Examining the Use of Offshore Online Gambling Sites in the United States via Routine Activities Theory: A SEM Analysis

Abstract

Despite the recent proliferation of legal online gambling in the Unites States, offshore gambling sites still remain prevalent, causing various problems in the U.S. Although numerous law violations occur in this domain, prior research has reported limited information about offshore gambling, mostly focusing on offshore gamblers’ characteristics and motivations. Using routine activities theory, this study attempted to understand environmental and theoretical factors that affect the use of offshore sites by focusing on offshore gambling-generating contexts that involve offshore sites and online casino reviews. Major findings show that the online visibility of offshore sites may be a key predictor of the use of the sites by U.S. players. In addition, online casino reviews providing a blacklist of online gambling sites served as informal guardians, helping players avoid unreliable offshore gambling sites that pose a risk to their customers. Policy implications were suggested based on the findings and provided insights toward effective online gambling regulatory efforts.

Introduction

The U.S. has recently experienced the relaxation of gambling prohibitions (both offline and online). Internet gambling has historically been federally restricted in the U.S., yet its permits can be issued on the state level. Indeed, a growing number of states have recently legalized online gambling. Only a few states, including Nevada, Delaware, and New Jersey, offered certain forms of legal online gambling before the first half of 2018; however, a proliferation of legal online sports betting across the states, caused by the repeal of the former federal ban on interstate sports betting in 2018, has expanded the legal online gambling market in many parts of the country. Legal online gambling is now available in more than twenty states in 2023 (“States that offer,” n.d.).

Despite the recent expansion of legal online gambling market in the U.S., the ‘black market’ of online gambling sites continue to benefit from American players. The American Gaming Association (AGA)’s report in 2019 showed that approximately $150 billion worth of wagers placed by Americans went to illegal sports betting operations each year (p. 7). Furthermore, its survey on U.S. sports bettors in 2020 reported that the number of U.S. players using offshore online sports betting sites increased 24% in states where sports betting is not yet legalized and even 3% in legal states from a year ago (American Gaming Association, 2020). These illegal online gambling sites do not hold a valid license issued by gambling authorities in the United States but can be accessible from the U.S. regardless of their base and legitimacy in other jurisdictions (Gainsbury et al., 2018). Most of these sites are known as offshore gambling sites that operate outside of the U.S., but tend to accept bets from customers who reside in the jurisdictions where their operating license is not valid (Gainsbury, Abarbanel, & Blaszczynski, 2019; Schmidt-Kessen et al., 2019).

Offshore gambling sites are a major concern for local governments (Gainsbury et al., 2013, 2019). As they are not subject to the regulations set by the U.S. gambling authorities, offshore sites are mostly free from any obligation imposed on operators licensed within U.S. borders. For instance, they are less likely than domestic/regulated ones to provide robust consumer protections or encourage responsible gambling practices (Gainsbury et al., 2019; Gainsbury, Parke &Suhonen, 2013). Also, they don’t need to abide by federal anti-money laundering compliance requirements and other financial obligations (e.g., local taxes and licensing fees) imposed by U.S. gambling authorities. At the same time, the fact that most offshore sites are based in “tax haven countries” allows them unfair competitive advantages over domestic operators;specifically, such financial evasion enables them to maintain their operation with lower costs, offer customers higher odds and better services, and provide more features as well as a wider variety of gaming options (Gainsbury et al., 2018, 2019). Therefore, the entrenchment of offshore gambling entities is a serious threat that poses a potential risk to players, compromises the value of domestic, legal, taxpaying gaming entities, and harms the local economy.

Not all of offshore sites are reliable; some of them have shown that they can engage in shady practices to take money out of the players' bank accounts. For instance, some sites lure naïve players by posing as legitimate ones or use targeted advertising to promote their sites to target problem gamblers seeking help (Cole, 2020); others even allow players to bet on nonsport events, such as the daily number of COVID-19 cases (Gomes, 2020). Some gambling sites are rogue, financially victimizing their customers or, in reverse, they can be targeted by criminals for money laundering (Lo, 2014), cyberattacks (Johnson, 2020), or gambling with stolen identities (Danzis, 2021).

Normally, players wish to avoid using these unreliable online gambling sites; therefore, many players tend to rely on online sources—such as online gambling reviews—to glean information regarding online gambling sites before placing a bet online. Online gambling (casino) reviews are websites that offer a wide range of information about online gambling, such as site reviews and promotions, news, and gambling laws. Some also provide a blacklist of online gambling sites—a list of rogue, unreliable online casinos reported by players—which helps players avoid using malicious online gambling sites. Therefore, online gambling reviews not only play a substantial role in reducing the distance between players and online gambling sites but also act as informal guardians in keeping players away from malicious offshore sites (Sutevski, n.d.).

Although offshore sites have been subject to crackdowns by United States’ (U.S.) government agencies for a long time (“Online Gambling Don’t Roll the Dice”, 2007), the pervasiveness of offshore online gambling could indicate that regulatory and law enforcement agencies’ efforts to eradicate them have not been historically effective. It is known that a number of law enforcement agencies still lack the ability to investigate cybercrimes effectively and are struggling to keep pace with criminals’ evolving technologies (Choi, 2015). Although shutting down illegal online gambling business is technically not impossible, there are many obstacles discouraging regulation efforts. These businesses make it difficult to track themselves by hiding their servers and identities with various schemes in cyberspace, such as proxy sites, domain proxy services, webhosting companies, or multiple relay servers placed in different jurisdictions (Choi et al., 2020). Additionally, while there are federal laws (such as the Unlawful Internet Gambling Enforcement Act of 2006 that targets banks and credit card processing firms to prohibit money transfers to offshore gambling sites), a variety of alternative payment processes have been employed to circumvent the laws, such as e-wallet, money order, prepaid cards, and checks. More recently, cryptocurrencies have been widely used for online gambling transactions, as they enable de facto anonymous, complex transactions and make international transactions easier, faster, and cheaper (Gainsbury & Blaszczynski, 2017; Millar, 2018).

Understanding why illegal online gambling happens in the U.S. is an important step toward designing an effective preventive measure suitable for the U.S. context. Many prior gambling studies took a micro- level view and have attempted to find the rationale behind the use of offshore sites by focusing on offshore players’ motivations; however, the motivations seemingly vary by players’ regional online gambling policies. For example, in areas where gambling is prohibited, the “pure” gambling motivations—such as gambling for excitement (Platz & Millar, 2001), a break from their daily routine (Loroz, 2004), socialization with other people (Lee et al., 2006), and financial rewards (Park et al., 2002)—may drive players into offshore gambling. When players have no legal “online” gambling option in their areas, the benefits of online gambling over offline gambling—such as convenience, ease of access, comfort, prohibitive distance from offline casinos, the privacy and the anonymity that online gambling affords, and criminal opportunities like money laundering or youth gambling (Fiedler, 2013; Lee et al., 2014; Wood & Williams, 2007)—may lead players into offshore gambling. Even where there are legal online gambling venues available, players may still be motivated to use offshore sites for better payout rates, game experience, ease of account creation, or untaxed winnings (Gainsbury et al., 2018, 2019; Millar, 2018). Given that the U.S. has complex gambling laws due to the fact that each state has their own gambling laws in addition to federal gambling laws, this micro-level approach may not be effective in understanding offshore players in the U.S., which calls for a macro-level approach—such as routine activities theory (RAT).

RAT is a part of crime opportunity theory where it sees crime as an event and attempts to understand crime on a macro-structural level (Cohen & Felson, 1979). Since RAT presumes that anyone can be motivated to commit crime when finding an attractive target with the absence of capable guardians, it focuses on crime-generating situations and the influence of environmental elements on the crime events, rather than mere offenders. Because of its interests in criminal targets and their capable guardians, RAT has been widely used to explain various crimes, including cybercrime.

Although it is essential to explore offshore gambling-generating situations in the context of the U.S., few studies have focused on environmental factors revolving around offshore gambling. Therefore, this study uses RAT as a theoretical framework to empirically examine offshore gambling from the aspects of the “attractive target” and their “capable guardians”. The aim of this study is to explore (1) how the structural and operational aspects of offshore sites influence U.S. players’ decisions to place bets on these sites; (2) the role of online casino reviews as a capable guardian on U.S. players choosing offshore sites; and 3) the applicability of RAT to offshore gambling behavior by evaluating a theoretical model constructed based on the observed variables. Specifically, the research questions being studied include:

What Factors of Offshore Gambling Sites Affect the Use of the Sites By U.S. Players? This research question examines the extent to which aspects of offshore sites affect the use of offshore sites by U.S. players via multiple linear regression. Variable construction is based on the theoretical elements of RAT and occurs through an examination of a sample of offshore sites. A website analytic tool is also used to retrieve additional information about the sample.

Does the Level of Activity By Online Casino Reviews Have an Effect on Players’ Decision On Choosing Offshore Sites? It examines the extent to which online casino reviews who provide a blacklist of gambling sites affect the use of offshore sites by U.S. players. Examining this research question will allow us to determine if the blacklist can act as capable guardians and therefore prevent players from using offshore sites.

Can Routine Activities Theory Explain Illegal Online Gambling Behavior? Using structural equation modeling, this study constructs a theoretical model with the observed variables of offshore sites to assess the extent to which the theoretical elements of RAT predict offshore gambling by U.S. players.

Literature Review

Routine Activities Theory

RAT focuses on offenders’ perspectives of criminal opportunity as key to understanding crime events and deviant behaviors, which emphasizes the importance of immediate environmental and situational factors and their influence on crime-generating situations or circumstances associated with the space and the timing of crime events. Cohen and Felson (1979) asserted that a crime can occur when 1) a motivated offender, 2) a suitable target, and 3) a lack of capable guardians converge at the same time and place. The conjunction of these components for crime helps people translate their criminal inclinations into actions and facilitates potential victims becoming actual victims. The occurrence of crime events can be fueled (or deterred) by other persons or circumstances in the situation that encourage (or discourage) the events.

Under the assumption that virtual crime scenes are analogous to the terrestrial ones, RAT has been supported as a theoretical explanation for cybercrime patterns (Yar, 2005). Many scholars have applied RAT to cybercrime, a catch-all term that covers a broad range of offenses associated with computers and networks (Casey, 2011), such as virus and malware infection (Bossler & Holt, 2009; Choi, 2008; Holt & Bossler, 2013; Reyns, 2015), phishing (Hutchings & Hayes, 2009; Leukfeldt, 2014), hacking (Leukfeldt & Yar, 2016; Reyns, 2015), identity theft (Reyns, 2013), web defacement (Holt, Leukfeldt, & Van De Weijer, 2020), consumer fraud (Pratt et al., 2010; Van Wilsem, 2011), and bitcoin gambling (Choi et al., 2020). RAT can be applied to offshore online gambling activities in the U.S. as an illegal online gambler (a motivated offender) deliberately targets offshore gambling sites (i.e., an attractive target) based on their attractiveness, especially in the absence of capable guardians. The following will discuss offshore gambling activities with some of the main components of RAT.

Motivated Offender

Although the motivations for crime may vary based on actor and action, RAT in its original form does not explain why individuals are motivated to commit crimes but simply assumes that anyone can be a motivated offender; therefore, offender motivations tend to be treated as a given in much cybercrime research and thus excluded from analyses (Holt & Bossler, 2013; Leukfeldt & Yar, 2016; Maimon et al., 2013; Yar, 2005). In cyberspace, there is a wide range of motivated cyber-offenders, including illegal online gamblers. There will always be an ample supply of motivated offenders who have greater proximity to their targets worldwide because of the borderless nature of online spaces. Given the spatially and temporally-separated nature of the online environment, offenders are not required to be co-present with their targets to commit a crime.

Suitable Target

A suitable target can be any type of individual, object, or place against which the motivated offender can commit a crime (Cohen & Felson, 1979). In cyberspace, there are plenty of targets suitable for predation, such as online users, proprietary data, websites, personal information, online payment, and computer system. Both motivated offenders and suitable targets are viewed as given situational factors for cybercrime.

Target Attractiveness

Felson (1998) argued that the extent of target attractiveness depends on four main elements: the perceived value, inertia, visibility, and accessibility of the crime target. In cyberspace, researchers have reported that the visibility and accessibility play a significant role in predicting the risk of victimization (Newman, Graeme & Clarke, 2003). However, due to significant differences between the virtual and terrestrial organization of criminal events, not all components of RAT are compatible with the online environment such as the inertia (Yar, 2005). Target attractiveness associated with using offshore gambling sites can be viewed from the aspects of a target’s: value, visibility, and accessibility.

Value When discussing illegal online gambling, certain characteristics of a gambling site may affect the target’s value to the offenders and therefore their site selection decision. Research indicates that characteristics preferred by offshore gamblers include reputation, promotion, payout rates, a range of games available, and consumer experience (Gainsbury et al., 2018, 2019), which would be of high value as those aspects are beneficial to the gamblers. In addition, given some disadvantages of using online casinos over the land-based ones (such as unreliability of Internet site or safety concerns; Gainsbury et al., 2018), offshore gamblers may also prioritize sites that are seemingly reliable and safe.

Visibility Target visibility refers to the exposure of targets against which offenders want to commit crimes. A number of cybercrime scholars reported that the online activities of a target contribute to increasing its visibility and, subsequently, the possibility of being targeted (Choi, 2008; Hinduja & Patchin, 2008; Holt & Bossler, 2013; Leukfeldt & Yar, 2016; Marcum et al., 2010; Pratt et al., 2010; Van Wilsem, 2011). As to illegal online gambling, offshore sites advertise themselves to increase their visibility to their target population through numerous channels, such as search engines, social media, forums, affiliate programs, porn sites, blogs, text messages, and emails (Choi et al., 2020; Griffiths, 2017; Kim & Lee, 2019; Yang et al., 2019).

Accessibility Target accessibility refers to offenders’ ability to access and then get away from their target (Felson, 1998). Yar (2005) asserted that the target accessibility in cyberspace is related to the structural aspects of online environments. When it comes to illegal online gambling, it is theoretically possible for online users to access any gambling sites, which are always available online. Many illegal online gambling sites open their door globally, taking bets from players in most countries. Given that potential illegal gamblers must make a deposit to a gambling site before placing a bet and getting rewards with a real money, a range of available deposit/withdrawal methods may also affect the level of target accessibility; the more payment options an online gambling site has, the more ways a player can gamble online for real money.

Lack of Capable Guardians

A capable guardian can be anyone who, by their mere presence, would impede potential offenders from committing a crime (Cohen & Felson, 1979). In other words, the absence of capable guardians would make crime more probable. Yar (2005) argued that, in cyberspace, guardians tend to be divided into formal, informal, and technological guardians.

Formal Guardians

Formal guardians are typically known as the law enforcement agent and the prosecutor (Cohen & Felson, 1979). Most police investigations have been focused on illegal online gambling operators and only rarely on illegal online gamblers. However, investigating illegal online gambling operations can be difficult, as many offshore gambling sites operate outside the purview of the U.S. gambling laws and law enforcement agencies. It is also known that an unsuccessful investigation of illegal online gambling operation could be attributed to insufficient knowledge, skills, and resources toward cybercrime investigation (Masogo & Mofokeng, 2018). These findings imply that considerable resources and efforts need to be invested in improving cybercrime investigations and prosecutions in order for formal guardians to act as effective deterrents to illegal online gambling.

Although lacking arrest powers, security guards can be seen as exercising formal guardians as they restrict potential offenders from committing crime against individuals or properties (Hollis-Peel et al., 2011). In the context of online gambling businesses, operators themselves may act as security guards to protect their sites from unacceptable access or players with inappropriate behaviors, as online gambling sites face a number of threats, including hackings and frauds (Idenfy, 2020). Some operators conduct account verification, which usually requests identifying documents online, to identify a player’s personal information (e.g., age, address, and phone number) and verify the identity connected with the player’s account. Through account verification, operators can prevent scammers from using their sites for criminal activities and cope with unexpected activities caused by the players.

Informal Guardians

RAT emphasizes how significant informal guardians are to deter crime from occurring (Cohen & Felson, 1979), which also has been supported by multiple gambling studies (Shadmanfaat et al., 2020; Sirola et al., 2019). A gambling review site in this context can act as an informal guardian due to one major piece of information it provides—a blacklist of online gambling sites. Dishonest gambling operators might be blacklisted if they victimized gamblers with a number of scams, made possible since they operate the site with little or no oversight (Banks, 2017). Such predatory practices are less likely to backfire than if they were U.S. legal gambling operators, as offshore gamblers are also gambling-law breakers who are afraid to reporting their victimization to the police. Therefore, players who recognize the risk of victimization involved with using offshore sites often rely on information from online casino reviews to avoid malicious gambling sites. Some of the sites share and update a list of online gambling sites that have been blacklisted based on user reports or if the sites do not meet criteria set by each site (e.g., rigged game, payment problem, spamming players, questionable practices, and false advertising; “2021’s guide to blacklisted casinos”, n.d.). This blacklist would warn players to avoid playing at disreputable online gambling sites, thereby serving a vital role in preventing players from potential victimization from illegal online gambling sites.

Technological Guardians

In cyberspace, technological guardians (e.g., automated protection) can constantly guard digital property and data or prevent unauthorized access and loss of the property (Yar, 2005). This concept is analogous to the idea of situational crime prevention, which refers to changing a setting’s environmental design in order to deter certain types of crime by increasing the efforts it takes to commit a crime and the risk of detection for offenders (Clarke, 1995). As to online gambling, there are some safeguards (e.g., website blocking) that are used to discourage unlawful participation in online gambling. Such technologies are used by jurisdictions who attempt to block or blacklist unlicensed gambling sites from being accessed by people within their territories or by online gambling operators who try to block access from out-of-jurisdiction players.

However, such security measures can be circumvented. For example, gamblers could use proxy servers, a virtual private network (VPN), or similar services that mask (or manipulate) the identification of a user's geolocation or provide misleading information about a user’s location (Griffiths, 2019), which could be deemed as fraud and result in criminal prosecution. Some offshore gambling sites that restrict players to sign-up from their ‘real’ physical location can ban VPN access through various methods (e.g., a reverse DNS lookup and packet analysis) in order to prevent a player from accessing from a banned jurisdiction or from taking undue advantage of bonus offers or any illegal activities by creating multiple accounts.

Methods

Sample and Procedure

This study employed a purposive sampling technique to collect a sample of online gambling sites. The data was collected from February 2 to 26 in 2021, using an IP address based in Nevada, USA. Since the focus of this study is on illegal online gambling sites in the U.S., this study targeted online gambling sites that do not have any valid gambling license in the U.S. and are accessible from the U.S. Social casinos, which provide free-to-play gambling themed games (not gambling products) and do not involve real money prizes, were also excluded since the focus of this study is on online gambling sites. As the data collection process occurred in the U.S., any online gambling site that blocks access from the U.S. was excluded from the sample. VPN or its alternatives was not used to bypass the access controls.

This study used the Google search engine to collect the sample of online gambling sites; Google has a massive amount of indexed webpages and effective search algorithms, which are optimized for keyword research (“How search organizes information”, n.d.). Multiple combinations of keywords were employed, such as the combination of the U.S. (US, USA, or American), online, and gambling (casino, sports bet, sportsbook, sports betting, poker, race, or slots).

As a result, a total of 153 offshore gambling sites were identified through the Google keywords search at first; however, 28 of them blocked access from Nevada, U.S. Therefore, this study examined a purposive sample of 125 offshore gambling sites to identify information that were later coded into variables based on the research questions (described in more detail below). Additional variables were coded based on information collected from a Search Engine Optimization (SEO) analytic tool, Ahrefs. SEO tools are used to track, measure, monitor, and analyze website activity to help a website gain visibility in search results (“Search Engine

Optimization (SEO) starter guide”, n.d.). This study used Ahrefs due to its feature that allows its clients to view data of any given website. Examining an online gambling site through a SEO tool produced data that helped assess the visibility aspect of the site, including monthly website traffic from the U.S. and the number of referring domain and organic keywords.

Dependent Variable

Website Traffic

The dependent variable for this study is the website traffic, which is operationalized as monthly website traffic coming from the U.S. Website traffic refers to the volume of visitors1 and does not necessarily include traffic from web crawler bots (“Site explorer”, n.d.). Ahrefs provides the organic search2 traffic of website by countries, which is estimated based on how many monthly visitors a website gets from Google (Hardwick, 2020a). The U.S. website traffic of those online gambling sites unlicensed by the U.S. authorities represents the degree to which the website is targeted and used for illegal activities by the U.S. players.

Independent Variables

Value

Some players value certain aspects of offshore gambling sites. For this study, the value was measured by multiple variables retrieved from a sample of online gambling sites, including the number of games offered, website reliability, bonus, customer support, and entertainment.

Number of Games Offered Some players may be attracted to a site that offers a wide range of game options (Gainsbury et al., 2018). Therefore, this variable measures the number of types of games an online gambling site offers. The type of game includes casino style games, sports betting, poker, and race (i.e., a horse racing game). Each type of game was coded as a binary variable, “yes” (1) or “no” (0), and subsequently the game variable was calculated by summing up the values of the binary numbers to reflect the total number of games offered.

Website Reliability Some players may value a trustworthy, legitimate online gambling site (Gainsbury et al., 2018). Website reliability measures the extent to which an online gambling site is safe and secure. This ratio variable was calculated by adding up the values of multiple binary variables, including the Hypertext Transfer Protocol Secure (Https), offshore license, and responsible gambling, each of which were coded as “yes” (1) or “no” (0).

The Https variable represents whether a site uses Https protocol. Https refers to an Internet protocol for securing communication between the two systems (e.g., the website and the user’s computer). It is a more secure version of Http protocol, using either the Secure Sockets Layer (SSL) or the Transport Layer Security (TLS) protocol that protects the integrity, authentication and confidentiality of data transfer (“Secure your site with HTTPS”, n.d.). Online gambling sites face numerous cyberthreats; players may prefer online gambling sites that can ensure that their funds and personal information are safe and secure. Any site that does not use Https protocol may be less secure from cyberattacks.

The offshore license variable represents whether a site is licensed by any authorities outside of the U.S. Even among online gambling sites unlicensed in the U.S., sites with valid licenses in other jurisdictions may be perceived as more reliable than the ones without a license. Most online gambling sites have to be registered in the jurisdictions where they want to launch their business, which means they are required to follow rules and restrictions set by the local gambling regulators. Being free from any restrictions, online gambling sites with no valid gambling license are much more likely to be rogue and to engage in bad business practices such as the use of flawed game software, payout fraud, and unauthorized use of personal information (Gainsbury, 2012).

Responsible gambling programs are designed to secure a fair and reliable gambling environment and to protect players from having a negative experience as well as problem gambling (Robillard, 2017). Players may want to keep their gambling behavior under control and, as such, are likely to have a positive attitude toward responsible gambling tools and resources (Gainsbury et al., 2013). Therefore, the responsible gambling variable measures whether a site has responsible gambling resources available for its customers.

Bonus Offshore gamblers take into account bonuses and free credits when selecting online gambling sites (Gainsbury et al., 2018). Therefore, the bonus variable represents the degree of promotional offer by an online gambling site and was measured by summing up the values of three binary variables, including the presence of a welcome bonus, “no deposit” bonus, and referral bonus, each of which was coded as “yes” (1) or “no” (0). A welcome bonus (or sign-up bonus) refers to a promotion offered to players creating a new account and making a deposit, which usually comes in the form of free spins or bonus cash. A “no deposit” bonus can be used for new players to win in real money games with no deposit required. A referral bonus is a promotion where a player receives bonus for referring friends to his/her site, which is based on the deposit amount the referred players make.

Customer Support Players may prefer a site with a solid, reliable customer support system in place. The customer support variable measures how many types of customer support services are provided from an online gambling site. The means of customer support include phone, live-chat, email, and message board; each variable was dichotomized as “yes” (1) or “no” (0), and subsequently added to produce the customer support variable.

Entertainment It is essential for online gambling sites to have a lot to offer in the way of entertainment, as players expect entertaining-gaming experiences from the sites (Gainsbury et al., 2018). Some entertainment features of online gambling site include a casino tournament, leaderboard, and live gambling, each of which was coded as “yes” (1) or “no” (0) and then summed up to create the entertainment variable. A casino tournament is a real money competition allowing players who signed up for the gaming event to play the same game at the same time to win big cash prizes, which enhances the social feature of online gambling. (“Online Casino Tournaments”, n.d.). A leaderboard is an aspect of gaming competition that shows the ranking of players, based on their wins during the gaming session (Epifani, 2021). Live gambling enhances the gambling experience and could be in the form of either a live casino or in-play betting. A live casino is a form of online casino game that is played with a human dealer hosting the games in a casino environment and broadcast live to players. In-play betting is a form of betting that can be placed while the event, such as a horserace or sports game, is taking place (“Live Dealer Casinos”, n.d.).

Visibility

The visibility of offshore gambling sites refers to the degree to which the sites are exposed in cyberspace. This study established this component of target with the variables collected from a SEO tool (i.e., Ahrefs), such as referring domains and organic keywords.

Referring Domains A referring domain is a website hosting backlink (Hardwick, 2020b). A backlink refers to a hyperlink from one webpage to another (Hardwick, 2020b; “Site explorer”, n.d.). The higher number of referring domains a website has, the more websites or webpages are referring users to that website. Therefore, this ratio variable could represent the visibility aspect of online gambling site.

Organic Keywords An organic keyword is a search term used to attract organic traffic which is driven from keywords that do not include a pay-per-click keyword (i.e., paid advertisements). For this study, the organic keywords variable represents the number of keywords a website ranks for in the top 100 organic search results in Google; such data is provided by Ahrefs (Soulo, 2020). An organic search result refers to “A free listing in Google Search that appears because it’s relevant to someone’s search terms” (“Organic search result”, n.d., para. 1). In other words, the variable shows how many times a website ranks in the top 100 Google search results from organic keywords. The higher number of organic keywords an online gambling site has, the higher visibility it has in search engines, and therefore the more likely it is exposed to potential users looking for a website for gambling.

Accessibility

This element indicates the extent to which offshore gambling sites are accessible to consumers. For this study, a sample of online gambling sites was limited to the gambling websites that can be accessible from Nevada, U.S. Therefore, this concept was only measured by the two variables; the number of payment options for deposit and withdrawal.

Payment Options Online gambling activity involves making a deposit and withdrawing rewards. Therefore, having various deposit/withdrawal methods would increase a player’s ability to access online gambling sites for illegal gambling activity. Payment options for both deposit and withdrawal include: credit/debit cards, e-wallet, bank wire, check, person to person, and prepaid card. Each deposit (or withdrawal) method was coded as “yes” (1) or “no” (0), and then summed to create the payment options variable for both deposit and withdrawal.

Formal Guardian

Formal guardian is operationalized as an online gambling site.operator, who can act as a security guard by verifying a user’s personal information. Therefore, this dichotomized variable measures whether a site requests users to upload a copy of any documents that can be used for proof of either identity, address, or ownership of payment method (e.g., driver’s license, passport, utility bill, and bank statement) to the website and is coded as “yes” (1) or “no” (0).

Informal Guardian

This study operationalizes informal guardian as a gambling review site. Some gambling review sites provide gambling information, including a list of rogue online gambling sites. The blacklist, therefore, may deter players from placing a bet on illegal online gambling sites.

The data for this ratio variable was collected via Google search, with the name of each gambling site in the sample combined with the keyword “blacklist”. Subsequently, the researcher checked if an online casino review put a gambling site on its blacklist to warn about the risk of using the site. Each attribute of the variable was calculated by counting the number of online casino reviews blacklisting the gambling site within the most relevant results for each search.

Technological Guardian

Technological guardian was measured based on the use of VPN detection systems. The terms of service of each site in the sample was examined to identify whether the site prohibits VPN access. This binary variable was coded as (1) if a site bans VPN access, and (0) if it does not.

Control Variables

For control variables, this study employs multiple variables, including cryptocurrency, years in business, and application. Cryptocurrency measures whether a site uses cryptocurrency as a way of deposit and/or withdrawal. The benefits of using cryptocurrency for payment method may affect player’s decision to choose an online gambling site (Choi et al., 2020). The cryptocurrency deposit and withdrawal variables were dichotomized as “yes” (1) or “no” (0), and subsequently added to produce the cryptocurrency variable. The years in business variable measures how many years a gambling site has been in business since its establishment. Some players may prefer relatively old online gambling sites due to its reliability and safety, others may prefer new online gambling sites due to their lucrative promotions (“The differences”, n.d.). It is expected that whether an online gambling site is relatively new or has been in business for a long time may affect the player’s decision. Application measures whether an online gambling site has an application software, either mobile or desktop version. This binary variable was coded as “yes” (1) or “no” (0). It is likely that an online gambling site with an application software option may attract more players (Choi et al., 2020). Although few scholars have focused on these aspects of offshore gambling sites, it is reasonable to assume that they could affect player’s decision for choosing a site, as each has its own merits. Therefore, these confounding variables need to be adjusted.

Statistical Analysis Methods

The study's examination involves two quantitative analytical models, which aim to identify the factors that impact the use of offshore sites by U.S. players as well as to assess a theoretical application of RAT on offshore gambling. To achieve this, the study utilized SPSS 19 software to conduct multiple linear regression and Mplus 7.4 software to perform confirmatory factor analysis (CFA) and structural equation modeling (SEM).

Multiple Linear Regression

A linear regression model seeks to illustrate the relationships between variables by identifying a straight line that best represents the observed data (Keith, 2014). When there are multiple independent variables that can be either continuous or categorical, a multiple linear regression model is used to estimate their relationships with one dependent variable. The coefficients of the independent variables in the model are associated with a coefficient of the dependent variable, indicating the contribution of each independent variable in predicting the dependent variable (Keith, 2014). To apply a linear regression model, it is important to assume that there is no autocorrelation between the residuals. Including control variables in the regression analysis allows us to control the relationships for alternative explanations and to estimate the expected degree of the use of U.S. illegal online gambling sites at a certain degree of the observed factors of the sites, as well as how strong the causal relationship is.

Confirmatory Factor Analysis

Factor analysis helps researchers identify if multiple observed variables reflect broader underlying latent variables (i.e., factors) and measure abstract concepts by reducing the number of variables into a few interpretable underlying factors (Brown, 2015). The factors are inferred by examining the covariances among multiple observed variables. Factor analysis is an appropriate method for constructing a theoretical model, especially when theoretical elements are abstract concepts, such as RAT.

Confirmatory factor analysis (CFA) is a type of factor analysis that differs from exploratory factor analysis; it is used to test the theoretical relationships between observed variables and unobserved variables in a hypothesized model driven by a theory (Schreiber et al., 2006)—which helps researchers determine whether the observed variables provide empirical support for the theoretical model. This study employed this technique to create latent variables that represent the elements of target suitability; Value (with Number of games offered, Website reliability, Bonus, Customer support, and Entertainment), Visibility (with Referring domains and Organic keywords), and Accessibility (with Payment options).

Structural Equation Modeling

Structural equation modeling (SEM) is a multivariate statistical modeling technique used to tests model fit and estimates coefficients based on hypothesized relationships between observed variables and latent variables, or among latent variables themselves. Given that SEM is described as a combination of the measurement model (confirmatory factor analysis) and the structure model (path analysis), it is often viewed as an extension of multiple regression that enables researchers to evaluate more complex causal models (Bollen & Noble, 2011). The measurement model evaluates the relationships between observed variables and their corresponding latent variables, while the structural model tests the hypothesized relationships between latent variables. To assess how well a hypothesized model fits the data, researchers use various indices of fit, such as absolute and relative fit indices. Absolute fit indices evaluate how closely the hypothesized model aligns with observed data, while relative fit indices compare the performance of the hypothesized model against a baseline model, which assumes no correlations between observed variables (McDonald & Ho, 2002).

Unlike multiple regression, SEM accounts for remaining error variance and allows for correlations among exogenous variables, whether they are observed or latent variables (Bollen & Noble, 2011). Given that this study aims to test a theoretical model of illegal online gambling behavior grounded in the RAT framework, SEM is an appropriate method as the model includes hypothesized causal relationships between a measured endogenous variable (i.e., Website traffic) and observed exogenous variables (i.e., Number of games offered, Website reliability, Bonus, Customer support, Entertainment, Referring domains, Organic keywords, Payment options, Formal guardian, Informal guardian, Technological guardian, Cryptocurrency, Years in business, and Application), as well as latent variables (i.e., Value, Visibility, Accessibility). Using this technique allows us to evaluate the applicability of RAT by examining the degree to which RAT elements predict U.S. players’ decision to select offshore sites.

The Current Study

Drawing from prior studies in the area of illegal online gambling and RAT, this study examined the following hypotheses:

1. Hypothesis 1 All factors of offshore sites under the target attractiveness will positively affect the U.S. website traffic of offshore sites.

2. Hypothesis 2 All factors of offshore sites under the capable guardians will negatively affect the U.S. website traffic of offshore sites.

3. Hypothesis 3 The blacklist provided by gambling review sites will negatively affect the U.S. website traffic of offshore sites.

4. Hypothesis 4 All theoretical elements of the target attractiveness will be positive predictors of the use of offshore sites.

5. Hypothesis 5 All theoretical elements of the capable guardians will be negative predictors of the use of offshore sites.

Results

Descriptive Statistics

Table 1 displays the descriptive statistics and the measurements in the current study. Regarding the dependent variable (n = 120), Ahrefs provided a monthly website traffic from the U.S. for 120 out of 125 offshore gambling sites. The mean monthly website traffic was 11,523.6 (SD = 39,602.491). For the independent-ratio variables, the average was 1.248 for Number of games offered (SD = 0.68), 2.496 for Website reliability (SD = 0.533), 2.008 for Bonus. (SD = 0.654), 2.472 for Customer support (SD = 0.747), 0.872 for Entertainment (SD = 0.907), 697.46 for Referring domains (SD = 1101.568), 3,686.76 for Organic Keywords (SD = 25,517.349), 2.632 for Payment options for deposit (SD = 0.799), 2.712 for Payment options for withdrawal (SD = 0.94), and 7.600 for Informal guardian (SD = 11.872).

Table 1.

Descriptive Statistics of Variables

	N	Mean (SD)	Frequency (%)	Min	Max	Skewness
Dependent variable
Website Traffic	120	3.123 (1.038)		0.6	5.56	− 0.263
Independent variables
Number of games offered	125	1.248 (0.680)		1	4	2.777
Website reliability	125	2.496 (0.533)		1	3	− 0.308
Bonus	125	2.008 (0.654)		1	3	− 0.008
Customer support	125	2.472 (0.747)		1	4	− 0.198
Entertainment	125	0.872 (0.907)		0	3	0.719
Referring domains	125	4.101 (1.167)		5.56	7.13	− 0.055
Organic keywords	125	2.228 (0.872)		0	5.44	0.631
Payment Options_deposit	125	2.632 (0.799)		1	5	0.282
Payment Options_withdrawal	125	2.712 (0.940)		1	5	− 0.161
Formal guardian	125		95 (76.0)	0	1	− 1.232
Informal guardian	125	7.600 (11.872)		0	57	2.000
Technological guardian	125		29 (23.2)	0	1	1.285
Control variables
Cryptocurrency	125	1.672 (0.579)		0	2	− 1.593
Years in business	125	11.120 (7.910)		0	36	0.469
Application	125		72 (57.6	0	1	− 0.311

For the independent-binary variables, Formal guardian was identified in 76% of the sample sites (n = 95) and Technological guardian in 23.2% of the sites (n = 29). For the control variables, the mean of Cryptocurrency was 1.672 (SD = 0.579), and that of Years in business was 11.120 (SD = 7.910). More than half of the sites offer application(s) for either desktop or mobile (n = 72, 57.6%).

Given that acceptable values of skewness tend to range from − 3 to + 3 (Brown, 2015), the original data was highly, positively skewed in terms of three variables—Website traffic (7.271), Referring domains (3.893), and Organic keywords (10.272), which violates the assumption of normality in linear regression analysis. These non-normal distributions may indicate that a small number of major offshore gambling sites take a large portion of U.S. players and are exposed on the Internet to a relatively high level, compared to the other sites. To adjust the highly right skewed distributions, this study conducted log transformation (base 10) for the skewed variables to achieve linearity. As a result, the skewness value became − 0.263 for Website traffic (X̄ = 3.123, SD = 1.038), − 0.0.055 for Referring domains (X̄ = 4.101, SD = 1.167), and 0.631 for Organic keywords (X̄ = 2.228, SD = 0.872).

Multiple Linear Regression Model

This study first examined the multiple linear regression model of illegal online gambling in which all the independent variables were tested at once. Table 2 shows the fit of the multiple linear regression model, which indicates that the model fits the data well (R² = 0.676, Adjusted R² = 0.692). Findings on the effects of the features of illegal online gambling site on the use of the sites by U.S. players are shown in Table 3 and graphically displayed in Fig. 1. Entertainment showed statistically significant relationship with Website traffic, indicating that the website traffic increases by 0.185 for every one unit increase in the entertainment. This suggests that U.S. players value the entertaining aspect of offshore sites, such as casino tournaments, a gaming competition, live casino, and in-play betting. In addition, the visibility variables—Referring domains and Organic keywords—were a significant indicator of Website traffic, indicating that the website traffic increases by 0.597 (or 0.576) for every one unit increase in the referring domains (or the organic keywords). This suggests that offshore gambling sites with many webpages referring to them and high visibility in search engines tended to have higher likelihood of being targeted by U.S. players. Contrary to our expectation, the other features of offshore gambling sites did not significantly influence the use of the sites.

Table 2.

Regression Statistics of the Multiple Liner Regression Model

	Regression statistics
Multiple R	0.822
R square	0.676
Adjusted R square	0.629
Standard error	0.632

Table 3.

Multiple Linear Regression Analysis for Factors Predicting Website Traffics

	b	S.E	β	t	p value
Constant	0.209	0.587	–	0.355	0.723
Value
Number of games offered	− 0.066	0.116	− 0.044	− 0.568	0.571
Website reliability	− 0.066	0.116	− 0.034	− 0.563	0.575
Bonus	− 0.081	0.112	− 0.049	− 0.718	0.475
Customer support	0.016	0.091	0.011	0.172	0.864
Entertainment	0.185*	0.083	0.163	2.223	0.028
Visibility
Referring domains	0.597**	0.172	0.275	3.481	0.001
Organic keywords	0.576**	0.103	0.456	5.575	0.000
Accessibility
Payment options_deposit	0.096	0.086	− 0.008	− 0.103	0.918
Payment options_withdrawal	− 0.009	0.150	− 0.057	− 0.921	0.359
Formal guardian	− 0.138	0.150	− 0.057	− 0.921	0.359
Informal guardian	0.006	0.006	0.071	1.089	0.278
Technological guardian	− 0.221	0.150	− 0.088	− 1.478	0.142
Control variables
Cryptocurrency	− 0.124	0.117	− 0.070	− 1.062	0.291
Years in business	0.019	0.010	0.144	1.971	0.051
Application	0.196	0.129	0.093	1.521	0.131

*p < 0.05, **p < 0.01

Fig. 1.

Diagram of Multiple Linear Regression Analysis for Factors Predicting Website Traffic

Structural Model

To examine if the theoretical elements of RAT can explain illegal online gambling behavior, this study performed a SEM analysis based on data from 125 offshore gambling sites. This study constructed a theoretically-driven SEM model with the strictly confirmatory approach, which allows only one model based on the given theory for theory-testing (Muller & Hancock, 2001). Confounding variables used in the regression model were excluded from the model, as the main premise of RAT is limited to the “three minimal elements” (Cohen & Felson, 1979, p. 589). First, latent variables were created for the elements of the target attractiveness (i.e., Value, Visibility, and Accessibility) by conducting CFA. The results of factor loading are shown in Table 4. As to the overall reliability, the Cronbach’s alpha value is considered as adequate for the Value variables (0.647), high and good for the Visibility variables (0.745), and reasonable for the Accessibility variables (0.673; Taber, 2018).

Table 4.

CFA Factor Loading for Latent Variables

	Unstandardized	Standardized (STDYX)
Value (alpha = 0.647)
Number of games offered	1.000	0.623
Website reliability	0.244	0.194
Bonus	0.449	0.291
Customer support	0.802	0.454
Entertainment	1.449	0.677
Visibility (alpha = 0.745)
Referring domains	1.000	0.789
Organic keywords	1.889	0.866
Accessibility (alpha = 0.673)
Payment options_deposit	1.000	0.590
Payment options_withdrawal	1.480	0.742

*p < 0.05, **p < 0.01

Following the CFA, the structural model was evaluated for the overall model fit to test how well the model fits the given data, including three indices of absolute model-fit (i.e., chisquare, root mean square error of approximation [RMSEA], and standardized root mean square residual [SRMR]) and two indices of relative model-fit (i.e., comparative fit index [CFI] and Tucker-Lewis index [TLI]; see Table 5). Two of three indices of absolute model-fit are within acceptable range (RMSEA = 0.079, SRMR = 0.073). Although the result of the chi-square test was significant (p < 0.01), the researcher evaluated model fit based on the other indices of model-fit because a chi-square test is deemed to be a less useful metric for model fit in comparison with other descriptive fit statistics due to the its sensitivity to sample size (Shi, Lee,& Maydeu-Olivares, 2019). Regarding the relative model-fit, the value of CFI (0.873) and TLI (0.853) falls within a range of mediocre fit. Although the indices of model-fit indicate that the measurement model does not fall in the category of a great fit between the model and the observed data, this study proceeded with analysis, because the theory-driven approach prioritizes a theoretically grounded model over model-fit statistics in social science (Tarka, 2018).

Table 5.

Model-fit Test of the Theoretical Model

AIC	BIC	χ2	df	CFI	TLI	RMSEA	SRMR
2554.014	2661.490	101.146**	57	0.873	0.853	0.079	0.073

The findings of the structural model are described in Table 6 and graphically shown in the Fig. 2. Table 6 shows both unstandardized and standardized model results. Among the measures of the target attractiveness, Visibility was predictive of higher use of offshore gambling sites by U.S. players (b = 2.267, p < 0.01). The standardized coefficient of Visibility (β = 0.843, p < 0.01) indicates that it has the strongest relationship with Website traffic among the exogenous variables. The standardized coefficient of Organic keyword indicates that the number of organic keywords associated with an offshore gambling site in Google provided the most substantial contribution to its website traffic among Visibility categories.

Table 6.

Unstandardized and Standardized Coefficients for SEM

Variable	Unstandardized			Standardized (STDYX)
	Estimate	S.E	p value	Estimate	S.E	p value
Website traffic on
Value	0.115	0.286	0.688	0.045	0.112	0.687
Visibility	2.267**	0.286	0.000	0.843**	0.070	0.000
Accessibility	0.019	0.243	0.937	0.008	0.107	0.937
Formal guardian	− 0.181	0.140	0.196	− 0.072	0.056	0.197
Informal guardian	− 0.012*	0.005	0.015	− 0.132*	0.055	0.016
Technological guardian	− 0.266	0.144	0.064	− 0.105	0.057	0.064

*p < 0.05, **p < 0.01

Fig. 2.

Diagram for SEM Estimations. *Unstandardized coefficient (Standardized coefficient); *p < 0.05, **p < 0.01

In addition, the findings indicate that there were positive correlations among the target attractiveness factors. Statistically significant unstandardized correlations were observed between Visibility and Value (0.087**) and between Visibility and Accessibility (0.072**). The results indicate that both Value and Accessibility indirectly affected the use of offshore gambling sites through the correlations with Visibility. These findings support the theoretical assumption of target suitability in that an increase in attractiveness of the crime target increases the possibility of the site being targeted by U.S. players.

Among the capable guardian elements, Informal guardian was predictive of lower use of offshore gambling sites by U.S. players (b =  − 0.012, p < 0.05), indicating the importance of the guardian role of online casino reviews providing a blacklist of gambling sites. The finding partially supports another theoretical element of RAT, capable guardians, by emphasizing the importance of an informal guardian (online casino reviews) in preventing the use of rogue online gambling sites.

Discussion and Conclusion

This study was designed to examine predictors of using offshore online gambling sites accessible from the U.S. from the perspective of RAT. It began with three main goals: (a) to determine what characteristics of offshore sites influence U.S. players as they choose offshore sites, (b) to ascertain if online casino reviews acting as a capable guardian affect the use of offshore sites by U.S. players, and (c) to examine whether the theoretical elements of RAT predict offshore gambling. This study found that a site’s entertainment, referring domains, and organic keywords were positive predictors of the use of offshore sites, while the other factors of offshore sites were not significant. Players seem to value entertaining-gaming experiences while doing online gambling; specifically, gaming competition and live casino play with other players enhance the social feature of gambling, which allows players to have a sense of human connection with others. Socialization with other people—which can drive an individual to gambling behavior (Lee et al., 2006)—is something they usually experience in a brick-and-mortal casino, not allowed them to do so from their home. This finding in line with the previous report in that players seek entertaining-gaming experiences from online gambling sites (Gainsbury et al., 2018).

In addition, the findings suggest that online visibility of offshore site affects the number of website visitors. A strong online visibility indicates that a potential customer is more likely to run into a reference (e.g., online casino review, Google) to offshore sites, which gives the gambling sites more opportunities to place their business in front of their target audience, both when customers are and are not searching for online gambling. The importance of online visibility has been highlighted in other online business (e.g., online shopping, tourism business; Drèze & Zufryden, 2004; Smithson et al., 2011). High visibility increases a website’s brand awareness and reputation, which are deemed as a precursor of purchase (here, monetary deposit). Therefore, the online visibility of offshore sites may be a key indicator of their business success (Drèze & Zufryden, 2004).

This study also constructed and tested a theoretical model of illegal online gambling based on Cohen and Felson’s (1979) RAT. Among the theoretical elements of RAT, this study focused on target attractiveness (i.e., the target’s visibility, value, and accessibility) and capable guardians (i.e., consisting of formal, informal, and technological guardians). The results of the SEM analysis supported the theoretical assumption of visibility in terms of illegal online gambling, while the value and accessibility showed almost no effects on illegal online gambling. This may be because the value and accessibility aspects of an online gambling site are not easily identified unless players sign into the site. This finding is in line with other cybercrime research in that the visibility tends to be a sole predictor within cybercrime victimization among the suitable target elements (Choi, 2008; Bossler & Holt, 2009; Holt & Bossler, 2009; Hutchings & Hayes, 2009; Leukfeldt, 2014; Leukfeldt & Yar, 2016; Pratt et al., 2010; Van Wilsem, 2011).

However, the positive correlations of the three elements of the target attractiveness may indicate that an online gambling site that has more webpages referring to the site or that is searched by more users in Google is also more likely to be highly valued as well as to have more ways to access real-money online gambling games. Therefore, all these elements contribute to the level of the target attractiveness of offshore site, which supports the theoretical assumption of the target attractiveness (Felson, 1998).

In terms of the capable guardians, the formal and technical guardians have no effects within illegal online gambling, which may be because most sites require account verification and are not strict in enforcing the use of VPN to access. A blacklist of gambling sites, managed by online casino reviews, functions as an informal guardian. It helps players avoid online gambling sites who possibly provide unpleasant experience to or even victimize their customers (Bank, 2017). Therefore, this model also partly supports the assumption of the capable guardians (Cohen & Felson, 1979).

Policy implication

Online visibility drives offshore gambling; offshore gambling sites put substantial efforts to place their business in front of their potential customers. Therefore, making an effort to decrease the online visibility of offshore gambling sites would be likely to prevent the sites from being targeted by U.S. players. In this context, the Australian Communications and Media Authority (ACMA) employed such an approach to block certain offshore gambling sites that have been illegally accepting Australian players (“Australia: ACMA orders blocking...”, 2021). The Australian regulators have made Australian Internet Service Providers (ISPs) block offshore gambling sites in breach of its Interactive Gambling Act 2001. Such efforts also need to be made by U.S. federal government agencies to deter offshore gambling sites that have been operating in the U.S. illegally.

Blocking access to offshore sites is not a necessarily panacea for illegal online gambling. It can be a whack-a-mole game—when ISPs block an offshore site based on its name or domain name, the site gets back to business again by changing its name or domain name. Therefore, additional efforts are necessary to effectively restrict offshore sites. Such efforts can include prosecuting offshore sites (something that the U.S. has done for years; see Sayre & Tau, 2020) or creating a favorable online gambling business climate for offshore online gambling sites to become legal U.S. operators (Sayre & Tau, 2020). While having offshore sites as legal U.S. operators may cause regulatory concerns, it would encourage market competition that could lead to better online gambling products and services for players (Sayre & Tau, 2020). Improved products and services provided by domestic, legal operators would reduce the demand for offshore sites and therefore bring many offshore players into the legal market. Such efforts to enhance a domestic industry to reduce the demand for products and services in other jurisdictions have been observed in various fields—such as medical tourism (see Béland & Zarzeczny, 2018).

Limitations and Future Research

As this study employed a purposive sampling technique, the sample may not correctly represent the true population, which may present a generalizability concern. Also, the sample size may not be large enough for accurate SEM analysis (Faber & Fonseca, 2014). Therefore, future studies should be conducted with sufficient collected sample to produce more precise estimations as well as reliable results, which may need a support of market research companies for data collection.

This study constructed the Value variables by adding up multiple binary variables, however there might be other ways to build each of the Value variables. Also, the Visibility variable can be measured by other elements, such as the number of reviews a site has that can indicate the degree to which the site is exposed to players using online gambling reviews. Thus, this study cannot be definitive as to claiming the measurements were accurately constructed with 100% confidence. In addition, the model-fit of the theoretical model indicated that the model was not in a great fit, which might be caused by the measurement error or the structure of the model (Barrett, 2007). Therefore, future studies may need to test various theoretical models with a wide range of variables, which may require comprehensive understanding and thorough examination of offshore gambling business. Expert panels can be an effective approach toward identifying characteristics of offshore sites.

This study deemed an offshore gambling site in the U.S. as the ‘target,’ not the ‘victim,’ focusing on the attractiveness of target itself. Given that the site also makes an effort to be targeted by potential offenders, some scholars might not completely agree with the applicability of RAT to illegal online gambling activities. Future studies may provide more empirical evidence on the applicability of RAT on illegal online gambling.

Data Availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Conflicts of interests

I confirm that this work is original and has not been published elsewhere, nor is it currently under consideration for publication elsewhere. I have no conflicts of interests to disclose, and there has been no financial support for this work.