1. Venue-Level Predictors of Alcohol-Related Violence:
An Exploratory Study in Melbourne, Australia
Anthony John McFadden1
& Martin Young1
&
Francis Markham2
# Springer Science+Business Media New York 2015
Abstract The direct and indirect socio-economic costs associated with alcohol-related vio-
lence in the night economy are significant and escalating. This violence tends to be associated
with a small proportion of venues. Little is known about which risk factors are most closely
associated with alcohol-related aggression at the venue level. Alcohol-related aggression was
measured through a novel survey of industry experts on the Melbourne night-economy.
Individual venue risk factors were measured via an exploratory observation study of 45
venues. Associations between alcohol-related aggression and observed risk factors were
identified using non-parametric multivariate, conditional inference trees. The venue character-
istics most associated with alcohol-related aggression were prominence of alcohol promotion,
level of rowdy behavior, and the extent to which music contained aggressive or violent
language. These results suggest that either through liquor accords, voluntary codes of practice,
or state mandate, practitioners are able to reduce the level of alcohol-related violence associ-
ated with their venue by taking simple, mediating actions.
Keywords Night economy . Licensed premises . Alcohol . Aggression . Violence
Int J Ment Health Addiction
DOI 10.1007/s11469-015-9552-3
The authors offer sincere thanks to Dr Alasdair Forsyth, Glasgow Caledonian University, Scotland, and Dr
Kathryn Graham, Centre for Addiction and Mental Health, Canada, for permission to use their research
instruments in this project, and Dr Michael Livingston and Dr Amy Pennay, Turning Point Alcohol and Drug
Centre, Australia, for their suggestions at the research design stage.
* Martin Young
martin.young@scu.edu.au
Anthony John McFadden
aj@urbnmind.com
Francis Markham
francis.markham@anu.edu.au
1
School of Tourism and Hospitality Management, Southern Cross University, Hogbin Drive, Coffs
Harbour, NSW 2450, Australia
2
Fenner School of Environment and Society, The Australian National University, Canberra, ACT
0200, Australia

2. During the last 30 years, economic restructuring, the expansion of the hospitality and leisure
industries, and softening of moral attitudes towards public alcohol consumption have pro-
foundly affected the form and character of contemporary cities (Chatterton and Hollands
2003). Post-industrial urban landscapes have been reinvented as dedicated leisure, entertain-
ment and residential precincts (i.e., retail shopping, restaurants, theatres, bars and nightclubs)
(Hannigan 1998; Hobbs 2005; Zukin 1992). An unintended consequence of the emergence of
this night economy, and the associated liberalization of alcohol supply in specific urban
districts, has been a sharp increase in alcohol misuse, alcohol-related aggression, and social
disorder (Hadfield 2006; Hayward and Hobbs 2007). In the state of Victoria, Australia, where
this research was conducted, the total cost of direct and indirect alcohol-related harm was
estimated to be AUD 4.3 billion in 2009 (Allen Group 2009). Moreover, the level of alcohol-
related aggression in the night economy has increased significantly over the last decade.
Between 2001 and 2011 reported alcohol-related violence in Victoria increased by 49 %
(Victorian Auditor General 2012). This violence is directly related to the number of alcohol-
serving businesses in the night-economy. For example, in 2007–08, 10 % of all Victorian
public place assaults occurred inside licensed premises and many more occurred on streets and
sidewalks adjacent to them. Over 25 % of these were recorded by police as involving alcohol
(DCPC 2010).
The growing incidence of alcohol-related assault, increasing policing and healthcare
costs, and concerted community pressure have compelled governments to grapple with
drunken violence. While entertainment and leisure industries make significant contri-
butions to the economic and cultural profile of post-industrial cities, the fundamental
challenge facing night-economy regulators is how to promote a vital and diverse
leisure industry whilst simultaneously reducing alcohol-related violence (Jayne et al.
2011). Individual premises may potentially play an important role in harm reduction.
Drinking establishments are the cornerstones of the night economy providing regulated
space where alcohol service and consumption conditions can be altered. As such, they
are key sites for interventions targeting alcohol-related violence and night economy
disorder.
The majority of alcohol-related violence occurs in a small proportion of risky
venues, usually late trading, large capacity nightclubs and pubs (Eck et al. 2007;
Stockwell 1997). Knowledge of venue-level risk factors may assist regulators to
modify drinking environments in order to reduce the incidence alcohol-related vio-
lence (Anderson et al. 2012). The goal of the current project is to identify the
environmental risk factors that are associated with alcohol-related aggression within
individual venues. To this end, the exploratory multivariate relationships between
venue-characteristics and alcohol-related aggression are tested for 45 businesses in
the Melbourne night-economy. An identification of the venue-level risk factors most
closely related with high levels of alcohol-related aggression may assist regulators to
better manage alcohol-related violence through environmental modification.
Licensed Premises and Alcohol-Related Aggression
The link between licensed premises and violence is long-established (Kumin 2005). Not only
are drinking establishments the sites of routine crime and violence, they are directly associated
with disproportionate levels of alcohol-related harm (Rowe et al. 2010; Mazerolle et al. 2012).
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3. For example, licensed premises are the third most common Australian setting for assault
leading to hospitalization or homicide, with 10 % of cases occurring in the proximity of a bar
(Langley et al. 1996). Research conducted in Sydney, Australia, finds that 44 % of all assaults
(excluding domestic violence) and 60 % of alcohol-related violence occurs in and around
drinking establishments (Ireland and Thommeny 1993). Indeed, studies of bar room aggres-
sion have consistently detected a link between the level of violence and level of patron
intoxication (e.g., Forsyth 2006; Graham 2003; Homel et al. 1997; Lincoln and Homel
2001). Both individual consumption and the proportion of patrons who are intoxicated are
associated with aggression (Graham et al. 2004; Homel et al. 2004). Furthermore, the overall
level of patron intoxication has a significant relationship with the frequency, severity and
escalation of aggressive incidents (Forsyth et al. 2005; Leonard et al. 2003; Roberts 2007).
Beyond the direct alcohol-violence link at the individual level, venue-specific factors also
affect violence outcomes. How businesses serve and manage alcohol consumption (e.g.,
alcohol promotion, service to intoxicated patrons, etc.) are significant predictors of aggressive
behavior (Graham 2000; Stockwell et al. 1993).
However, not enough is known about the environmental-level venue risk factors that are
associated with alcohol-related aggression. Hughes et al. (2011), in a systematic review of
research on the environmental variables in licensed premises, identifies a wide range of risk
factors that act synergistically to produce alcohol-related aggression in the drinking environ-
ment. These include physical factors (cleanliness and crowding), patron characteristics (age
and gender), social factors (permissive atmosphere, sexual activity) and organizational factors
(management practice and staff training) (Hughes et al. 2011; cf. Plant et al. 2007). The way in
which these risk factors combine in specific venues to produce high assault rates in particularly
violent venues is of particular importance.
Indeed, the majority of alcohol-related violence occurs within a small proportion of risky
venues, such as late-trading, large-capacity nightclubs and pubs (Eck et al. 2007; Stockwell
1997). For example, NSW Police assault statistics show that 12 % of inner city Sydney venues
accounted for 60 % of alcohol-related assaults associated with licensed premises over a 2 years
period (Briscoe and Donnelly 2003). Furthermore, a longitudinal European study examining
clusters of large capacity nightclubs shows that the risk of assault to be 50 % higher in and
around specific licensed premises (Warburton and Shepherd 2006). Research conducted in
New South Wales, Australia, finds that intoxicated persons involved in assault across 21
metropolitan police command areas are nearly twice as likely to have consumed alcohol in bars
and night clubs as opposed to other settings (Rowe et al. 2010). In addition, 20 % of venues
accounts for 80 % of these assaults.
Considerable research evidence associates venue-specific risk factors with elevated vio-
lence (Graham et al. 2006a, b, c; Homel et al. 2004; Quigley, Leonard, & Collins 2003). The
most important risk factors include patron intoxication, physical discomfort (i.e., dirtiness,
poor ventilation), permissive atmosphere (i.e., lack of enforcement of social rules), negative
social interaction (i.e., sexualised behaviour) and poor organisational practices (i.e., lack of
responsible service of alcohol) (Graham et al. 2006a; Graham et al. 1980; Homel et al. 2004;
Forsyth 2006).
The identification and management of the environmental and situational risk factors that are
associated with alcohol-related aggression may potentially play an important role in reducing
alcohol-related harm in the night-economy (McIlwain and Homel 2009). Yet the management of
alcohol-related violence in the night economy is complex and challenging. Governments require
the most efficient and effective regulatory tools in order to minimize harm without placing an
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4. excessive regulatory burden on businesses (Graham and Homel 2008). Research focused on
environmental venue risk factors adds to the evidence base available to policymakers and police,
thereby improving their capacity to monitor and respond to problem venues (Wiggers et al.
2004). Research which specifically examines how venue risk factors in drinking establishments
are related to aggression provides important information for evidence-based venue-level inter-
vention strategies (McIlwain and Homel 2009). Hence, a refined knowledge of situational venue
characteristics most associated with aggression may be used to: a) develop adaptive and flexible
venue risk auditing tools for compliance units and regulatory authorities, and b) enhance liquor
legislation and regulatory compliance to reduce violence in licensed premises (Stockwell 2001).
Existing programs such as the Safer Bars Program (2000) in Ontario, Canada and the No More
Risky Business (2012) initiative in Queensland, Australia, represent applied examples of the
ways in which situational venue risk factors may be evaluated and modified to reduce aggression
in the drinking environment (Hauritz et al. 1998).
The current study focuses specifically on alcohol-related aggression in licensed premises,
an issue of growing community cost and concern at both individual and population levels
(Anderson et al. 2012). Specifically, this exploratory research aims to identify the risk factors
most closely associated with alcohol-related aggression for venues in the Melbourne CBD
night-economy.
Material and Methods
Study Area and Sample
Study Area
Licensed premises have proliferated in the City of Melbourne since a 1985 inquiry into alcohol
regulation recommended an expansion of the night economy (Nieuwenhuysen, 1986). The
number of licensed premises in the Melbourne Central Business District (CBD) increased by
67 % between 2000 and 2007, rising from 579 venues to 966 venues (City of Melbourne
2008). As of 2008, the greater Melbourne Metropolitan area had approximately 1600 licensed
premises (City of Melbourne 2008).
Considerable economic and social costs have accompanied this expansion of the night-
economy. In 2009–2010, 2568 assaults were committed in the Melbourne CBD, which
constitutes a 4 % increase on 2008 figures and a 35 % increase in CBD assaults since 2005
(Tomazin 2011). Furthermore, ambulance attendances increased by 258 % in Metropolitan
Melbourne between 2000–01 and 2010–11 (Victorian Auditor General 2012). Notably, in
2007–08, 10 % of all public place assaults occurred in licensed premises and over 25 % were
flagged as involving alcohol (DCPC 2010).
Sampling
The authors obtained a database of licensee details (i.e., venue name, address, capacity and
trading terms) for all licensed premises within the Melbourne CBD (as delimited by the
postcode 3000 boundary) from the website of the Victorian Commission for Gambling and
Liquor Regulation (VCGLR 2012) in May 2012. In total 155 late trading premises were
identified. A two-stage sampling strategy was used. In the first stage, 60 late-trading premises
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5. were selected for inclusion in the study using a non-proportional probabilistic stratified
sampling design, with six stratum containing 10 premises. Strata were defined according to
venue type (hotels, bar or nightclub) and geographic location (east or west of Swanston Street).
Outcome variable data were collected for this primary sample of 60 venues.
Due to logistical constraints, predictor variables could only be collected in 45 venues,
necessitating a second sampling stage. In this stage, 45 venues were selected from the frame of
60 venues using non-proportional probabilistic stratified sampling. The sum of the physical
aggression (PA) and non-physical aggression (NPA) outcome variables was bracketed to into
four sampling strata (1–3, 4, 5, and 6–7). The first and fourth brackets were exhaustively
sampled in order to gain sufficient representation of the tails of the risk distribution, while the
remaining venues were probabilistically sampled from the central two strata. This resulted in
12, 11, 8, and 14 venues selected from each stratum respectively.
Measures
Outcome Variables The authors developed two measures of aggression risk for late-trading
premises as the outcome variables of the study, following the definitions of (Graham et al.
2006c). Non-physical aggression (NPA) was defined as: expressing anger or disapproval;
abusing, swearing at, shouting at, insulting or demeaning someone; mutual arguments (verbal
disagreements between willing parties); explicit threats, challenges, or attempts to initiate a
fight; provocative or aggressive rule breaking; unwanted sexual overtures; or intimidation.
Physical aggression (PA) was defined as: pushing or shoving; pulling or grabbing; intentional
bumping; unwanted sexual contact; holding or restraining; punching; slapping; glassing;
throwing décor or persons; or miscellaneous (e.g., hair pulling, pinching, kicking).
PA and NPA were estimated for licensed premises through a survey of industry experts.
Purposive sampling was used to select an export cohort including bar managers, venue
managers, event managers, bar staff, security guards and entertainers. The decade long
involvement of the first author in the Melbourne music industry facilitated the identification
of a diverse and experienced sample of industry professionals. Access to industry experts is
unusual as most routinely reject research enquiries, producing a novel and valuable data set,
one not easily replicated.
A confidential questionnaire was administered face-to-face to the industry experts (n=18)
by the first author in June 2012. For each venue in the study, respondents were asked: How
often would you expect NON-PHYSICAL alcohol-related aggression to occur in the venue?
and How often would you expect PHYSICAL alcohol-related aggression to occur in the venue?
Possible answers were Never; Rarely; Sometimes; Often; Always; or Don’t Know, with values
Never to Always assigned a value of 0 to 4. NPA and PA for licensed premises were calculated
as the venue mean of respondent ratings, with Don’t Know responses removed listwise.
Respondents were provided with the definitions of physical and non-physical aggression
detailed above. The order of licensed premises in the survey instrument was randomized in
each questionnaire to mitigate against order-bias effects.
Inter-rater reliability of PA and NPA measures was assessed by calculating two-way
random intra-class correlations (ICC). Inter-rater reliability was very high, with ICC
(2,18)=0.87 (95 % confidence interval: 0.75, 0.91), meaning that between 75 and
91 % of the variance in the mean aggression scores of industry experts represented
variation in the underlying constructs.
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6. Predictor Variables Predictor variables were generated by conducting a series of structured
in-venue observations. The observation instrument was adapted from that of Alasdair Forsyth
(2006) and Kathryn Graham (Graham 2000, 2006), versions of which have been extensively
used in studies in Australia (e.g., Homel et al. 2004), Canada (e.g., Graham et al. 2006c) and
the United Kingdom (e.g., Forsyth 2006). The observation instrument was comprised of 32
measurements of venue characteristics, grouped into four categories. The first section dealt
with aspects of venue maintenance and atmosphere. The second section measured levels of
apparent alcohol intoxication, patron decorum and demographics. The third section addressed
venue governance and patron interactions. The fourth section dealt with marketing and music
content. The measures were selected from Alasdair Forsyth’s more extensive instrument on the
basis of: a) speed of assessment, b) a demonstrated association with aggression in previous
studies, and c) applicability to the bar area and dance floor, two important hotspots for
aggression (Graham et al. 2011). The instrument was refined after pilot testing, with the
addition of questions relating to operational capacity, patron boredom and food service.
The first author attended each assessed venue for approximately 25 min over nine nights in
June and July 2012. All observations were made on a Thursday, Friday or Saturday night
between the hours of 10 pm and 3.30 am. The time of observation was recorded and used in the
explanatory modelling to control for temporal variation in predictor variables (e.g., rowdiness).
Industry contacts provided priority entry where admittance was anticipated to be difficult or
entry queues extensive. Consistent with Graham et al. (2006a), the first author purchased a non-
alcoholic beverage in each venue which made him less conspicuous, enabled the close
inspection of alcohol promotions and ensured an engagement with the bar staff. The first author
also dressed in a manner similar to the clientele of each venue in order to be as unobtrusive as
possible. The observation instrument was completed immediately after exiting the venue.
Analytical Approach (300 Words)
Multivariate conditional inference trees, a type of recursive partitioning, were used to identify
the combination of predictor variables that were most associated with alcohol-related aggres-
sion. Recursive partitioning, also known as decision tree analysis, provides a non-parametric
framework for identifying groups of licensed premises with similar risk outcomes by repeat-
edly splitting groups of premises into smaller and more homogenous subgroups. Because
recursive partitioning models interactions rather than independent linearly-additive effects,
recursive partitioning is particularly well suited to datasets with relatively few observations per
predictor variable (so-called large p, small n problems) (Zhang and Singer 2010). As applied in
this research, conditional inference trees can provide IF-THEN rules for identifying venues
with different risk profiles. This format is particularly useful in applied research as these
outputs are readily understood by policymakers who may lack the statistical knowledge
required to interpret more sophisticated outputs such as the coefficient estimates and p-values
resulting from a multivariate generalized linear model (Breiman 2001).
Two separate conditional inference tree models were constructed, one for each of the
outcome variables (PA and NPA). All measures on the in-premises observational instrument
were used as predictor variables. Permutation tests of independence were used to ensure that
each split was statistically significant at the α=0.05 level. Terminal nodes were required to
have at least 10 observations. Bonferroni-adjusted p-values of splits were used as a stopping
criteria to reduce type-I errors associated with recursive partitioning methods such as CART
and C4.5 (Hothorn et al. 2006).
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7. The Human Research Ethics Committee of Southern Cross University approved this
research (clearance no. ECN–12–107).
Results
A summary of violence risk ratings derived from the industry experts survey is presented in
Table 1. The mean NPA and PA scores across these venues are 2.1 (SD=0.7) and 1.8 (SD=
0.8) respectively. Average observed venue characteristics are also presented in Table 1.
Figure 1 presents the results of the recursive partitioning analysis including all predictor
variables and NPA as the outcome variable. The venue characteristics most strongly associated
with NPA are the visibility of alcohol promotions and the level of patron rowdiness. The
riskiest subgroup of venues have a median violence risk score of 2.7 (MAD=0.4) and is
defined as premises where alcohol products and specials are promoted prominently or
extremely prominently. In lower risk venues where alcohol promotions are displayed no more
than somewhat prominently, multivariate analysis identifies rowdy patron behavior as the most
important predictor of non-physical alcohol-related aggression. The least risky venues, where
alcohol is promoted no more than somewhat prominently and patron behavior is only slightly
rowdy, had a median risk rating of 1.6 (MAD=0.3). Between these extremes, a third group of
venues (median=2.0, MAD=0.3) with limited alcohol promotions but a greater level of
rowdiness is identified.
Figure 2 presents the results of the conditional inference tree analysis with PA as the outcome
variable. Once again, the riskiest subgroup of venues (median=2.5, MAD=0.4) is defined as
premises where alcohol products and specials are promoted prominently or extremely promi-
nently. The most important characteristic splitting the lower risk venues is the extent to which
house music contained aggressive or violent language and imagery. Those venues whose music
contains no signs of aggression have a median rating of 1.2 (MAD=0.3), while those with at
least partially aggressive music have a median risk rating of 1.5 (MAD=0.2).
Discussion
The industry expert survey produced a measure of aggression that is reliable between
respondents and is an effective tool in this research context. Unlike police assault records,
the industry expert survey measures both non-physical and physical alcohol-related aggres-
sion. This is important because non-physical aggressive actions (i.e., verbal abuse, arguing) not
only heighten the risk of physical aggression but also represent a core component of violence
in drinking establishments (Graham et al. 2006c). The survey demonstrates high inter-rater
reliability suggesting good face validity. Research into fear of crime suggests that subjective
appraisal of risk and violence is more important in modifying behavior (e.g., in terms of
protective and avoidance behaviors) than the objective incidence of crime as measured by
police local crime (Doran and Burgess 2012). Therefore, replication and comparison with
reported assault statistics and observed incidents of alcohol-related aggression would be
useful.
In addition, this study shows that rapid venue risk audits are logistically feasible. Venue risk
factors that may be audited in short periods of time are able to differentiate risky from non-
risky venues. Rapid assessment tools may be utilised in three key ways: 1) as an early warning
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8. system identifying problem venues and maintaining an up–to-date venue risk index, 2) to
enhance targeted evidence based policing of high-risk premises, and 3) in the formulation of
site specific strategies to curb aggression. Such approaches may provide an additional, robust
tier of venue risk assessment complimenting the risk-based liquor licensing frameworks
currently favoured in jurisdictions such as Victoria, Australia.
The prominent promotion of alcohol (e.g., discounted alcoholic energy drinks such as
Jägerbombs and pre-mixed drinks, excessively cheap drinks, extended happy hours, Bbuy two,
get one free^ discounts, etc.) is the strongest individual predictor of both physical and non-
physical alcohol-related aggression. This association is likely produced by alcohol promotion
intensifying the rates of intoxication and hence violence (Stockwell et al. 1993). Indeed, other
Table 1 Summary of observed
predictor variables for venues
N=45
Variable Mean SD
Female patrons (%) 43.8 11.4
Age group 18–21 (%) 31.3 23.8
Age group 21–29 (%) 46.1 9.9
Age group≥30 (%) 22.7 18.8
Groups of≥3 males (%) 20.9 13.4
Non-Caucasians (%) 22.2 13.2
Ventilation (0–9) 2.9 1.2
Surface cleanliness (0–9) 3.5 1.6
Floor cleanliness (0–9) 3.4 1.4
Toilet cleanliness (0–9) 2.8 1.8
Patron movement (0–9) 3.5 1.7
Dance floor crowding (0–9) 3.7 2.1
Bar crowding (0–9) 3.7 1.5
Music volume (loudest) (0–9) 6.4 1.6
Music volume (quietest) (0–9) 4.1 1.7
Operational capacity (0–9) 4.8 1.6
Alcohol intoxication (0–9) 4.8 1.6
Rowdiness (0–9) 3.9 1.7
Patron boredom (0–9) 4.0 1.6
Venue monitoring (0–9) 4.7 1.2
Security attitude (0–9) 3.7 1.8
Bar staff attitude (0–9) 3.4 1.7
Permissiveness (0–9) 4.2 1.3
Sexual activity (0–9) 3.6 2.0
Sexual competition (0–9) 3.2 2.2
Competitive games (0–9) 1.6 2.6
Aggressive music (0–9) 3.2 2.1
Sexualised music (0–9) 4.4 1.5
RSA display (0–9) 4.4 1.0
Alcohol promotion (0–9) 5.6 1.6
Beverage cost (AUD) 4.8 0.5
Food service (0–9) 6.3 2.3
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9. Fig. 1 Conditional inference tree predicting risk of non-physical aggression in licensed premises. R2
=0.58, n=
45. med. = median, MAD=median absolute deviation
Fig. 2 Conditional inference tree predicting risk of physical aggression in licensed premises. R2
=0.56, n=45.
med. = median, MAD=median absolute deviation
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10. research finds a positive relationship between within-premises alcohol promotion and exces-
sive drinking over extended periods (Forsyth et al. 2005). However, in the current study,
alcohol promotion is the strongest individual predictor of aggression, implying that promotions
are associated with violence risk at a level over and above the pharmacological effects of
intoxication. This may be because promotions of alcoholic beverages, particularly combina-
tions of alcohol and energy drinks, encourage patterns of risky drinking behavior (i.e., fast rate
of drinking, round buying) and produces mass patron intoxication (i.e., cheap drinks, drink
specials) which are clearly linked to aggression (Forsyth et al. 2005; Lincoln and Homel
2001). Furthermore, the physiological impacts of energy drinks may mask the pharmacolog-
ical and behavioral effects of alcohol allowing for increased alcohol consumption (Miller et al.
2013). The presence of energy drink stimulants adds an additional dimension of complexity
and difficultly to accurate RSA assessment (i.e., service refusal) of patron intoxication by bar
staff.
The multivariate analysis also reveals that rowdy behavior is an important predictor of non-
physical aggression. This finding is consistent with prior studies that suggest venue permis-
siveness (i.e., tolerance for rowdy behavior) is strongly associated with aggression, in some
studies more powerfully than alcohol effects (Graham et al. 2006a). The strength of the
association is based on the perceptual role (i.e., establishing patron behavioral expectations)
and the direct role (i.e., directly provoking aggression through patron interplay) of rowdy
behavior in precipitating aggression (Graham and Homel 2008). For example, roughhousing,
even if not originally intended as aggressive, can provoke an aggressive response (Felson and
Steadman 1983). The escalatory quality of patron rowdiness may explain its association with
both the frequency and severity of aggression (Graham et al. 2006c). More broadly, this
evidence confirms the significance of social risk factors as environmental precipitators of
aggression.
In addition, music with aggressive content was an important predictor of physical aggres-
sion. Aggressive music may encourage violent interactions or exacerbate conflicts. More
broadly, music programming may play an important role in setting the tone of an
establishment and manipulating the mood of its patrons. As Forsyth (2009) argues, different
types of music may act as precipitators of aggression, especially music of certain genres (e.g.,
Hip Hop and Heavy Metal). Conversely, this finding suggests that patron behavior may be
modified through sonic governance (Hadfield 2009). As loud, overtly sexual and aggressive
music may directly produce rowdy behavior and be associated with a permissive environment,
effective programing and the training of entertainers may be an additional situational deterrent
that increases patron decorum and reduces in-premises violence (Graham 2009).
These applied strategies align with research showing that targeted enforcement of alcohol
supply, specifically though RSA laws, significantly impacts intoxication levels, server prac-
tices, rate of assault injuries, and overall levels of night economy violence and disorder (Jeffs
and Saunders 1983; Sim et al. 2005). Therefore, strategically regulating the composition of
alcohol promotions (i.e., limiting the promotion of high-risk products such as Jägerbombs and
pre-mixed energy drinks, and limiting drinks discounting) should be viewed as a useful
regulatory tool (Babor et al. 1980). Furthermore, venue staff training which includes tech-
niques to identify and defuse aggression and manage rowdy behavior are key measures which
may be applied at a premises level to strengthen RSA programs and prevent escalation of non-
physical aggression to physical violence (Graham and Homel 2008).
At one level, these modifications to night economy business practices may reduce the
amount of revenue earned from alcohol sales in venues with higher risk-profiles. However,
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11. alcohol-related aggression is associated with substantial direct and intangible costs, such as
extra security staffing costs, risk of temporary or permanent closure by regulatory authorities,
potential violence-related legal liabilities, reduced staff wellbeing and productivity, occupa-
tional health and safety costs, and lost custom. As such, a reduction in aggression-related costs
may compensate for revenue foregone from potential alcohol sales.
Limitations
The subjective nature of the venue observations made by the first author may have prejudiced
the measurement of venue risk factors. For example, the first author was aware of the
composite aggression score and risk category of each venue prior to observation which meant
that measurements may have been influenced by access to survey participant’s perceptions.
Additionally, a pre-existing perception of the violence risk for each venue may have influenced
impressions, and subsequently measurement, of risk factors. While this was acceptable in the
exploratory study, a more comprehensive follow-up would require two or more observers
conducting assessments simultaneously. This would also allow for temporal randomization.
We accounted for this by including time of observation as a predictor variable, and it was not
statistically significant. Larger studies would ideally include a randomized design for venue
selection. In addition, the Industry Expert Survey is a subjective measure of aggression based
on the perceptions of stakeholders. These perceptions may have been influenced by competing
interests such as rating a competitor’s venue poorly, although the high inter-rater reliability of
the Industry Expert Survey suggests that this does not substantially bias the results.
Conclusion
The prominent promotion of alcohol is consistently identified as the most important predictor
of both physical and non-physical aggression in late-trading premises. For venues with less
prominent promotions, the level of rowdy behavior (NPA) and the aggressiveness of music
content (PA) are the next most important predictors of violence. These findings are encourag-
ing for individual businesses and regulators seeking to reduce the incidence of alcohol-related
aggression. Operators may be able to reduce violence within their premises by adopting some
relatively straightforward measures. Application of RSA policies which relate to the sale and
marketing of alcohol should be followed by night-economy businesses. Regulators may wish
to consider more effective enforcement of existing RSA policies regarding alcohol promotion.
Indeed, RSA regulations which further restrict alcohol promotions that cause mass intoxication
(i.e., permanently discounted drinks, shooters) and in particular alcohol and energy drink
combinations should be considered.
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