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Type
Original Research
PAGE NO.
43-50
10.37547/tajiir/Volume07Issue08-04
OPEN ACCESS
SUBMITED
18 July 2025
ACCEPTED
27 July 2025
PUBLISHED
06 August 2025
VOLUME
Vol.07 Issue 08 2025
CITATION
Maksym Ivanov. (2025). Features of ensuring security in gambling and
entertainment establishments with an increased risk of conflict situations.
The American Journal of Interdisciplinary Innovations and Research, 7(8),
43
–
50.
https://doi.org/10.37547/tajiir/Volume07Issue08-04
COPYRIGHT
© 2025 Original content from this work may be used under the terms
of the creative commons attributes 4.0 License.
Investi
Features of ensuring
security in gambling and
entertainment
establishments with an
increased risk of conflict
situations
Maksym Ivanov
Kyiv University of Tourism, Economics and Law. Organization
Management. Specialist. Dublin, IL, USA
Abstract
- The study presents a systematic review and
analysis of existing methodological approaches to
preventing and neutralizing conflict situations in
gambling and entertainment venues. The article aims to
identify the specific challenges that arise in the process
of ensuring security in gaming and entertainment
establishments, where the risk of conflict incidents is
elevated. The methodological framework comprises a
comprehensive overview of specialized scholarly
publications from 2021 to 2025, an analysis of best-
practice experience from leading industry operators,
and empirical data drawn from official statistical reports.
The investigation identifies the principal conflictogenic
factors:
substantial
financial
losses,
increased
aggression under the influence of alcohol, and
psychological instability among patrons. The limited
effectiveness of traditional reactive security systems
—
primarily focused on responding to incidents after they
occur
—
is demonstrated. To address the uncovered
deficiencies, a three-tier model of proactive security is
proposed. The practical significance of the findings is
clear for security service directors, managers of gaming
and entertainment complexes, and professionals in
criminology and corporate security.
Keywords:
casino security, conflict management,
gaming industry, situational awareness, proactive
security, conflict de-escalation, intelligent video
surveillance, player psychology, risk management,
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personnel safety.
Introduction
Gambling-entertainment
establishments
—
whether
casinos, slot machine arcades, or betting shops
—
have
historically exhibited extremely high levels of risk. The
combination of large monetary turnovers, intense
emotional surges inherent in gambling, and regular
alcohol consumption creates an environment in which
conflicts can escalate from verbal confrontations to
physical aggression.
The global gambling-entertainment industry is
experiencing sustained growth: expert projections
estimate that its market size will exceed USD 150 billion
by 2026, inevitably leading to an increased flow of
patrons and, consequently, a higher likelihood of
incidents [1]. Official statistics published by regulatory
authorities in various jurisdictions often understate the
true scope of the problem, as operators seek to
minimize reputational damage. Reports from the UK
Gambling Commission, for example, reveal persistently
high levels of disorder and violent incidents in licensed
venues [2, 11].
Recent technological advancements have produced a
dual effect: on
one hand, sophisticated video‐
monitoring and analytics systems have been deployed;
on the other hand, risks associated with mobile‐device–
based fraud schemes have increased. To date, academic
studies remain largely fragmented: they tend to focus
either on technological solutions (video surveillance,
access control) or on personnel aspects (training and
certification of security staff), without offering a unified,
proactive approach that takes into account the
psychological characteristics of gambler behavior.
The aim of the present study is to systematize existing
methodologies for ensuring security in gambling-
entertainment venues.
The scientific novelty of this work lies in the proposal of
a three‐tier model that synergistically integrates
technological, personnel, and procedural components
for the early detection of conflictogenic factors and the
preventive de-escalation of situations.
The author’s hypothesis posits that an integrated,
proactive approach focused on identifying markers of
anomalous behavior delivers a higher level of security
compared to the traditional reactive model based on
forceful intervention.
Materials and Methods
The literature on security provision in gambling and
entertainment venues with a high risk of conflict
situations can be grouped into four primary research
directions. The first direction addresses macroeconomic
and sectoral analysis, where authors systematize market
volumes, growth dynamics and the scale of participants
involved in the industry. For example, the Gambling
Global Market Report 2025 [1] offers an overview of the
global structure of the gambling market, its key
segments and principal growth drivers, while noting
potential risks of conflict escalation associated with the
expansion of the online component. Official statistics
from the Gambling Commission for November 2024 [2]
reveal trends in incidents of violence and fraud at land-
based venues in the United Kingdom, linking them to
seasonal peaks in patronage. In addition, key data from
Statista as of April 2024 [11] analyze the relationship
between the financial performance of casino operators
and the frequency of law-enforcement interventions,
enabling an assessment of macro-level conflict risks.
The second direction concentrates on technological
solutions for risk management and conflict prevention.
Khan A., Aazka K. P. [3], in their study “The Casino
Syndrome,” examine the impact of an AI
-driven
globalization trend on cultural and social aspects,
demonstrating that automated recommendation and
personalization systems may intensify gaming fervor
and provoke aggressive behavior among patrons. Liu M.
T., Dong S., Zhu M. [4], in their work on digital
technologies in the gambling industry, emphasize the
role of video-monitoring systems, visitor-behavior
analysis and predictive analytics for early detection of
group tension and potential conflicts. Finally, Yokomitsu
K. et al. [10] demonstrate the effectiveness of internet-
based personalized normative feedback (PNF) for
individuals exhibiting signs of problem gambling,
indirectly reducing the likelihood of conflict situations by
adjusting high-risk behavior before it culminates in
violence or fraud.
The third direction pertains to psychological and social
interventions aimed at reducing conflict through staff
training and community engagement. Hing N. et al. [5],
in an integrative review, show that problem gambling
significantly increases the risk of domestic violence, and
they propose incorporating impulse-control measures
into counseling programs for domestic aggressors. Mills
T. et al. [7] and colleagues evaluate a multicomponent
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Community of Practice approach to gambling-harm
reduction, in which participants exchange local de-
escalation practices, fostering the development of
adaptive strategies across diverse cultural contexts.
Similarly, Brenig D., Gade P., Voellm B. [6] investigate the
effectiveness of de-escalation technique training,
concluding that these methods can be transferred to
casino and entertainment-center staff to reduce the
number of violent incidents.
The fourth direction explores managerial approaches to
creating a service environment that minimizes conflicts.
Tsai H., Fong L. H. N. [12] study visitor-need satisfaction
in casinos and its impact on loyalty, finding that
subjective norms and perceived value of play enhance
positive emotions and lessen the likelihood of aggressive
reactions to losses. Palomba A., Zhang A., Hedlund D. [8]
analyze passive and interactive modes of sports
consumption, showing that well-organized pre-game
viewing areas for sports broadcasts can reduce tension
and emotional volatility among sports bettors. Finally,
Cheng C. C. et al. [9] describe strategic service
attributes
—
from furniture arrangement to guest-flow
management
—
that directly influence the risk of conflict
situations in casinos.
Despite the diversity of approaches, the literature
reveals certain contradictions. Some authors [3, 4]
emphasize technological solutions, while another group
[5, 7] highlights the importance of social and
psychological interventions, and a third focuses on
service-management practices [8, 12]. However,
integration of macroeconomic indicators with micro-
level de-escalation practices remains insufficiently
addressed,
as
do comprehensive studies on
architectural and engineering measures for conflict
prevention in gaming halls and on the specifics of
legislation
across
jurisdictions.
Security-service
preparedness for armed or organized groups and cyber-
security risks of access-control and video-surveillance
systems are also underexplored. Future research should
adopt an interdisciplinary approach, combining industry
statistics, technological innovations, psychosocial
interventions and service practices into a unified model
for security provision.
Results and Discussion
Based on an analysis of theoretical foundations and
advanced practices, a comprehensive security assurance
methodology was proposed, realized through a three-
tier integrated model. The implementation of this
methodology enables a radical reorientation of
processes: instead of passively responding to incidents
after their occurrence, the focus shifts to the early
detection of risk factors and the development of
preventive measures to avert conflict situations. The
construction of the model was grounded in a thorough
examination and systematic classification of the risk
parameters presented in Table 1.
Table 1. Key risk factors in gaming and entertainment venues and their manifestations (compiled by the
author based on analysis of [5, 7, 8]).
Risk factor
Behavioral indicators
Potential consequences
Financial losses
Increased irritability; striking the gaming machine;
blaming the dealer or equipment; soliciting loans
from other patrons; delaying gameplay
Aggression toward staff and other
guests;
attempts
at
fraud;
vandalism
Alcohol or drug
intoxication
Impaired coordination; slurred speech; excessive
loudness;
undue
familiarity;
inappropriate
emotional responses; falling asleep at the table or
machine
Reduced self‐control; provocation
of conflicts; sexual harassment;
inability
to
assess
situations
accurately
Psychological
instability (problem
gambling)
Prolonged gaming sessions without breaks; neglect
of personal hygiene; signs of depression or anxiety;
desperate attempts to chase losses; dishonesty
about the extent of losses
Suicidal ideation; panic attacks;
uncontrollable anger outbursts;
threats to self and others
Fraud and collusion
Unconventional
betting
patterns;
use
of
unauthorized devices; attempts to distract staff;
Financial
losses
for
the
establishment;
conflicts
upon
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coordinated actions with other players (e.g.
gestures, eye contact)
detection;
organized
criminal
activity
Interpersonal
conflicts
Disputes over bets or seating; accusations of unfair
play; personal animosity; breaches of etiquette
Verbal insults escalating to physical
altercations; disruption of the
overall atmosphere of safety and
comfort
The three‐tier integrated security model is based on
three
interrelated
subsystems
—
technological,
personnel, and procedural
—
each of which ensures the
integrity of the overall protective framework.
The first tier is the technological subsystem for proactive
monitoring. At its core lies not merely a conventional
CCTV infrastructure but an intelligent video‐stream
analysis solution. The application of modern machin
e‐
learning techniques and deep neural networks enables
real‐time processing of data from multiple cameras,
detecting statistically significant deviations in the
behavior of observed subjects [3, 4]. The architecture of
this platform is depicted in Figure 1 and comprises
modules for frame preprocessing, analytical engines for
anomaly detection and classification, and a notification
subsystem.\
According to predefined scenario templates (see Table
1), the system tracks:
•
sudden, uncontrolled physical impulses (for
example, a sharp strike against a desk surface);
•
facial‐expression changes corresponding to extreme
emotional states (such as pronounced anger, fear,
or frustration);
•
prolonged immobility within a specific zone without
any interaction with the surroundings (a classic
indicator of preparatory actions for fraudulent
behavior). Upon detecting any of these patterns, the
system does more than archive the video
recording
—
it generates a detailed alert for the
security operator, indicating the level of potential
threat and the type of anomaly recorded. This
approach allows human‐control resources to be
reallocated: rather than continuously monitoring
numerous screens, the specialist’s attention is
focused on key incidents requiring immediate
response.
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Fig. 1. Architecture of an intelligent monitoring and alerting system (compiled by the author based on the
analysis of [5, 6, 12]).
The second level constitutes a personnel subsystem
aimed at cultivating soft skills. Since even the most
advanced technological solutions prove ineffective
without qualified staff, it becomes essential to rethink
approaches to selecting and training security personnel.
Rather than emphasizing physical attributes and the
ability to use force, priority shifts to psychological
resilience,
acute
observation,
and
high-level
communication abilities. A mandatory component of
this subsystem is an intensive course in verbal and
nonverbal de-escalation techniques. Within this course,
staff learn to diagnose in detail the stages of tension
escalation and practice a repertoire of methods for each
phase: from active empathetic listening and
paraphrasing grievances to strategies for distraction and
the formulation of constructive solutions (for example,
escorting the disputing party to a specially arranged area
for calm dialogue or offering non-alcoholic beverages).
A consolidated analysis of outcomes from various
training programs demonstrates a significant increase in
effectiveness compared with traditional methods.
The third level
—
the procedural subsystem of adaptive
response
—
serves as the nexus between AI technologies
and personnel through clearly defined yet flexible
standard operating procedures (SOPs). For each type of
alert generated by the artificial intelligence system (level
1), a specialized staff action algorithm (level 2) is
developed. For instance, upon detection of a “low
-
intensity, verbal aggression” alert,
a soft-intervention
protocol activates: a specially trained employee
—
who
need not wear a uniform and may be the floor
manager
—
approaches the visitor and politely inquires
whether everything is all right. Conversely, a “high
-
intensity, physical threat” aler
t triggers a different
scenario, involving the immediate dispatch of the
nearest response team to the incident location and
notification of the shift supervisor. A detailed flowchart
of actions for pre-conflict situations is presented in
Figure 2. An important element of this level is
integration with Responsible Gambling programs: the AI
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system monitors session duration as an indicator of
potentially risky behavior, and under the SOP, an
employee discreetly informs the client of the elapsed
time and suggests taking a break.
Fig. 2. Algorithm for the security service’s response to a pre
-conflict situation (compiled by the author based on
the analysis of [7, 9, 10]).
The integration of three complementary layers
generates a synergistic effect that surpasses the sum of
their individual impacts. Modern technological solutions
enable the early detection of potential incidents
—
capabilities that cannot be achieved by relying solely on
visual and auditory monitoring of personnel across a
large facility. Highly qualified staff perform the so-called
“last mile” of interaction, transforming automated alerts
into informed socio-psychological interventions that
help de-escalate tense situations. Standardized action
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algorithms and regulated procedures eliminate
uncertainty and minimize the likelihood of human error
under critical conditions, thereby maintaining a stable
and predictable level of security.
Implementing such a multilayered model not only
reduces direct costs associated with property damage,
litigation, and compensation payments, but also
enhances indirect economic benefits. Creating a safe
and comfortable environment strengthens the trust and
loyalty of the majority of visitors, who seek positive
experiences rather than exposure to stressful incidents;
this, in turn, positively influences the long-term financial
performance of the facility.
A predictive analytics model
—
based on the assessment
of each system element’s effectiveness both in isolation
and as part of the whole
—
demonstrates the potential
for a substantial reduction in conflict incidents upon full
implementation of the proposed system [4, 7].
The final concept transcends a mere compilation of
recommendations, establishing a comprehensive
methodological platform for developing an adaptive,
highly efficient, and human-centered security system in
the gaming and entertainment industry. Such a system
not only addresses the technological and sociocultural
challenges of the twenty-first century but also embeds
the principles of a humanistic approach, ensuring
continuous procedural evolution, responsive flexibility,
and a balance between guest comfort and risk
protection.
Conclusion
A comprehensive analysis of sector-specific literature
and industry practice confirmed the initial hypothesis
that a proactive integration of technological, personnel,
and procedural elements is markedly more effective
than reactive measures in preventing and mitigating the
scale of conflict situations. As a result, the primary risk
factors and characteristic behavioral indicators were
identified, upon which an early threat detection system
can be configured. The application of the proposed
model promises not only a significant reduction in the
number of incidents and associated losses but also
contributes to enhancing the establishment’s public
image, thereby increasing its appeal to a broader
audience. Prospects for further research include
empirical validation of the developed framework under
real-world conditions, the formulation of a methodology
for quantitatively assessing its economic efficiency, and
an examination of the ethical implications of deploying
artificial intelligence technologies for visitor behavior
monitoring.
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