# Does high-rise residential building design shape antisocial behaviour?

Yung Yau (Department of Public Policy, City University of Hong Kong, Kowloon, Hong Kong)

ISSN: 0263-7472

Publication date: 20 August 2018

## Abstract

### Purpose

The purpose of this paper is to examine links between environmental design of high-rise housing communities and residents’ perceptions about antisocial behaviour (ASB).

### Design/methodology/approach

A conceptual framework was proposed to investigate correlations between architectural design parameters and perceived severity of ASB activity. A questionnaire was administered to test the relationships. Residents of 14 public rental housing estates in Hong Kong participated, and 422 complete responses were analysed.

### Findings

Strong correlation was discovered between elements of residential design and residents’ perceptions of ASB severity. Block layout, building height and number of flats per floor affected residents’ feelings about ASB threat. Access to outside air in communal corridors also significantly reduced residents’ complaints about ASB.

### Practical implications

This study offers insights into how architectural design of high-rise residences might reduce residents’ perception of ASB severity. Findings impact current ASB research, but also architects’ and developers’ designs. Better planned built environments will enhance residents’ security and satisfaction, reinforcing communities.

### Originality/value

Previous studies have ignored whether architectural design of high-rises could directly influence residents’ perception of ASB severity. This study is the first to focus on the relationship.

## Keywords

#### Citation

Yau, Y. (2018), "Does high-rise residential building design shape antisocial behaviour?", Property Management, Vol. 36 No. 4, pp. 483-503. https://doi.org/10.1108/PM-10-2017-0057

### Publisher

:

Emerald Publishing Limited

## Introduction

As scholars have suggested, aspects of housing quality shape inhabitants’ lives (Dunn, 2000; Newcombe et al., 2005; Raw and Hamilton, 1995). On the one hand, design factors like layout, location, orientation and size significantly affect the intrinsic quality of housing. On the other hand, operational and adjustable factors like effective management, the ease of forming neighbourhood relationships, and residents’ general behaviour have significant effects on housing quality and, thus, residents’ quality of life (Bonaiuto et al., 2003; Wong et al., 2006). One key influence on residents’ lives is vulnerability to antisocial behaviour (ASB). ASB is “[any] behaviour that causes harassment to a community” (Local Government Information Unit, 1997, p. 5). Some kinds of ASB are criminal-like activities that injure other residents or vandalise properties while most other types of ASB are really minor offences that disrupt the peace and quietness of a neighbourhood but not prohibited by the criminal law (Local Government Information Unit, 1997; Millie et al., 2005).

Individuals who indulge in ASB disturb the peace, comfort, or privacy of other residents in the community. ASB can also affect other nearby residential areas. For example, residents who have been subjected to protracted ASB locally grow irritable and lose confidence in their neighbourhoods. High rates of ASB affect entire residential areas. Proliferation of antisocial acts signals that a neighbourhood’s social controls and behavioural norms are breaking down (Perkins and Taylor, 1996; Skogan and Maxfield, 1981). Vandalism and housing disrepair make chaotic environments which increase residents’ perception that they are vulnerable to crime (McCrea et al., 2005; Wood et al., 2008). Similarly, empirical studies have identified direct correlation between a neighbourhood’s levels of physical and social disorders (e.g. litter, graffiti and vandalism) and enhanced fear of crime (LaGrange et al., 1992; Perkins and Taylor, 1996). Neighbours’ sense that the community is decaying has been indexed to heightened symptoms of anxiety and depression (Latkin and Curry, 2003). Latkin et al. (2005) have shown in one controlled empirical study that physical and social disorders in one neighbourhood contributed to residents’ extreme distress and, ultimately, was a contributing factor to incipient drug addiction. ASB is both physically and mentally harmful. Its influences on individuals are both direct and indirect (Curtis et al., 2004; Molnar et al., 2004; Putrik et al., 2015; Stansfeld et al., 2000). Social psychologists have found that ASB causes social disruption and reduces residential satisfaction (Agyemang et al., 2007, Jacobson et al., 2008; Weidemann and Anderson, 1982). High rates of ASB and widespread incivilities among residents drive down a neighbourhood’s property values (Brown, 2011).

Across the world, ASB is increasingly attracting scholars’ attention. Besides, recognising the catastrophic consequences of allowing ASB to proliferate, public authorities in different countries have implemented policies to fight it. Cities have enacted laws enforcing stricter tenancy regulations and have employed lease termination as a deterrent against and final remedy for recurrent ASB. Similar legal restrictions, such as forcing newcomers to complete probationary tenancies, courts summarily issuing ASB orders against repeat offenders, and civil orders that penalise parents who say they cannot control their children’s behaviour, have been widely used (Chartered Institute of Housing, 2001; Flint and Nixon, 2006; Hunter et al., 2005). In Hong Kong, a penalty-point system has been institutionalized since 2003 to expel public housing tenants who repeatedly commit proscribed ASB (Yau, 2011). From a communitarian perspective, key scholars have argued that more effective approaches to reducing ASB would focus on enhancing the entire community’s social identity and heightening solidarity among neighbours (Yau, 2014; Hopkins-Burke and Hodgson, 2015).

In the literature, it is often argued that social environments of housing communities have a significant bearing on the proliferation of ASB in the neighbourhoods. However, for this research project, it is particularly intriguing that Yau (2014) has also suggested public housing-related ASB could be mitigated through better residential design. This is a remarkably different approach from legal and community initiatives directed towards changing residents’ behaviours. Yet empirical research assessing the influence of housing design on ASB has been exceptionally rare (Cozens et al., 2001a, b, 2002). With this deficiency in mind, the current Hong Kong-based research aims to investigate whether differences in housing design contribute to changing levels of ASB activity. This study of potential correlations between housing features and the prevalence of ASB in Hong Kong’s high-rise public rental housing estates is organised as follows. First, the most relevant scholarship on ASB will be assessed. Puzzlingly, major research has rarely considered whether the design parameters of a large multi-unit residential edifice could exacerbate or limit ASB activities. An analytic framework for assessing evidence of these factors will then be detailed and its criteria justified. Applications of the investigative framework to survey data collected from residents of high-rise public rental housing in Hong Kong will offer patterns that suggest strong contributors to ASB. The analysis results will be interpreted. Last, a nuanced discussion of the results’ implications for housing design, planning and management and future research will be offered.

## Literature review: ASB and housing design

### Epidemic housing-related ASB around the world

Residential communities are where ASB occurs frequently and produces its damaging consequences (Bullock and Jones, 2004; Flint, 2004). Increased ASB activities in residential communities preoccupy policy-makers in many countries. ASB has attracted extensive attention from academics, architects, urban planners, housing authorities, law-enforcement authorities, residents’ organisations, and other stakeholders. Take for example the fact that over 87 per cent of respondents to a recent study of social housing in New South Wales, Australia, reported experiencing verbal abuse and threats from neighbours (Stein and Marjoribanks, 2014). Approximately 10 per cent of Australian households have reported illegal drug use in their residential communities, while 25 per cent complained that their neighbourhoods had been vandalized (Australian Bureau of Statistics, 2006). In the American Housing Survey 2009, approximately 25.4mn respondents complained of excessive noise in their communities, and 9.8mn identified reckless littering as a chronic problem (United States Census Bureau, 2010). In the study conducted in the early 1990s, 20 per cent of Scotland’s public housing tenants complained that neighbours repeatedly indulged in nuisance behaviours (Clapham et al., 1995). In England and Wales between April 1999 and December 2013, 24,427 ASB Orders were issued (Home Office, 2014). Meanwhile, in Singapore’s public housing estates, residents reported that neighbours’ noisiness had significantly diminished their quality of life (Housing and Development Board, 2014a). In Singaporean public housing, nearly half of all households suffered from nuisance behaviours (Housing and Development Board, 2014b). Yau (2012b) documented that, when questioned, nearly 25 per cent of Hong Kong public housing tenants characterised the neighbourhood problems they endured as intolerable.

### Causes and determinants of ASB proliferation

ASB proliferation has many plausible causes. Seen as a product of poor moral principle and weak willpower, ASB becomes an issue of individual and agency. Intrapersonal factors like poor education, chronic unemployment, and substance abuse affect people’s tendency to engage in ASB. If ASB is a problem of individual self-control, then the root problem is residents’ decisions to engage in ASB. Poor decision-making has been linked to interpersonal issues such as family problems and poor peer relationships (Home Office, 2003). Research in the UK has found that personality disorders and mental health issues frequently prompt individuals to act-out antisocially (Cale, 2006). In Australia, McGee et al. (2009) revealed that ASB was perpetrated at significantly higher rates by children who struggled with family problems. However, ASB authorities have also linked widespread behavioural disorders to socio-structural conditions endemic to large urban populations. Ipsos Mori (2006) and Jacobs and Arthurson (2003) have suggested that profoundly diminished job opportunities for young people and the consequences of poor parenting are crucial structural determinants. Millie (2009) has contended that the growth of ASB-related community problems adheres to the statistical evidence of deteriorating family values and moral standards in modern societies (Millie, 2009).

Another stream of ASB research has focussed on how social systems can influence individual behaviours and minimise broad social circumstances that spark ASB activities in marginalised groups (Burney, 2009; Flint and Rowlands, 2003). These studies have paid considerable attention to the circumstances that shape how community feelings grow sensitised to the apprehending threats and vigilantly detecting communal conflicts that might not be clearly related to ASB. ASB activities can invite more destructive behaviours from disaffected residents. But residents who are keenly alert for evidence of suspected ASB are likely to find it, and confirmed anxieties increase. Divisive communities colour residents’ perceptions of how ASB affects their quality of life. Studies have shown that socio-economic factors such as gender, marital status, and length of residence clearly influenced residents’ sensitivity to possible ASB activity (Taylor et al., 2010). Moley (2008) concluded that, in the UK, perceptions that ASB-related problems required more attention from authorities were exhibited most often by residents in neighbourhoods that were “hard-pressed” or of “moderated means” (p. 125). Another British study found that residents in social housing, as well as those living in flats and maisonettes, were predisposed to show high levels of sensitivity to ASB (Taylor et al., 2010). Furr-Holden et al. (2011) concluded that the presence of abandoned buildings in neighbourhoods powerfully contributed to juvenile ASB activities. These crack properties can be easily accessible sites of gang, prostitution and drug-related undertakings. However, in an Australian study by McGee et al. (2009), data analysis failed to support the theory that more abandoned buildings necessarily elicited higher rates of ASB. McGee et al. (2009) questioned whether the socialized expectation that derelict buildings invited delinquency was empirically valid or whether studies that supported the claim suffered from confirmation bias.

### Housing design: the missing piece to the puzzle of ASB research

Factors related to individual circumstances and structural social trends do clearly affect ASB incidence rates. Along with these issues of individual dysfunction and group conflict, another set of conditions — the effective or poor design of housing and of residential communities — has been linked both to documented rates of antisocial activity and to residents’ enhanced sensitivity to ASB activities. Poor housing design has been connected to neighbourhood problems in Australia (Jacobs and Arthurson, 2003). However, though the poor residential design’s contribution to disruptive behaviours has been observed, the apparent relationship has not been systematically tested. By contrast, empirical evidence that poor housing design increases local crime rates has been well documented (e.g. Newman and Franck, 1980, 1982). According to the rational offender perspective, criminals prefer to commit crimes that “require the least effort, provide the highest benefits and pose the lowest risks” (Taylor and Harrell, 1996, p. 2). If these are the “rational” criminal’s primary considerations, then crime prevention must take account of a wide range of circumstances that make criminal acts more tempting or less profitable.

Design features of residential environments can contribute both to inviting criminality and to deterring it. Consequently, “crime prevention through environmental design” deserves recognition as one of the most influential paradigms in forensic sociological studies. Experts agreed that different physical features impact whether homes would attract criminals (Colquhoun, 2004; Newman, 1973; Robinson, 1996; Stollard, 1991). It makes intuitive sense that criminal opportunities would be reduced by design features that offer residents better surveillance, that segment outdoor spaces into locations more easily controlled by small groups of neighbours, that clearly demarcate private from public spaces, and that locate home entryways close to well-used public thoroughfares. Architectural design features that reduce crime ought to, one anticipates, also diminish residents’ fear of imminent crime. Effective crime-deterrent architectural designs strengthen community-based informal control of residences (Newman, 1972; Taylor and Harrell, 1996). Building layouts that minimise the number of apartments sharing access to one outer threshold, which provide a single means of entry and exit from a few homes, enhance residents’ ability to monitor their environment and reduces strangers’ casual access. Reinforcing gates, doors, and windows with physical barriers also dissuades criminals (Newman and Franck, 1982). Better lighting in communal areas enhances communal surveillance and deters would-be criminals (Welsh and Farrington, 2008). Manzi and Smith-Bowers (2005) provided a wealth of empirical proof that incorporating visible gating in common entrances made homes more secure. There is a wealth of studies on environmental criminology and public health that document the impact of built environmental designs on crime incidence. Moreover, Wood et al. (2008) have found that the visible security of effectively designed residences enhances residents’ apprehension of their own domestic safety. Foster et al. (2010) have also documented links between security-enhanced neighbourhood designs and residents’ confidence.

The majority of studies on ASB activity have been conducted in the West, specifically in Australia, the UK and the USA. Research focussing on how ASB affects residential communities in the East has lagged. The paucity of research in Eastern countries on ASB is particularly glaring when one considers how prevalent ASB activities are in many of the high-rise residential communities that predominate in cities like Hong Kong, Taipei and Singapore. A separate factor that requires consideration is whether the logical tenets and empirically proven crime-prevention methods of environmental crime deterrence translate unequivocally to ASB prevention. Take for instance, Newman’s (1973) concept of defensible space: it works well for deterring burglars but does not necessarily reduce conflictual behaviours among neighbours.

To give credit where it is due, Yau (2014) argued that the problem of ASB in Hong Kong’s housing estates could be mitigated through better housing design. His analysis has not elicited a wave of new empirical studies on how residential designs could diminish Eastern cities’ endemic ASB problems and enhance community solidarity. The need to better understand how built environments affect ASB occurrence is no less imperative for the lack of research. Responding to this pronounced gap, this research directly examines the effects of housing design parameters on ASB activity in Eastern urban residential communities. Spurred by this study, the researcher anticipates other ASB experts will explore the ways in which design details in residential construction can influence psycho-social responses to the problem of individuals seeking to live comfortably and privately while always in close proximity to many more people. How might better housing design influence residents’ sense of being vulnerable to ASB?

## Research method

### Analytic framework of this research

To explore possible relationships between housing design parameters and rates of ASB, the researcher adopted a multiple regression analysis approach, as it allows for demographic and socio-economic variables to be controlled. For this study, an analytic framework was developed for empirical testing. The framework is graphically depicted in Figure 1. In the framework, the severity of ASB problems in a housing estate is hypothesised to be dependent on two sets of factors. The first set comprises housing design parameters, including block layout, corridor design, the number of storeys in each block and the number of flats per storey. These design parameters are the central foci of this empirical study. The second set of potentially significant circumstances consists of demographic and socio-economic characteristics of a specific high-rise community’s residents. Characteristics include residents’ gender, age and education level. These factors serve as control variables in the exploratory analysis. Definitions and measurements of the primary factors being considered in the framework are explained in the following section.

### Measurement of constructs

This study treated the incidence level of ASB in the particular residential neighbourhoods being examined as the dependent variable for the empirical analysis. Rather than using objective measurements, like annual records of the number of ASB incidents reported or the number of punitive orders served against perpetrators, this study adopted residents’ subjective perceptions of ASB as the principal index of ASB manifestation for several reasons. First, the statistics about ASB incidents and resident complaints disseminated by Hong Kong’s public authorities do not accurately reflect the number of ASB incidents reported in residential communities (Yau, 2016). Public statistics are undermined by victims’ reluctance to report ASB incidents (Home Office, 2008). Second, the number of cease-and-desist orders served against ASB perpetrators is a poor indicator of ASB activities’ frequency in a community because the frequency with which statutory orders are issued depends on unknown limitations, like whether public resources have been allocated for combatting ASB. Accuracy of the records of ASB orders served is also contingent on the bureaucratic effectiveness of the enforcement authorities. Third and most importantly, statistics about ASB incidents and citizens’ complaints publicly available from Hong Kong’s government only reflect aggregated totals of ASB activities at the level of the whole territory. No discrete information is available for street-block and estate-level activities.

Without reliable empirical data on ASB activities, this study has had to utilise residents’ self-reported experiences of ASB activities, which we have identified with residents’ self-assessment of past and future ASB threat. To gauge the incidence level of ASB witnessed by a local resident in a public rental housing estate, the resident was asked to rate the following seven aspects of ASB using a five-point Likert scale (5=very serious; 4=serious; 3=quite serious; 2=a little serious; 1=not a problem at all). The classes of ASB respondents assessed were as follows:

• neighbour-generated noise;

• pet nuisances;

• neglected water seepage or dripping;

• littering;

• abusiveness of neighbours in common areas;

• graffiti, unlawful flyer-posting and vandalism; and

• harassment and intimidation.

The overall level of intensity of ASB activity perceived by the resident was taken as the simple average of the seven responses.

As for the exogenous variables, block layout refers to the type of building plan configuration implemented in an individual residential block. In Hong Kong, a rental housing block is commonly configured in a cruci, cross, trident, H-shaped, linear or slab form. As shown in Figures 2–4, habitable rooms (e.g. living rooms, dining rooms or bedrooms) of a flat face those of adjacent flat in the first three configurations. It is expected that noise, odour and other nuisances can be more easily spread from one flat to another. On the contrary, the H-shaped, linear and slab forms minimise the mutual disturbance among residents. Figures 5 and 6 demonstrate that in these two layout designs, the living or dining rooms of adjacent flats do not face each other. Block layout is indicated by a set of dummy variables. The variable LINEAR equalled 1 if the housing block was a linear or slab form and zero if otherwise. The variable HSHAPE equalled 1 if the housing block was in an H-shaped form and zero if otherwise. The variable TRIDENT equalled 1 if the housing block was a trident-shaped block and zero if otherwise. The reference categories are the cross and cruci forms.

The category corresponding to the design of a block’s corridors (CDES), reflects the extent of the outer boundary walls of communal corridors that is exposed to external air. The variable is taken as the percentage of the enclosing walls of the communal corridors on a typical floor of a housing block, measured in length on a building plan, that have openable windows or other portals that permit access to external space and air. Figure 7 illustrates the measurement of CDES. It was anticipated that the effects of noise and odour originating from one flat and permeating other adjacent flats would be diminished if the communal corridor linking the flats were more “open”. The openings on the corridor’s containment walls can serve as points to allow sound and foul air to discharge from the interior to the exterior of a housing block. Airborne sound cannot be reflected where there is an opening in the walls. With a higher degree of “openness”, the communal corridor can allow undesirable noise and odour generated in one flat to attenuate more effectively before they reach other flats. Besides, two factors relate to building scale. The first is the total number of domestic storeys in a residential block (STOREY). The second is the average number of flats per floor in a residential block (FLAT).

The key control variables picked for the study characterised demographic and socio-economic factors: gender, age, educational attainment and personal income and household size are employed. A resident’s gender is indicated by the dummy variable MALE, equalling 1 for males and zero for women. For each resident’s age group, the variable AGE is indicated with a six-category scale (6=65 years old or above; 5=55–64 years old; 4=45–54 years old; 3=35–44 years old; 2=25–34 years old; and 1=18–24 years old). The highest educational attainment of the resident (EDU) is measured using a six-category scale (6=postgraduate degree or above; 5=bachelor degree; 4=sub-degree post-secondary education; 3=upper secondary school or matriculation; 2=lower secondary school; and 1=primary school or below). Income level (PINC) was indicated with a seven-point measure: 7=HK$30,000 or above; 6=HK$25,000–HK$29,999; 5=HK$20,000–HK$24,999; 4=HK$15,000–HK$19,999; 3=HK$10,000–HK$14,999; 2=HK$4,000–HK$9,999; and 1=below HK$4,000. Income brackets identified each resident’s average monthly personal income. Household size (HSIZE) was measured as the number of household members living in a resident’s flat. In addition to the five demographic and socio-economic factors mentioned above, the length in years of a resident’s occupation of the same housing estate (LOR) is included in the model to indicate the resident’s attachment to the estate.

### Collection of data

Empirical testing of the analytic model elaborated in the previous section required that relevant data be collected from Hong Kong’s public rental housing estates. Both the primary data sourced directly from residents and secondary data on the housing blocks’ construction were employed for the analyses. For the primary data, an online structured questionnaire survey was conducted in Hong Kong in the period between November 2016 and March 2017. A questionnaire was designed to solicit the information required to empirically test the analytic model. Before the survey officially started, the questionnaire had been pretested and modified in response to testers’ feedback. When the questionnaire was revised to its final version, a letter was sent to the sampled households in selected public rental housing estates. Letters invited the respective household heads to complete an online survey. As for the secondary data, estate-based information such as development scale and occupant density were obtained from various governmental sources such as the website of the Housing Department and government’s census data.

In total, 14 public rental housing estates in Hong Kong were sampled. These housing estates are scattered throughout Hong Kong, and their housing blocks had been constructed in different design configurations and to different scales of square-footage and occupant-density. Selective sampling allowed for a more meaningful research analysis. In all, five of these 14 housing estates were located on Hong Kong Island, three in Kowloon and six in the New Territories. The scales of the estates ranged from 900 residential units to 7,900 housing units. In the 14 sampled estates, there was a total of 106 housing blocks. In each of the sampled housing estates, approximately 20 per cent of the housing blocks were randomly selected, resulting in a total of 23 housing blocks that contained tenants who were invited to participate in the study. As Table I shows, ten housing blocks (43.5 per cent) came from the New Territories, five (21.7 per cent) from Kowloon and eight (34.8 per cent) from Hong Kong Island.

Of the sampled housing blocks, the basic design formats were distributed in these proportions. Eight housing blocks (34.8 per cent) were designed with a linear or slab layout and another eight (34.8 per cent) with cruci or cross form layouts. The number of storeys in these housing blocks in these estates ranged from 14 to 40, with a mean of 23.3. On average, there were 14.5 residential units on each floor. The average age of the 23 housing blocks was 30.1 years. The percentage of an enclosure walls’ perimeter for a typical communal corridor that was open to external air ranged from 3.2 to 33.6 per cent, with a mean of 12.1 per cent.

In each of these 23 housing blocks, approximately 25 per cent of the residential units were randomly sampled — for a total of 1,950 residential units. Invitations were sent to the household heads of these residential units. Household heads were requested to answer an online survey, which included the study’s questionnaire. The researcher contacted households once, waited for responses, and then repeated the invitation to households that had not replied. After the two appeals, a total of 451 replies were received, representing an overall response rate of 23.1 per cent. Among these returned questionnaires, 422 were deemed valid for the analysis. The remaining 29 replies were incomplete so they were discarded. Multiple regression technique was employed to analyse the survey data.

Table II summarises the characteristics of the 422 respondents. Over half of the respondents were male. The respondents’ ages were distributed quite evenly across adult age groups. Data on education level revealed that approximately 15 per cent of the respondents had attained bachelor degrees or higher. Comparative data for income showed that the group earning HK$15,000–HK$19,999 contributed the largest share (35.5 per cent) of any one income bracket for average monthly income. Regarding household income, the sample looks comparable with the population in public rental housing in Hong Kong. According to the 2016 Population By-census, the median monthly domestic household income in all public rental housing was HK$16,000 (Census and Statistics Department, 2017). The average household size was 3.4 people, and the respondents’ mean length of residence in the same estate was 18.1 years. As Table III shows, residents considered neighbours’ noise to be the single-most serious type of ASB. Harassment and intimidation was the ASB category respondents complained of least. The correlation matrix of continuous independent variables is presented in Table IV. Inspection of the correlation matrix does not reveal any significant problems of multicollinearity in the data set. ### Results of regression analyses Two models were used for empirically testing relationships between housing design parameters and ASB perceptions. Model 1 included housing design parameters (e.g. block layout, building height and number of flats per storey) only as independent variables. In addition to the housing design parameters, Model 2 incorporated the control variables (e.g. the respondents’ demographic and socio-economic characteristics and length of residence). Table V shows the results of the model estimation using the ordinary least squared method. The estimation returned adjusted R2 of 0.42 and 0.49 for Models 1 and 2, respectively, implying around 42–49 per cent of the variation in the dependent variable (i.e. ASB) could be explained by differences in the independent variables incorporated in the respective models. As far as the control variables are concerned, only age showed significant (at 10 per cent level at least) effects on ASB perceptions. Older respondents tended to perceive a less serious level of ASB in their residential neighbourhoods. A ten-year increase in age resulted in a 0.5-point reduction in the overall severity level of ASB. On the other hand, gender, education level, personal income and household size did not correlate with any pronounced trend in the respondents’ ASB perceptions (even at the 10 per cent level). Similarly, length of residence had no significant correlation with ASB perception. As for the housing design parameters which are the foci of the current study, the estimation results of Models 1 and 2 were similar. The estimated coefficients of the dummy variables LINEAR (−0.1062 and −0.0956) and HSPAPE (−0.0808 and −0.0776) were found to be negative, and they were statistically significant at the 10 per cent level at least in the two estimation models. Thus, compared with residents in housing blocks with cruci- or cross-form layouts, respondents living in housing blocks with a linear, slab or H-shaped form perceived less serious ASB problems, ceteris paribus. In both models, there was no significant difference between the estimated coefficients of LINEAR and HSPAPE (even at the 10 per cent level). In other words, when other factors were controlled, residents living in housing blocks in a linear or slab-form layout and with an H-shaped form perceived similar levels of ASB severity. On the other hand, in both models, the dummy variable TRIDENT was found to have no insignificant impact on ASB (even at the 10 per cent level), indicating that residents living in housing blocks in a trident form and in blocks with cruci and cross forms did not have significantly dissimilar ASB perceptions, keeping other things constant. The estimated coefficient of the variable CDES was found negative and statistically significant at the 1 per cent level in both models. These results suggested that residents living in a housing block where the communal corridor had a greater proportion of perimeter opening to external air perceived a lower level of ASB severity in their housing estates. Say according to the estimation results of Model 2, when the “openness” of the communal corridor was increased by 10 per cent (or 0.1), the overall ASB score would drop by 0.46. If communal corridors of a housing block were more “open” to external air, the residents’ perception of threatening or nuisance ASB activity was diminished. The building height factor, as proxied by the number of storeys in a building block, was found to have significant (at the 10 per cent level in Model 1 and 5 per cent level in Model 2) positive impacts on ASB perceptions. Yet, the impacts brought by building heights were rather marginal. A rise in the number of storeys in a housing block by 10 would contribute to a 0.05-point increment only in the overall ASB level. As for the variable FLAT, it also had a positive and statistically significant (at the 1 per cent level in both models) estimated coefficient, signifying a positive relationship between number of flats per storey and ASB perception. ## Discussion and implications The estimation results of the empirical model suggested that block layout and corridor design were the factors that powerfully influenced residents’ perceptions of ASB level in their housing estates. The analysis results confirmed our expectations. By carefully arranging the housing units on a floor and making openings on enclosure walls of communal corridors, dampen the spread of noise, odour and other nuisances among residents. These enhancements can be incorporated in the design stage — long before residents and housing managers struggle to find solutions to ASB problems during the operation stage that will likely last decades. As the analysis results suggest, linear, slab and H-shape forms are preferable block layouts, as they can reduce residents’ perceptions of ASB environmental effects. Trident, cruci and cross layouts are less preferable from the perspective of ASB perception minimisation. Apart from block layout, corridor design was also found to correlate strongly with perceived ASB level. Residents living in a housing block with communal corridors that were more open to external air complained less of ASB effects. The findings of this research should encourage architects to reduce future residents’ perception of ASB distractions by investing communal corridors with more openable windows and other safe means of accessing “outside” air. Alternatively, balconies could be integrated in design of communal corridors. Furthermore, as the analysis results implied, adding more storeys to a housing block will likely increase ASB effects, and it will certainly increase residents’ perceptions that their peace and safety is threatened by neighbours’ ASB activities. The same problems are exacerbated by plans that add additional units to each storey. These relationships echo arguments by Makinde et al. (2016) that every crowded living environment promotes ASB activity. When there are too many storeys in a building and too many flats compacted on each floor, the boundaries between “private” flats and public, shared areas (including communal corridors and environmental cleanliness) become uncomfortably thin. Tenants who grow sensitive to the fact that, even when they are alone in their rental units, they are sharing space with others in the building will feel vulnerable to neighbours’ constant activities. Inclined to interpret neighbours’ unwanted intrusions on their privacy as ASB, residents are more likely to feel like victims. If their resentments increase, they might become intentional sources of retaliatory ASB. The exploratory analyses produced provocative results that should be explored in future research. Previous scholarship on ASB has argued that residents’ age was a primary determinant in sensitivity to ASB; however, this research has indicated that a more imposing source of influences that decreased or elevated tenants’ sensitivity to ASB activity were key housing design parameters. These aspects of high-rise buildings’ physical construction connected to residents’ sense that their privacy was secure from or vulnerable to neighbours’ intrusive proximity. Building features that also proved significant correlated to tenants’ sense that public corridors had access to open air. Renters’ perceptions about these conditions powerfully influenced their sense of the quality of their living environments. In order to curb ASB activities in high-rise residences and reduce disputes between neighbours, the Hong Kong government would be wise to consider these discoveries when they seek to integrate ASB-dampening features in designs for new public and private housing developments. This study’s findings should also be cautionary for governmental and professional organisations that certify sustainable building projects (e.g. Building Environmental Assessment Method Plus). With this study’s main recommendations in mind, architects and real estate developers should remember that a new building’s incorporation of renewable materials and implementation of new energy-saving and waste-reducing technologies is very important. But the ultimate purpose of all residential projects is to create an enhanced sustainable built environment for individuals and communities to coexist in peacefully and happily. Second, to make a housing estate pleasant place for living and visiting, housing managers should make sure that those ASB-dampening design features will not be “disabled” in the building operation stage. Over years, building managers will need to oversee repairs, renovations, and alterations to guarantee that ASB-reducing features are not sabotaged by poorly conceived retrofitting. Indeed, tenants must contribute to community health by ensuring that ASB-suppressing features continue to work. Openable windows in communal corridors should not be kept closed. Closed windows retain heat, but they also trap noise and odour within communal corridors. Housing managers who oversee maintenance of new cost-efficient but crowded government-subsidised high-rise residences must be aware that tenants recognise when increasing the number of flats per storey has occurred at the expense of privacy. Too many tenants inhabiting each storey will become sensitised to ASB activities. Housing managers might need to proactively institute more stringent house rules (like “no-pet” policies) or patrol common areas where friction between neighbours often occurs. This research’s implications are likely not limited to enhancing ASB governance in Hong Kong’s residential high-rises. If additional research confirms these findings, the architectural features we discovered to be most effective in securing residents’ contentment could prove advantageous in other countries high-rise and large-scale residential structures, especially those which are being implemented in Asia. As Yau (2012a) contended, ASB activities have proliferated in Hong Kong’s private residential housing developments in a fashion comparable to its spread in crowded public rental housing communities. This research has investigated residents’ quality of life in public housing, but the ASB-suppressing architectural features we have identified might have equally enduring benefits for multi-unit private housing in Asian cities. ### Conclusion and agenda for future research It has been widely accepted that ASB activities are a matter of burgeoning concern, as much for community government as for city and district law enforcement. The possible effects of design and construction features on large multi-unit structures have not been seriously investigated until now. Scholarship on ASB’s disruptive influence on communities has focussed on individual behaviours and structural social trends in contemporary home life. Therefore, the researcher finds it exciting that this study’s conclusions have pointed to a more powerful set of environmental influences correlating to effective building design. This contributes to the existing body of ASB research by providing new, statistically supported theories of how building features could both reduce the conditions that contribute to disruptive ASB and, by increasing residents’ sense of well-being, diminish their perceived sensitivity to problems of close cohabitation that could be identified as ASB. The findings of this research have direct relevance to current public housing policy. But their implications extend to the potential benefit of many modern housing stakeholders: real-estate developers, tenants and owner-occupiers, housing managers, architects and governments. The relationship between housing design and residents’ perceived sensitivity to ASB disruption is complex. Nevertheless, because unhappy residents’ reactions to perceived ASB-related conflict affect whole communities’ well-being, identifying likely environmental contributors to ASB potentially impacts community health, residential satisfaction and social capital. This avenue of exploration warrants further theoretical consideration and empirical study. The current study focusses on public housing only. The housing design-ASB relationship in private housing should be examined. Moreover, only several factors such as block layout, openness of communal corridor, building height and development density were incorporated in the exploratory analysis in the current study. Some design parameters that could have effects on residents’ ASB perceptions were ignored. These parameters include thicknesses of internal walls and floor slabs, and types of window systems. Future studies should be carried out to find out the effects of these design parameters. Furthermore, it is necessary to develop a more complex modelling of the linkages between the housing design, neighbourhood cohesion and ASB perception in the future. While Yau (2014) argued that solidarity with one’s community could be nurtured through better housing design, it seems logical that some housing design features might enhance a neighbourhood’s solidarity but simultaneously exacerbate residents’ sensitivity to ASB influences by outsiders and residents who resist conformity. Future studies need to look at an expanded range of housing design parameters. The spectrum of ASB activities researchers observe should be expanded. Further, future studies are warranted to explore the effects of housing design parameters or features on ASB and neighbourhood cohesion and the dynamic relationships between ASB and neighbourhood cohesion after controlling the structural and contextual factors, as shown in Figure 8. Such research will facilitate better understanding of how institutionalized environmental features affect residents’ perceptions of their security and well-being in their living places. And yet this study also signals a profound shift in ASB studies that, by drawing attention to designed residential communities, opens the door of disciplinary opportunity to architects, engineers, ecologists, and urban planners to contribute to the study of environment’s influence on individual and communal perception of social disruptive interactions by neighbours. The theoretical implications are challenging and intriguing. But the practical results of future research into the influence of built environments on large, complexly engineered residences promise concrete rewards from better designed homes and better organised communities that will help engender sustainable communities for all our future cities. ## Figures #### Figure 1 Analytic framework contrasting variables’ influence on ASB #### Figure 2 Cruci form of block layout #### Figure 3 Cross form of block layout #### Figure 4 Trident form of block layout #### Figure 5 Linear form of block layout #### Figure 6 H-shaped form of block layout #### Figure 7 Graphical illustration of measurement of CDES #### Figure 8 Proposed conceptual framework for subsequent research ## Table I Characteristics of sampled housing blocks Characteristic Count Percentage Location Hong Kong Island 8 34.8 Kowloon 5 21.7 New territories 10 43.5 Block Layout Linear or slab form 8 34.8 H-shaped form 4 17.4 Trident form 3 13.0 Cruci or cross form 8 34.8 Note: n=23 ## Table II Characteristics of the survey respondents Characteristic Count Percentagea Gender Male 268 63.5 Female 154 36.5 Age 18–24 years old 15 3.6 25–34 years old 60 14.2 35–44 years old 138 32.7 45–54 years old 143 33.9 55–64 years old 58 13.7 65 years old or above 8 1.9 Education level Primary school or below 68 16.1 Lower secondary school 109 25.8 Upper secondary school or matriculation 108 25.6 Sub-degree post-secondary education 73 17.3 Bachelor degree 58 13.7 Postgraduate degree or above 6 1.4 Average monthly personal income Below HK$4,000 42 10.0
HK$4,000-HK$9,999 71 16.8
HK$10,000-HK$14,999 83 19.7
HK$15,000-HK$19,999 150 35.5
HK$20,000-HK$24,999 51 12.1
HK$25,000-HK$29,999 16 3.8
HK\$30,000 or above 9 2.1
Layout of housing block
Linear or slab form 131 31.0
H-shaped form 68 16.1
Trident form 63 14.9
Cruci or cross form 160 37.9

Notes: n=422. aThe percentages of the categories for each characteristic may not total 100% because of rounding

## Table III

Respondents’ perceptions of ASB severity

Type of ASB Very serious Serious Quite serious A little serious Not a problem at all
Noise 120 (28.4%) 107 (25.4%) 86 (20.4%) 80 (19.0%) 29 (6.9%)
Pet nuisances 90 (21.3%) 89 (21.1%) 116 (27.5%) 86 (20.4%) 41 (9.7%)
Neglected water seepage or dripping 86 (20.4%) 100 (23.7%) 110 (26.1%) 79 (18.7%) 47 (11.1%)
Littering 117 (27.7%) 109 (25.8%) 86 (20.4%) 70 (16.6%) 40 (9.5%)
Abusiveness in common areas 86 (20.4%) 110 (26.1%) 104 (24.6%) 81 (19.2%) 41 (9.7%)
Graffiti, flyer-posting, and vandalism 87 (20.6%) 90 (21.8%) 112 (26.5%) 90 (21.3%) 41 (9.7%)
Harassment and intimidation 83 (19.7%) 94 (22.3%) 98 (23.2%) 103 (24.4%) 44 (10.4%)

Notes: n=422. The figures in parentheses represent proportions of respondents

## Table IV

Correlation coefficient matrix of continuous independent variables

Variable AGE EDU PINC HSIZE LOR CDES STOREY FLAT
AGE 1
EDU −0.015 1
PINC −0.010 −0.331 1
HSIZE 0.001 −0.087 0.082 1
LOR 0.049 0.147 −0.223 −0.029 1
CDES −0.057 −0.005 −0.020 −0.064 −0.014 1
STOREY −0.017 −0.036 0.009 0.067 −0.014 0.017 1
FLAT −0.009 −0.075 0.222 0.118 0.013 0.052 −0.059 1

## Table V

Results of the ordinary least squared estimation of the empirical models

Model 1 Model 2
Variable Coefficient t-statistic Coefficient t-statistic
Intercept 3.6874 30.5300*** 3.8236 25.1482***
LINEAR −0.1062 −2.0255** −0.0956 −1.8260*
HSHAPE −0.0808 −2.1079** −0.0776 −2.0303**
TRIDENT 0.0927 1.5095 0.0730 1.1855
CDES −4.7635 −18.4959*** −4.6472 −17.7415***
STOREY 0.0051 1.9030* 0.0054 2.0504**
FLAT 0.0247 8.9628*** 0.0242 8.8510***
MALE 0.0277 0.8731
AGE −0.0516 −3.6734***
EDU 0.0157 1.4183
PINC 0.0013 0.1158
HSIZE 0.0021 0.1964
LOR −0.0020 −0.8040
R2 0.4346 0.4959
F-statistics 6.0409*** 6.8132***
Dependent variable ASB ASB
Number of observations 442 442

Notes: *,**,***Denote the estimated coefficients of the variables or test statistics to be significant at the 10, 5 and 1 per cent levels, respectively

## References

Agyemang, C., Van Hooijdonk, C., Wendel-Vos, W., Lindeman, E., Stronks, K. and Droomers, M. (2007), “The association of neighbourhood psychosocial stressors and self-rated health in Amsterdam, the Netherlands”, Journal of Epidemiol Community Health, Vol. 61 No. 12, pp. 1042-1049.

Australian Bureau of Statistics (2006), Crime and Safety, Australia (April 2005), Australian Bureau of Statistics, Sydney.

Bonaiuto, M., Fornara, F. and Bonnes, M. (2003), “Indexes of perceived residential environment quality and neighbourhood attachment in urban environments: a confirmation study on the city of Rome”, Landscape and Urban Planning, Vol. 65 Nos 1/2, pp. 41-52.

Brown, J. (2011), A Municipal Exigency: An Exploration of the Correlation of Physical and Social Incivilities on the Decline of Residential Property Values in Richmond, VA, Virginia Commonwealth University, Richmond, VA.

Bullock, K. and Jones, B. (2004), Acceptable Behaviour Contracts Addressing Antisocial Behaviour in the London Borough of Islington, Home Office, London.

Burney, E. (2009), Making People Behave: Anti-social Behaviour, Politics and Policy, Willan, Cullompton.

Cale, E.M. (2006), “A quantitative review of the relations between the ‘big 3’ higher order personality dimensions and antisocial behaviour”, Journal of Research in Personality, Vol. 40 No. 3, pp. 250-284.

Census and Statistics Department (2017), “Summary results of 2016 population by-census”, available at: www.bycensus2016.gov.hk/ (accessed 3 January 2018).

Chartered Institute of Housing (2001), The Law: An Adequate Response to Anti-social Behaviour, Chartered Institute of Housing, Cardiff.

Clapham, D., Kintrea, K., Marlcolm, J., Parkey, H. and Scott, S. (1995), A Baseline Study of Housing Management in Scotland, Scottish Office, Edinburgh.

Colquhoun, I. (2004), Design Out Crime: Creating Safe and Sustainable Communities, Architectural Press, Oxford.

Cozens, P.M., Hillier, D. and Prescott, G. (2001a), “Crime and the design of residential property: exploring the perceptions of planning professionals, burglars and other users”, Property Management, Vol. 19 No. 4, pp. 222-248.

Cozens, P.M., Hillier, D. and Prescott, G. (2001b), “Defensible space: Burglars and police evaluate urban residential design”, Security Journal, Vol. 14 No. 4, pp. 43-62.

Cozens, P.M., Hillier, D. and Prescott, G. (2002), “Gerontological perspectives on crime and nuisance: the elderly critically evaluate housing designs in the British city”, Journal of Aging and Social Policy, Vol. 14 No. 2, pp. 63-83.

Curtis, L.J., Dooley, M.D. and Phipps, S.A. (2004), “Child well-being and neighbourhood quality: evidence from the Canadian national longitudinal survey of children and youth”, Social Science and Medicine, Vol. 58 No. 10, pp. 1917-1927.

Dunn, J.R. (2000), “Housing and health inequalities: review and prospects for research”, Housing Studies, Vol. 15 No. 3, pp. 341-366.

Flint, J. (2004), “The responsible tenant: housing governance and the politics of behaviour”, Housing Studies, Vol. 19 No. 6, pp. 893-909.

Flint, J. and Nixon, J. (2006), “Governing neighbours: anti-social behaviour orders and new forms of regulating conduct in the UK”, Urban Studies, Vol. 43 Nos 5/6, pp. 939-955.

Flint, J. and Rowlands, R. (2003), “Commodification, normalisation and intervention: cultural, social and symbolic capital in housing consumption and governance”, Journal of Housing and the Built Environment, Vol. 18 No. 3, pp. 213-232.

Foster, S., Giles-Corti, B. and Knuiman, M. (2010), “Neighbourhood design and fear of crime: a social-ecological examination of the correlates of residents’ fear in new suburban housing developments”, Health & Place, Vol. 16 No. 6, pp. 1156-1165.

Furr-Holden, C.D.M., Lee, M.H., Milam, A.J., Johnson, R.M., Lee, K.-S. and Ialongo, N.S. (2011), “The growth of neighborhood disorder and marijuana use among urban adolescents: a case for policy and environmental interventions”, Journal of Studies on Alcohol and Drugs, Vol. 72 No. 3, pp. 371-379.

Home Office (2003), Respect and Responsibility: Taking a Stand against Anti-social Behaviour, Home Office, London.

Home Office (2008), Perceptions of Anti-Social Behaviour: Findings from the 2007/08 British Crime Survey, Home Office, London.

Home Office (2014), Anti-Social Behaviour Order Statistics: England and Wales 2013 Key Findings, Home Office, London.

Hopkins-Burke, R. and Hodgson, P. (2015), “Anti-social behaviour, community and radical moral communitarianism”, Cogent Social Sciences, Vol. 1 No. 1, pp. 1-13.

Housing and Development Board (2014a), Public Housing in Singapore: Residents’ Profile, Housing Satisfaction and Preferences – HDB Sample Household Survey 2013, Housing and Development Board, Singapore.

Housing and Development Board (2014b), Public Housing in Singapore: Social Well-being of HDB Communities – HDB Sample Household Survey 2013, Housing and Development Board, Singapore.

Hunter, C., Nixon, J. and Slatter, M. (2005), “Neighbours behaving badly: anti-social behaviour, property rights and exclusion in England and Australia”, Macquarie Law Journal, Vol. 5, pp. 149-176.

Ipsos Mori (2006), “Public attitudes to parenting”, available at: www.ipsos-mori.com/researchpublications/researcharchive/poll.aspx?oItemId=374 (accessed 23 July 2016).

Jacobs, K. and Arthurson, K. (2003), Development Effective Housing Management Policies to Address Problems of Anti-social Behaviour, Australian Housing and Urban Research Institute, Melbourne.

Jacobson, J., Millie, A. and Hough, M. (2008), “Why tackle anti-social behaviour”, in Squires, P. (Ed.), ASBO Nation: The Criminalisation of Nuisance, The Policy Press, Bristol, pp. 37-55.

LaGrange, R.L., Ferraro, K.F. and Supancic, M. (1992), “Perceived risk and fear of crime: role of social and physical incivilities”, Journal of Research in Crime and Delinquency, Vol. 29 No. 3, pp. 311-334.

Latkin, C.A. and Curry, A.D. (2003), “Stressful neighborhoods and depression: a prospective study of the impact of neighborhood disorder”, Journal of Health and Social Behavior, Vol. 44 No. 1, pp. 34-44.

Latkin, C.A., Williams, C.T., Wang, J. and Curry, A.D. (2005), “Neighborhood social disorder as a determinant of drug injection behaviors: a structural equation modeling approach”, Health Psychology, Vol. 24 No. 1, pp. 96-100.

Local Government Information Unit (1997), Community Safety: Consultation in Advance of the Crime and Disorder Bill, Home Office, London.

McCrea, R., Shyy, T.-K., Western, J. and Stimson, R.J. (2005), “Fear of crime in Brisbane: individual, social and neighborhood factors in perspective”, Journal of Sociology, Vol. 41 No. 1, pp. 7-27.

McGee, T.R., Wickes, R.L., Bor, W. and Najman, J. (2009), Antisocial Behaviour Across Neighbourhoods: Individuals and Families in Context, Criminology Research Council, Canberra.

Makinde, O., Björkqvist, K. and Österman, K. (2016), “Overcrowding as a risk factor for domestic violence and antisocial behaviour among adolescents in Ejigbo, Lagos, Nigeria”, Global Mental Health, Vol. 3, pp. 1-10.

Manzi, T. and Smith-Bowers, B. (2005), “Gated communities as club goods: segregation or social cohesion”, Housing Studies, Vol. 20 No. 2, pp. 345-359.

Millie, A. (2009), Anti-Social Behaviour, Open University Press, Berkshire.

Millie, A., Jacobson, J., McDonald, E. and Hough, M. (2005), Anti-Social Behaviour Strategies: Finding a Balance, Joseph Rowntree Foundation, York.

Moley, S. (2008), “Public perceptions”, in Kershaw, C., Nicholas, S. and Walker, A. (Eds), Crime in England and Wales 2007/2008, Home Office, London, pp. 117-142.

Molnar, B.E., Gortmaker, S.L., Bull, F.C. and Buka, S.L. (2004), “Unsafe to play? Neighborhood disorder and lack of safety predict reduced physical activity among urban children and adolescents”, American Journal of Health Promotion, Vol. 18 No. 5, pp. 378-386.

Newcombe, R.G., Lyons, R.A., Jones, S.J. and Patterson, J. (2005), “Home injuries and built form: methodological issues and developments in database link”, BioMed Central Health Services Research, Vol. 5 No. 12, pp. 1-6.

Newman, O. (1972), Defensible Space, Macmillan, New York, NY.

Newman, O. (1973), Architectural Design for Crime Prevention, New York University, New York, NY.

Newman, O. and Franck, K. (1980), Factor Influencing Crime and Instability in Urban Housing Developments, United States Government Printing Office, Washington, DC.

Newman, O. and Franck, K. (1982), “The effects of building size on personal crime and fear of crime”, Population and Environment, Vol. 5 No. 4, pp. 203-220.

Perkins, D.D. and Taylor, R.B. (1996), “Ecological assessments of community disorder: their relationship to fear of crime and theoretical implications”, American Journal of Community Psychology, Vol. 24 No. 1, pp. 63-107.

Putrik, P., de Vries, N.K., Mujakovic, S., van Amelsvoort, L., Kant, I., Kunst, A.E., van Oers, H. and Jansen, M. (2015), “Living environment matters: relationships between neighbourhood characteristics and health of the residents in a Dutch municipality”, Journal of Community Health, Vol. 40 No. 1, pp. 47-56.

Raw, G.J. and Hamilton, R.M. (1995), Building Regulation and Health, Building Research Establishment, Garston.

Robinson, M.B. (1996), “The theoretical development of ‘CPTED’: 25 years of responses to C. Ray Jeffery”, in Laufer, W.S. and Adler, F. (Eds), The Criminology of Criminal Law: Advances in Criminological Theory, Transaction, New Brunswick, pp. 427-462.

Skogan, W. and Maxfield, M. (1981), Coping with Crime: Individual and Neighborhood Reactions, Sage, Beverly Hills, CA.

Stansfeld, S., Haines, M. and Brown, B. (2000), “Noise and health in the urban environment”, Reviews on Environmental Health, Vol. 15 Nos 1/2, pp. 43-82.

Stein, J. and Marjoribanks, G. (2014), The Right to Quiet Enjoyment in Social Housing, Hunter Community Legal Centre, Newcastle.

Stollard, P. (Ed.) (1991), Crime Prevention through Housing Design, Chapman and Hall, London.

Taylor, J., Twigg, L. and Mohan, J. (2010), “Investigating perceptions of antisocial behaviour and neighbourhood ethnic heterogeneity in the British crime survey”, Transactions of the Institute of British Geographers, Vol. 35 No. 1, pp. 59-75.

Taylor, R.B. and Harrell, A.V. (1996), Physical Environmental and Crime, National Institute of Justice, Washington, DC.

United States Census Bureau (2010), American Housing Survey for the United States: 2009 – Current Housing Report, United States Department of Housing and Urban Development and United States Census Bureau, Washington, DC.

Weidemann, S. and Anderson, J.R. (1982), “Residents’ perceptions of satisfaction and safety: a basis for change in multifamily housing”, Environment and Behavior, Vol. 14 No. 6, pp. 695-724.

Welsh, B. and Farrington, D. (2008), “Effects of improved street lighting on crime: a systematic review”, Campbell Systematic Review, Vol. 4, pp. 1-12.

Wong, S.K., Cheung, A.K.C., Yau, Y., Ho, D.C.W. and Chau, K.W. (2006), “Are our residential buildings healthy and safe? A survey in Hong Kong”, Structural Survey, Vol. 24 No. 1, pp. 77-86.

Wood, L., Shannon, T., Bulsara, M., Pikora, T., McCormack, G. and Giles-Corti, B. (2008), “The anatomy of the safe and social suburb: an exploratory study of the built environment, social capital and residents’ perceptions of safety”, Health & Place, Vol. 14 No. 1, pp. 15-31.

Yau, Y. (2011), “On the anti-social behaviour control in Hong Kong’s public housing”, Housing Studies, Vol. 26 No. 5, pp. 701-722.

Yau, Y. (2012a), “Insignificant or ignored? Antisocial behaviour in private housing in Hong Kong”, Urbani Izziv, Vol. 23 No. 2, pp. 103-111.

Yau, Y. (2012b), “Ruling out trouble: unacceptable behaviour and its control in Hong Kong’s public housing”, Habitat International, Vol. 36 No. 1, pp. 11-19.

Yau, Y. (2014), “Anti-social behaviour management: a communitarian approach”, Habitat International, Vol. 42, pp. 245-252.

Yau, Y. (2016), “Benchmarking the extent of quality-of-life crime: a study in Hong Kong’s public housing sector”, in Klein, A. (Ed.), Crime and Criminal behaviour, Nova, New York, NY, pp. 65-83.

Hope, T. and Hough, M. (1988), “Area, crime and incivilities: a profile from the British crime survey”, in Hope, T. (Ed.), Communities and Crime Reduction, HMSO, London, pp. 30-44.

## Acknowledgements

The final form of this article owes much to the discussion at the Workshop on Property Management and Land Management: New Challenges in Declining and Growing High-rise Cities held in Hong Kong on 13 June 2017. The work described in this paper was supported by the Research Grant Writing Fund offered by the College of Liberal Arts and Social Sciences, City University of Hong Kong.

## Corresponding author

Dr Yung Yau can be contacted at: y.yau@cityu.edu.hk