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The majority of the previous research on hot spots policing focuses on a single set of relatively small selected experimental areas. However, given limited resources, most law enforcement agencies dispatch hot spots intervention units to several areas on a rotation basis. The purpose of this paper is to examine policing activities in hot spots to determine if the various types of crimes were affected when deployment was applied on a rotation basis.

This study uses data from the Dallas Police Department. The differential influence of police activities, including stops, citations, and arrests, are observed against a number of aggregate crime measures (i.e. violent, property, nuisance offenses, and total index crimes). The impact of police activities have been observed for their immediate and lagged effects during the following week to measure residual deterrence effects.

It was found that the DPD's Disruption Unit's hot spots policing immediately affected violent crimes, nuisance offenses, and total index crimes, while there were no residual effects of hot spots policing. The Disruption Unit was engaged in policing activities that include motor vehicle and pedestrian stops, issuing citations, and making arrests. Among these activities, the number of police stops was the most significant factor for the reduction in violent crime and nuisance offenses.

The researchers use a patrol sector as a unit of analysis in order to compare the influence of various types of police activities on crime across a broader area. Future research should consider using an intermediate geographic unit of analysis (e.g. patrol beat).

The paper examines the differential influence of policing activities on different types of crime around hot spots when deployment was applied on a rotation basis. Both immediate and lagged effects were investigated to find residual deterrence effects of hot spots policing.

The Hot Spot Analysis developed by the Wuppertal Institute is a screening tool focussing on the demand of reliable sustainability‐oriented decision‐making processes in complex value chains identifying high priority areas (“hot spots”) for effective measures in companies. This paper aims to focus on this tool.

The Hot Spot Analysis is a qualitative method following a cradle‐to‐cradle approach. With the examples of coffee and cream cheese hot spots of sustainability indicators throughout the entire life cycle are identified and evaluated with data from literature reviews and expert consultations or stakeholder statements. This paper focuses on the indicator resource efficiency as an example of how the methodology works.

The identified hot spots for coffee are the raw material procurement phase in terms of abiotic material, water and energy consumption, the production phase concerning biotic material and the energy consumption in the use phase. For cream cheese relevant hot spots appear in the raw material procurement phase in terms of biotic materials and water as well as biotic materials and energy consumption during the production phase.

Life cycle analyses connected to indicators like resource efficiency need to be applied as consequent steps of a Hot Spot Analysis if a deeper level of analysis is eventually aimed at which is more cost and time intensive in the short term. The Hot Spot Analysis can be combined with other sustainability management instruments.

Research and management can be directed to hot spots of sustainability potential quickly which pays off in the long term.

The paper shows that companies can address sustainability potentials relatively cost moderately.

The purpose of this study is to better understand distinct solution strategy types for common commissioning and startup problems (Hot Spots) in the construction of industrial facilities. The authors also sought to better understand which solution strategy types offer the best value for the effort required.

The authors used a method of qualitative coding of text-based data to identify themes, patterns and trends from a collection of 178 commissioning and startup (CSU) solution strategies for the CSU Hot Spots. Coding categories emerged after multiple iterations. The authors also mapped high-value, low-effort solution strategies across the categories. Chi-squared testing and analysis of proportion statistics help quantitatively justify this qualitative research.

The authors identified 12 distinct coding categories and showed that they follow a non-uniform distribution via statistical testing. Those strategy types which provide particularly good value for the effort required are identified (such as quality assurance and control strategies), as well as those strategy types that do not.

Research is limited to CSU for the construction of industrial facilities. The findings are also limited to a subset of the most commonly problematic CSU activities. Many findings may be beneficial for heavy civil and commercial CSU as well.

Coding categories, definitions and descriptions provide a good overview of all 178 solution strategies for CSU project professionals. Implementing certain types of solutions or solution programs may allow CSU managers to prevent multiple Hot Spots from becoming problematic or to keep problems already occurring from becoming worse. Managers will also benefit from knowledge about which strategy types are more likely to give a higher value for lower effort.

Qualitative coding and analysis of solution strategies for common CSU problems have never been conducted so rigorously in any other CSU study. This method has yielded results distinct from other CSU studies which have used quantitative methods. Insights from findings have advanced the body of knowledge surrounding problem-solving in the commissioning and startup sub-discipline.

The purpose of this study is to discover which solution strategies to common industrial commissioning and startup (CSU) problems (Hot Spots) owner and contractor organizations identify as most effective and to identify which strategies are identified by one or both organization types.

Ratings for the relative value provided by strategies, and the effort required to implement strategies were solicited from CSU industry experts employed by owner or contractor organizations via a survey. Quantitative modelling using the Possible, Implement, Challenge, Kill (PICK) chart method distinguished high-value, low-effort strategies from other strategies.

Owners and contractors identify distinct sets of CSU solution strategies as high value and low effort, with some overlap. Of 178 total strategies, 40 (22.5 per cent) were identified by owners and 34 (19.1 per cent) by contractors, with 19 (10.7 per cent) of those strategies in common. Strategies with the greatest differences in opinions between owners and contractors are also identified.

Research findings are limited to industrial-type, operational systems-intensive facilities. Similarities may exist with other systems-intensive project types, such as some commercial or infrastructure projects. The survey sample size is relatively small (n = 35), but close to that of other CSU-related surveys. The majority of survey participants were based in North America at the time of participation. Further, the number of contractor and owner participants differed slightly.

CSU managers and personnel should consider using high-value, low-effort strategies before resorting to other less effective strategies, as applicable on their projects. Depending on which organization is executing CSU, or if both organization types share CSU responsibilities, different solution strategies may be most effective.

Differences in owner and contractor perspectives and opinions have been noted in other aspects of the project lifecycle but never for CSU solution strategies. Use of the strategies identified will support more effective CSU execution.

The purpose of this study is to identify the situation of spatial inequality in the residential system of Tehran city in terms of housing prices in the year 2021 and to examine its changes over time (1991–2021).

In terms of purpose, this study is applied research and has used a descriptive-analytical method. The statistical population of this research is the residential units in Tehran city 2021. The average per square meter of a residential unit in the level of city neighborhoods was entered in the geographical information system (GIS) in 2021. Moran’s spatial autocorrelation method, map cluster analysis (hot and cold spots) and Kriging interpolation have been used for spatial analysis of points. Then, the change in spatial inequality in the residential system of Tehran city has been studied and measured based on the price per square meter of a residential unit for 30 years in the 22 districts of Tehran by using statistical clustering based on distance with standard deviation.

The result of spatial autocorrelation analysis with a score of 0.873872 and a p-value equal to 0.000000 indicates a cluster distribution of housing prices throughout the city. The results of hot spots show that the highest concentration of hot spots (the highest price) is in the northern part of the city, and the highest concentration of cold spots (the lowest price) is in the southern part of Tehran city. Calculating the area and estimating the quantitative values of data-free points by the use of the Kriging interpolation method indicates that 9.95% of Tehran’s area has a price of less than US$800, 17.68% of it has a price of US$800 to US$1,200, 25.40% has the price of US$1,200 to US$1,600, 17.61% has the price of US$1,600 to US$2,000, 9.54% has the price of US$2,000 to US$2,200, 6.69% has the price of US$2,200 to US$2,600, 5.38% has the price of US$2,600 to US$2,800, 4.59% has the price of US$2,800 to US$3,200 and finally, the 3.16% has a price more than US$3,200. The highest price concentration (above US$3,200) is in five neighborhoods (Zafaranieh, Mahmoudieh, Tajrish, Bagh-Ferdows and Hesar Bou-Ali). The findings from the study of changes in housing prices in the period (1991–2021) indicate that the southern part of Tehran has grown slightly compared to the average range, and the western part of Tehran, which includes the 21st and 22nd regions with much more growth than the average price.

There is massive inequality in housing prices in different areas and neighborhoods of Tehran city in 2021. In the period under study, spatial inequality in the residential system of Tehran intensified. The considerable increase in housing prices in the housing market of Tehran has made this sector a commodity, intensifying the inequality between owners and non-owners. This increase in housing price inequality has caused an increase in the informal living for the population of the southern part. This population is experiencing a living situation that contrasts with the urban plans and policies.

The purpose of this paper is to evaluate an experiment to improve residents’ opinions of the police in Portland, Oregon. Officers conducted community engagement patrols (CEPs) in 60 high-crime areas. The CEPs prioritized non-investigative contacts with community members to build trust and promote positive police–community interactions in designated high-crime locations. It is hypothesized that community members living in/near intervention sites would report greater exposure to officers, more positive interactions and feel more positively about police than residents in control areas.

In total, 90 crime hot spots were identified using crime reports and calls for service. Locations were randomized into three groups: 2 CEPs/day (n=30), 4 CEPs/day (n=30), and control (i.e. no supplemental patrols, n=30). Officers were dispatched to treatment locations via the computer-aided dispatch system for 90 consecutive days, resulting in 16,200 scheduled CEPs. Surveys were mailed to 11,760 households immediately after the intervention ended and 1,537 were returned (13.1 percent).

Residents from intervention areas reported a higher number of positive police contacts, whereas contacts that residents perceived as negative did not differ between the three conditions. Community attitudes, including perceived police legitimacy, were generally unaffected by CEP dosage.

This paper documents the outcomes of a large-scale field experiment seeking to improve public attitudes toward police using directed CEPs in crime hot spots. Whereas the intervention succeeded in providing more opportunities for positive contact with police, attitude change may necessitate longer-term strategies.

The purpose of this paper is to use an evaluation of a micro-place-based hot-spot policing implementation to highlight the potential issues raised by data quality standards in the recording and measurement of crime data and police officer movements.

The study focusses on an area of London (UK) which used a predictive algorithm to designate micro-place patrol zones for each police shift over a two-month period. Police officer movements are measured using GPS data from officer-worn radios. Descriptive statistics regarding the crime data commonly used to evaluate this type of implementation are presented, and simple analyses are presented to examine the effects of officer patrol duration (dosage) on crime in micro-place hot-spots.

The results suggest that patrols of 10-20 minutes in a given police shift have a significant impact on reducing crime; however, patrols of less than about 10 minutes and more than about 20 minutes are ineffective at deterring crime.

Due to the sparseness of officer GPS data, their paths have to be interpolated which could introduce error to the estimated patrol dosages. Similarly, errors and uncertainty in recorded crime data could have substantial impact on the designation of micro-place interventions and evaluations of their effectiveness.

This study is one of the first to use officer GPS data to estimate patrol dosage and places particular emphasis on the issue of data quality when evaluating micro-place interventions.

The purpose of this study is to analyse the trends regarding housing segregation over the past 10–20 years and determine whether housing segregation has a spillover effect on neighbouring housing areas. Namely, the authors set out to determine whether proximity to a specific type of segregated housing market has a negative impact on nearby housing markets while proximity to another type of segregated market has a positive impact.

For the purposes of this paper, the authors must combine information on segregation within a city with information on property values in the city. The authors have, therefore, used data on the income of the population and data on housing values taken from housing transactions. The case study used is the city of Stockholm, the capital of Sweden. The empirical analysis will be the estimation of the traditional hedonic pricing model. It will be estimated for the condominium market.

The results indicate that segregation, when measured as income sorting, has increased over time in some of the housing markets. Its effects on housing values in neighbouring housing areas are significant and statistically significant.

A better understanding of the different potential spillover effects on housing prices in relation to the spatial distribution of various income groups would be beneficial in determining appropriate property assessment levels. In other words, awareness of this spillover effect could improve existing property assessment methods and provide local governments with extra information to make an informed decision on policies and services needed in different neighbourhoods.

On housing prices emanating from proximity to segregated areas with high income differs from segregated areas with low income, policies that address socio-economic costs and benefits, as well as property assessment levels, should reflect this pronounced difference. On the property level, positive spillover on housing prices near high-income segregated areas will cause an increase in the number of higher income groups and exacerbate segregation based on income. Contrarily, negative spillover on housing prices near low-income areas might discourage high-income households from moving to a location near low-income segregated areas. Local government should be aware of these spillover effects on housing prices to ensure that policies intended to reduce socioeconomic segregation, such as residential and income segregation, produce desirable results.

Furthermore, a good estimation of these spillover effects on housing prices would allow local governments to carry out a cost–benefit analysis for policies intended to combat segregation and invest in deprived communities.

The main contribution of this paper is to go beyond the traditional studies of segregation that mainly emphasise residential segregation based on income levels, i.e. low-income or high-income households. The authors have analysed the spillover effect of proximity to hot spots (high income) and cold spots (low income) on the housing values of nearby condominiums or single-family homes within segregated areas in Stockholm Municipality in 2013.

The purpose of this paper is to examine how various policing innovations, including problem‐oriented policing, broken windows, intelligence‐led policing, Compstat, third‐party policing, and hot spots, could be integrated into the community policing philosophy.

The paper provides a definition of community policing and individually examines each policing innovation to determine how they fit within the community policing philosophy.

The findings suggest that various policing innovations are wholly compatible with the community policing philosophy and that incorporating these innovations into community policing may improve their overall utility and the likelihood of their adoption.

The paper highlights the need for new ideas in policing to be built into existing policing innovations rather than developed in isolation.

The findings have implications for how law enforcement agencies fundamentally approach their work and come to understand and use policing innovations and how they are developed by scholars.

The paper is valuable to scholars and police practitioners because it clarifies the community policing philosophy and unifies various ideas regarding policing under one framework.