assault) between 2013 and 2015 in K District, Seoul. These datasets include locations, types, and date of each lighting and crime. Based on this information, this study obtained 7 target areas where the improved lighting was geographically concentrated and 7 control areas in the vicinity of target areas with similar sizes. Using the QGIS program and the odds ratio analysis method, this study examined the changes in the total number of crimes before and after the lighting improvement within the target and control area. This study found that improved lighting, in general, was effective in preventing the five major crimes altogether. Second, this study found differing effects of the improved lighting by different crime type and geographical area. For example, improved lighting was more effective for theft than violent assault. Also, the effect of improved lighting was found only within 5 target areas out of 7 areas. In more detail, this study found that distribution of crime became more concentrated in the edge or boundary of the target area, which indicates displacement of crime influenced by the improved lighting.

Hot spots policing and crime reduction: an update of an ongoing systematic review and meta-analysis

This updated systematic review assesses the effects of focused police crime prevention interventions at crime hot spots. The review also examined whether focused police actions at specific locations result in crime displacement or diffusion of crime control benefits. Systematic review protocols and conventions of the Campbell Collaboration were followed to identify eligible hot spots policing studies, and meta-analytic techniques were used to assess the impact of hot spots policing on crime and investigate the influence of moderating variables. The search strategies identified 65 studies containing 78 tests of hot spots policing interventions. Meta-analyses revealed a small statistically significant mean effect size favoring the effects of hot spots policing in reducing crime outcomes at treatment places relative to control places. Crime displacement and diffusion effects were measured in 40 tests. Meta-analyses favored a small statistically significant diffusion of crime control benefits over displacement. The extant evaluation research provides fairly robust evidence that hot spots policing is an effective crime prevention strategy. Focused police intervention at hot spot locations does not seem to result in the spatial displacement of crime into areas immediately surrounding targeted locations. Rather, crime control benefits seem to diffuse into proximate areas.

Parameter Optimization of Gradient Tree Boosting Using Dragonfly Algorithm in Crime Forecasting and Analysis

Crime forecasting and analysis are very important in predicting future crime patterns and beneficial to the authorities in planning effective crime prevention measures. One of the challenges found in crime analysis is the crime data itself as its form, representation and distribution are varied and unpredictable. To handle such data, most researchers have been focusing on applying various Artificial Intelligence (AI) techniques as an analytical tool. Among them, Gradient Tree Boosting (GTB) is a newly emerged AI technique for forecasting especially in crime analysis. GTB possesses a unique feature among other AI techniques which is its robustness towards any data representation and distribution. Subsequently, this study would like to adopt GTB in modelling crime rates based on 8 defined crime types. Similar to other AI techniques, GTB’s overall performance is heavily influenced by its input parameter configuration. To assess such a challenge, this study would like to propose a hybrid DA-GTB crime forecasting model that is equipped with a metaheuristic optimization algorithm called Dragonfly Algorithm (DA) in optimizing GTB’s three main parameters namely number of trees, size of individual trees and learning rate. From the experimental result obtained, the application of DA for parameter optimization yielded a positive impact in enhancing GTB forecasting performance as it produced the smallest error compared to non-optimized GTB. This indicates that the proposed model is able to perform well using time series data with a limited and small sample size.

Crime Prevention Effect of the Second Generation Crime Prevention through Environmental Design Project in South Korea: An Analysis

In Yeomni-dong Sogeum-gil, Korea, the first generation CPTED (Crime Prevention Through Environmental Design) project was implemented in 2012, focusing on improving the physical environment. Later, spreading nationwide, it was developed into the second generation CPTED, emphasizing the role of resident participation and improving upon the weak points of the first project. This study makes a comparative analysis of crime reduction and diffusion before and after the second generation CPTED conducted in S-dong, Dongjak-gu, Seoul, Korea, using crime location data to verify the crime prevention effect. Most previous studies on Korean CPTED projects sought verification through surveys that involved subjective opinions of the researchers or participants, creating the need for verification through quantitative and objective analysis based on crime data. This follow-up research examines the effects of the first generation CPTED Project by making an objective analysis of the differences in crime prevention effects between the first and the second project. Findings revealed that the second CPTED had a positive effect in reducing the rate of burglary and violent crime. The second generation CPTED project also led to the crime control benefits of crime diffusion, in contrast to the earlier project, where crime displacement occurred.

Policing and community safety in northern Canadian communities: challenges and opportunities for crime prevention

Although there is an emerging body of research literature on rural policing, less is known about policing in small communities in Canada’s territories populated largely by Indigenous peoples. These communities are often situated in geographically isolated areas, are subjected to harsh weather conditions, and may experience high rates of crime and disorder. Drawing on interviews conducted with RCMP officers in the two Canadian territories of Yukon and Nunavut, this paper examines the dynamics of policing in northern communities and how these might affect efforts to create sustainable, effective crime prevention initiatives. The findings reveal that geographic isolation, social problems, and history of distrust of the police, combined with the structure through which police services are delivered, present significant challenges to the development and sustainability of crime prevention initiatives. The unique environments of northern communities, however, also provide opportunities for the creation of police–community partnerships built on mutual trust that can provide the basis for effective crime prevention programs.

A novel pedestrian detection algorithm based on data fusion of face images

In order to facilitate effective crime prevention and to issue timely warnings for the sake of public security, it is important to pinpoint the accurate position of particular pedestrians in crowded areas. Face recognition is the most popular method to detect and track pedestrian movement. During the face recognition process, feature classification ability and reliability are determined by the feature extraction methods. The primary challenge for researchers is to obtain a stable result while the targeted face is subject to varying conditions—particularly of illumination. To address this issue, we propose a novel pedestrian detection algorithm with multisource face images, which involves a face recognition algorithm based on the conjugate orthonormalized partial least-squares regression analysis under a complex lighting environment. Statistical learning theory is a research specialization of machine learning, especially applicable to small samples. Building upon the theoretical principles used to solve small-sample statistical problems, a new hypothesis has been developed; using this concept, we integrate the conjugate orthonormalized partial least-squares regression with the revised support vector machine algorithm to undertake the solution of the facial recognition problem. The experimental result proves that our algorithm achieves better performance when compared with other state-of-the-art methodologies, both numerically and visually.

방범용 CCTV의 범죄예방효과에 대한 수사경찰의 인식: 인천지방경찰청 소속 경찰관을 중심으로

방범용 CCTV의 범죄예방효과에 대한 수사경찰의 인식: 인천지방경찰청 소속 경찰관을 중심으로

The mismeasure of Terry stops: Assessing the psychological and emotional harms of stop and frisk to individuals and communities.

In Terry v. Ohio, the US Supreme Court relied on a balancing test to uphold the reasonableness of the practice known as "stop and frisk," balancing the contribution of the practice to effective crime prevention and detection against the nature and quality of the intrusion to individual rights. In recent years, statistics have been powerfully deployed by legal scholars, jurists, and policymakers to challenge the assumption that stop and frisk leads to frequent discovery of contraband or other criminal behavior, and to address stark racial and ethnic disparities in the deployment of stop and frisk. However, the other side of the Terry equation-the nature and quality of the intrusion-has received far less attention from the legal community. With few exceptions, Terry jurisprudence portrays the Terry frisk simply as a brief pat-down of the outer clothing and treats each Terry stop as an isolated encounter for purposes of measuring the harm involved. Yet there is a robust social science literature on the effects of stop and frisk on individuals, including data on its effects on individuals from marginalized or vulnerable groups, on individuals over time, and on communities as a whole. Moreover, stop and frisk in the current era has evolved from a tool in the arsenal of individual officers to a systematic, widely deployed strategy. This article argues that the failure to grapple with the application of modern knowledge to modern policing practices leads to a mismeasurement on both sides of the Terry equation. Not only does stop and frisk cause a wide range of emotional and psychological harms; these harms may also interfere with the ability of law enforcement to prevent and investigate crime. Even apart from any legal doctrinal implications for stop and frisk jurisprudence, recognizing the flawed assumptions described in this article should encourage all the relevant stakeholders to re-evaluate the consequences of the Terry regime.

Spatio-temporal crime predictions in smart cities: A data-driven approach and experiments

Steadily increasing urbanization is causing significant economic and social transformations in urban areas, posing several challenges related to city management and services. In particular, in cities with higher crime rates, effectively providing for public safety is an increasingly complex undertaking. To handle this complexity, new technologies are enabling police departments to access growing volumes of crime-related data that can be analyzed to understand patterns and trends. These technologies have potentially to increase the efficient deployment of police resources within a given territory and ultimately support more effective crime prevention. This paper presents a predictive approach based on spatial analysis and auto-regressive models to automatically detect high-risk crime regions in urban areas and to reliably forecast crime trends in each region. The algorithm result is a spatio-temporal crime forecasting model, composed of a set of crime-dense regions with associated crime predictors, each one representing a predictive model for estimating the number of crimes likely to occur in its associated region. The experimental evaluation was performed on two real-world datasets collected in the cities of Chicago and New York City. This evaluation shows that the proposed approach achieves good accuracy in spatial and temporal crime forecasting over rolling time horizons.