The ‘In’ Crowd: Is there a relationship between ‘in-play’ betting and problem gambling?

For those of us who watch football on the television in the UK, it is almost impossible to watch a game without seeing the many gambling adverts alerting us to the fact we can now bet on over 60 ‘in-play’ markets while watching the game. Should I wish to, I can bet on everything from who is going to score the first goal, what the score will be after 30 minutes of play, how many yellow cards will be given during them game and/or in what minute of the second half the first free kick will be awarded.

‘In-play’ betting is arguably the fastest growing form of gambling in the UK and the UK’s leading ‘in-play’ bookmaker Bet 365 made over £500 million last year. One of the issues I have been asked by the press is to what extent ‘in-play’ betting can be problematic. One of the interviews I did recently was with the Mail on Sunday who published some of my comments yesterday in an article entitled ‘Risky business: With the advent of online gambling, are we creating an epidemic of addiction? ’I was quoted as saying:

‘What the in-play markets have done is take what was traditionally a discontinuous form of gambling – where you make one bet every Saturday on the result of the game – to one where you can gamble again and again and again. You cannot become addicted to something unless you are constantly being rewarded. If the reward only happens once or twice a week, it’s impossible to become addicted. In-play has changed that”

This indeed was a good summary of the interview I did. In-play betting is something that many of us in the problem gambling field are keeping an eye on because it’s taken something that has traditionally been a non-problem form of gambling to something that is more akin to betting on horse racing. At a typical Gamblers Anonymous group, you will get horse racing addicts, slot machine addicts, casino addicts, but it was rare that you got anyone ever having problems with things like football betting, mainly because football betting opportunities were once a week on the pools or betting before the match on a Saturday afternoon.

As I noted in my published quote above, if the reward for gambling only happens once or twice a week, it is completely impossible to become addicted. In-play has changed that because we now have football matches on almost every day of the week making a daily 2-hour plus period of betting seven days a week. As a psychologist who has researched problem gambling for over 25 years, I would assess the structural characteristics of this type of activity and associate it with the type that causes problem gambling for those that are vulnerable and susceptible. So why do I think this?

When considering speed and frequency of gambling in relation to problem gambling, concepts such as event duration, event frequency and payout interval can often be misunderstood and applied in the wrong context. Often, these are mistaken for having the same meaning. Furthermore, concepts such bet frequency and event duration are often ignored despite their importance of their role in the speed and frequency of betting. All of these terms refer to slightly different aspects of gambling although they are all implicated factors that affect speed and frequency.

Event duration essentially refers to how fast the “event” is (i.e., the speed of a gambling activity such as a reel spin on a slot machine that typically lasts for a few seconds). Professor Alex Blaszczynski and his colleagues at the University of Sydney (Australia) noted that gamblers prefer faster speeds and find fast speeds while playing more enjoyable. Therefore, they argued that gamblers’ motivation to play could encourage more persistent gambling activity. Another study by Professor Ladouceur and Dr. Serge Sevigny at the University of Laval (Quebec, Canada) investigated the effects of slot machine game speed on concentration, motivation to play, loss of control, and number of games played on people randomly assigned to either a high-speed (5 seconds) or a low-speed (15 seconds) gambling condition. Their results showed that high-speed gamblers played more games and underestimated the number of games played more than low-speed gamblers. However, speed didn’t influence concentration, motivation, or loss of control over time or money. Despite many methodological limitations they concluded that speed had limited impact on occasional slot machine gamblers.

A paper by Dr Kevin Harrigan and Dr. Mike Dixon (University of Waterloo, Canada) estimated the speed of slot machine play on slot machines. On a machine with a reel spin of every six seconds, players can play 10 times per minute, (i.e., 600 spins per hour) whereas those on a machine with a reel spin of every three seconds, players can play 20 times a minute (i.e., 1200 spins per hour). I also found similar results in research I carried out on British slot machines in the late 1980s and early 1990s.

It is important to acknowledge that duration of the betting event is different from event frequency. However, they may be inextricably linked in so much as the length of a betting event will obviously limit the frequency with they can take place. For example, a betting event lasting two hours (e.g., wagering only on the final outcome of a football game) could not have an event frequency greater than one in any 2-hour period, but a roulette spin (lasting approximately 5-6 seconds) may have an event frequency of several hundred in the same two-hour period. Furthermore, as a result of the introduction of in-running or situational betting (i.e., ‘in-play betting’) this relationship is even less clear.

Event frequency refers to the number of events that are available for betting in any given time period. For example, a lottery draw may occur twice a week but an electronic keno lottery draw may occur 100 times per hour. In this example, a keno lottery draw has a higher event frequency. Bet frequency, on the other hand, refers to the number of bets or wagers placed in any given time period. Using the lottery again as an example, multiple tickets (e.g., 10 tickets) can usually be purchased as frequently as desired before any single lottery draw. So here bet frequency would be equal to 10 but event frequency would be equal to 1. Therefore, bet frequency can often be higher than event frequency and hence, it is possible to spend more than one can afford even with a low event frequency.

The relationship between bet frequency and event frequency needs further empirical investigation. As researchers and clinicians, we often make the assumption the two have a strong relationship; the higher number of betting events – the higher the frequency of betting. Until more research is forthcoming a definitive answer is currently not available. Although, players can place many bets on just one gambling event, the outcome of this event can influence future betting activity. By outcomes, we are essentially referring to winning or losing. Losing can often create financial and emotional motivation to continue betting (i.e. chasing). It could be speculated that the satisfaction from winning may reduce motivation for further betting in the short-term, or it may increase betting as a result of increased bankroll, illusions of control and/or cognitive biases. Therefore, a higher event frequency not only offers more opportunity and choice for betting, but also affects motivation for betting through revealing consequential wins and losses at the end of each event. However, it should also be noted that betting frequency is also impacted by other factors (e.g., peer pressure, time constraints to gamble, etc.).

So does the speed of a game influence the prevalence of problem and pathological gambling? Based on the relationship between event duration, event frequency, bet frequency, and payout interval, empirical research has consistently shown that games that offer a fast, arousing span of play, frequent wins, and the opportunity for rapid replay are those most frequently cited as being associated with problem gambling. The actual prevalence rate of problem and pathological gambling will of course depend on many other factors than speed of the game alone, but games with high and rapid event frequencies such as slot machines are most likely to impact on increased rates of problem and pathological gambling. In-play betting appears to be an activity that is starting to blur the lines between continuous and discontinuous forms of gambling.

Frequency of opportunities to gamble (i.e., event frequency) also appears to be a major contributory factor in the development of gambling problems. The general rule is that the higher the event frequency, the more likely it is that the activity will result in gambling problems. Addictive behaviours have been shown to be associated with the rewards and the speed of rewards and payout rates. Therefore, the more potential rewards there are, and the higher the amount of the rewards, the more problematic the activity is likely to be. Given the time, money and resources, a vast majority of gambling activities are “continuous” in that people have the potential to gamble again and again. Therefore, in relation to problem gambling, in-play betting is an activity that we really need to keep an eye on.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Additional input by Dr. Jonathan Parke (Salford University, UK)

Further reading

Blaszczynski, A, Sharpe, L., & Walker, M. (2001). The Assessment of the Impact of the Reconfiguration on Electronic Gaming Machines as Harm Minimization Strategies for Problem Gambling. Report for the Gaming Industry Operators Group, University of Sydney Gambling Research Group, Sydney

Griffiths, M.D. (1993). Fruit machine gambling: The importance of structural characteristics. Journal of Gambling Studies, 9, 101-120.

Griffiths, M.D. (1994). The role of cognitive bias and skill in fruit machine gambling. British Journal of Psychology, 85, 351-369.

Griffiths, M.D. (1999a). Gambling technologies: Prospects for problem gambling. Journal of Gambling Studies, 15, 265-283.

Griffiths, M.D. (2008). Impact of high stake, high prize gaming machines on problem gaming. Birmingham: Gambling Commission.

Harrigan, K. & Dixon, M. (2009). PAR Sheets, probabilities, and slot machine play: Implications for problem and non-problem gambling. Journal of Gambling Issues, 23, 81-110.

Ladouceur. R., & Sévigny, S. (2005a). The impact of video lottery game speed on gamblers. Journal of Gambling Issues, 17.

Loba, P., Stewart, S. H., Klein, R. M. & Blackburn, J. R. (2002). Manipulations of the features of standard Video Lottery Terminal (VLT) games: Effects in pathological and non-pathological gamblers. Journal of Gambling Studies, 17, 297-320.

Parke, J. & Griffiths, M.D. (2006). The psychology of the fruit machine: The role of structural characteristics (revisited). International Journal of Mental Health and Addiction, 4, 151-179.

Parke, J. & Griffiths, M.D. (2007). The role of structural characteristics in gambling.  In G. Smith, D. Hodgins & R. Williams (Eds.), Research and Measurement Issues in Gambling Studies (pp.211-243). New York: Elsevier.

Trust is a must: The role of trust, personalization and context in online gambling

Until recently there appeared to be a commonly held perception that consumers viewed the Internet as an information gathering tool rather than a place to spend money. The explosive growth in online gambling shows this is no longer true. Historically, the two things that have had the power to drive any new consumer technology were pornography and gambling. These activities have helped satellite and cable television, video, and then the Internet. For me, the interesting question is how online gaming companies use as many ways as possible to get punters to log onto their website and how they are going to target new punters in the future.

Let’s look at it from an individual level. A gambler has logged on to the Internet and they are in the process of deciding which online gambling site to make a beeline for. What kinds of things influence their decision? A recommendation from one of their friends? Advice from a gambling magazine or player forum? An advert they saw online? From a psychological perspective, research on how and why people access particular commercial websites indicates that one of the most important factors is trust. If people know and trust the name, they are more likely to use that service. Reliability is also a related key factor. Research shows that some punters still have concerns about Internet security and may not be happy about putting their personal details online. But if there is a reliable offline branch like nearby (e.g., a Gala casino), it gives them an added sense of security and what I would call a “psychological safety net”. For some people, trust and security issues will continue to be important inhibitors of online gambling. Punters need assurance and compelling value propositions from trusted gaming operators to overcome these concerns.

One of the growth areas in e-commerce has been personalization and most online ventures now have a personalization strategy as part of its business plan. However, this practice is a double-edged sword that can prove to be a large logistical problem for some companies. Tracking every move for marketing purposes is one thing. Using these data for personalization purposes can prove troublesome. The amount of data is potentially enormous. Producing personalized pages for everyone is also logistically difficult and may even turn punters away. The key is knowing what to ask the punter. Online operators have to think intelligently and creatively about what to ask people who visit their sites in a way that the information gained can be used effectively. Attracting and providing customers with useful information relies on the gaming companies putting punters first.

Integration can also be a factor here. Online gambling companies are going to have to think of creative ways to make the gaming experience more personal and match it more closely to the real gaming experience something that has worked well for online poker sites. Companies may also need special pricing for online customers. Price is just one of the many considerations a gambler weighs up. It is more about a complete service than price alone (although in the gambling world, offering competitive odds and bonuses will obviously make websites attractive to gamblers).

One of the most important marketing strategies that online companies engage in is “imprinting” new customers. Online punters quickly adopt predictable Internet usage patterns and evidence suggests that they don’t switch online allegiances easily. Smart online gambling operators will work at becoming a starting point for the novice gambler and capitalize on this opportunity for capturing player loyalty. The emerging post-teenage market is a key consideration. There is a whole Internet generation coming through who have a positive outlook on online commercial activities. They may be happier to enter credit card details online and/or meet others online. This has the potential to lead to major changes in clientele as the profiles of these people will be radically different from previous punters. The problem is that the young don’t tend to have much disposable income and are less likely to own credit cards. Therefore, another market segment that those in the online gambling business will start to target are the over-50s who are starting to use the Internet for shopping and entertainment use. Early retirees have both time and money, which is why online companies will target the ‘grey’ pound, euro or dollar.

So what’s coming next? Contextual commerce may be one avenue that the online gaming affiliate industry uses more and more. In most retail outlets, shoppers notice what other people are buying and this may influence the purchaser’s choice. Companies are now working on software that allows customers to do this online including interacting with other shoppers. Seeing what everyone else is buying (or betting on) may again influence the decision process. There is also the potential to bring in techniques used on home television shopping channels. Presenters tell viewers how much of a product has been sold with viewers to instil a sense of urgency into the buying process, along with an element of peer review. This could be applied in some online gambling situations if people are gambling as part of a community such as online poker tournaments. I think it’s a case of ‘watch this space!’

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D. (2003). Internet gambling: Issues, concerns and recommendations. CyberPsychology and Behavior, 6, 557-568.

Griffiths, M.D. (2007). Brand psychology: Social acceptability and familiarity that breeds trust and loyalty. Casino and Gaming International, 3(3), 69-72.

Griffiths, M.D. (2008). Online trust and Internet gambling. World Online Gambling Law Report, 8(4), 14-16.

Wood, R.T.A.  & Griffiths. M.D. (2008). Why Swedish people play online poker and factors that can increase or decrease trust in poker websites: A qualitative investigation. Journal of Gambling Issues, 21, 80-97.

Zangeneh, M., Griffiths, M.D. & Parke, J. (2008). The marketing of gambling. In Zangeneh, M., Blaszczynski, A., and Turner, N. (Eds.), In The Pursuit Of Winning.  pp. 135-153. New York: Springer.

Net loss? A brief overview of online gambling

Last month, Daria Kuss and I published a systematic review of the world wide online gambling literature (2001-2011). The aim of our literature review was to highlight the research that had examined (i) Internet gambling behaviour and (ii) Internet gambling addiction. A total of 39 studies met our inclusion criteria (i.e., the study included primary empirical data, was published in a peer reviewed journal after 2000, and specifically addressed gambling on the Internet). Based on previous research we argued that a combination of individual, situational and structural characteristics would determine whether and to what extent individuals engaged in Internet gambling. Our review attempted to review which characteristics were most important based on the empirical evidence to date.

Individual characteristics include things such as socio-demographic variables, attitudes and motivations. In terms of socio-demographics related to internet gambling, being male, of young age, single (i.e., not in a stabe relationship), and being of higher education were associated with gambling on the Internet. With regards to attitudes, opinions in the published research studies diverged; some viewed Internet gambling as more dangerous than land-based gambling, whereas for others, it was preferable due to anonymity. The motivations reported, for the most part, related to enjoyment and social activities.

Situational characteristics consist of the physical and social environments Internet gamblers are in when they gamble. The studies we reviewed indicated that situational characteristics (i) have an impact on the ways in which people gamble including the stakes they set and (ii) are likewise impacted by the ways in which people gamble on the Internet. However, it must be noted that research into the situational characteristics associated with pathological gambling on the Internet is still relatively scarce compared to studies assessing the structural characteristics. Therefore, in order to present a comprehensive picture of Internet gambling addiction, future research may be informed by particularly addressing the physical and social environments in which gambling on the Internet occurs.

Structural characteristics comprise both the technology of the Internet itself and the gambling types and behaviors that can be performed within it. The former also incorporates the factors that differentiate online gambling from land-based gambling, such as anonymity, convenience and access, levels of trust, gambling-reinforcing factors, and implemented safeguards. The latter addresses the specific types of games that are played online, and the ways in which different people can engage in their preferred gambling activities on the Internet. In sum, relative to situational characteristics, a large amount of research has been conducted specifying and investigating the structural characteristics of the Internet with regards to online gambling. Such studies have examined the technology of the Internet as enabling gambling relative to land-based venues as well as ways in which gambling on the Internet is reinforced

From those who gambled online, a minority appeared to develop a problem and/or an addiction to Internet gambling. With regards to the reported prevalence of Internet gambling addiction, the results of the various studies varied substantially. Of Internet users, 12-23% appeared to have online gambling problems, whereas 5-20% were found to be pathological gamblers. Student Internet gamblers, on the other hand, had higher prevalence rates suggesting that 18-77% suffer from pathological gambling online. Medical and dental patients also fell within higher ranges with approximately 66% gambling online in a pathological way. Finally, the prevalence rates for adolescents suggested that between 8% and 25% of those who gambled on the Internet were problematic gamblers. However, most of the survey studies had major methodological limitations.

Firstly, a large majority of studies included in our review did not comprise samples that were representative of the general population (i.e., self-selected samples were mostly used). As a consequence, this limits the external validity of results. (In fact, only two pieces of published research have used a large representative national sample – the two most recent British Gambling Prevalence Surveys – see one of my previous blogs concerning the implications of the online gambling data from the latest BGPS findings). Secondly, the methodologies applied to assess Internet gambling addiction were diverse and researchers used a number of different classifications. Thirdly, the reliance on self-reports brought into question the reliability of the reported findings. A solution to this problem may be to include significant others of problem/pathological gamblers in determining whether and to what extent the latter’s gambling behaviours can be classified as being clinically relevant.

Despite these shortcomings, it appears that in general, the results supported the prevalence estimates for land-based pathological gamblers, indicating that the prevalence of pathological gambling was higher in adolescents and college students. The dissimilarity of findings for prevalence rates may therefore be related to (i) measures and conceptualizations, (ii) cut-off points, and (iii) samples used. Valid comparisons are only possible when similar diagnostic tools for problem and pathological gambling are used. Future researchers are therefore advised to conduct cross-cultural studies in order to control for the effect of culture on pathology status.

With regards to specific risk factors for the development of pathological gambling online, it appears that those identified in our literature review were very similar to the results of other studies concerned with land-based pathological gambling. Specifically, the findings that Asian and African ancestry and substance abuse increase the odds for pathological gambling as did the number of gambling types engaged in, and the frequency of gambling. Furthermore, the results with regards to specific personality and socio-demographic characteristics as well as mood status associated with pathological Internet gambling were in line with the findings regarding pathological gambling. More specifically, we found that impulsivity, younger age, male gender, emotional distress, being single, and having higher rates of depression and maladaptive coping, were associated with both online and land-based pathological gambling.

Based on the results of the studies reviewed, gambling on the Internet appeared to be associated with problematic gambling more than land-based gambling is. A reason for this may be the structural characteristics of the Internet inherent to this technology, namely availability, ease of access, anonymity, and convenience. In line with this, the Canadian researchers Robert Wood and Richard Williams point out that although “Internet gambling is an exacerbating rather than a causal factor for most problem gamblers who gamble on the Internet, the nature of online gambling still makes it inherently more problematic than most other forms of gambling”. Therefore, the prevalence of problematic gambling among Internet gamblers is likely to be higher than in land-based gamblers. Therefore, the Internet cannot be claimed to be addictive per sé, but rather to facilitate the engagement in addictive behaviours, such as gambling. Future research is needed to highlight the addictive potential of other Internet applications in addition to gambling. This will inform both prevention efforts and potential treatment modalities.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Additional input from Daria J. Kuss (Nottingham Trent University)

Further reading

Griffiths, M.D. (2010). Gambling addiction on the Internet. In K. Young & C. Nabuco de Abreu (Eds.), Internet Addiction: A Handbook for Evaluation and Treatment. pp. 91-111. New York: Wiley.

Griffiths, M.D. & Parke, J. (2003). The environmental psychology of gambling. In G. Reith (Ed.), Gambling: Who wins? Who Loses? pp. 277-292. New York: Prometheus Books.

Griffiths, M.D., Parke, J. & Derevensky, J. (2011). Online gambling among youth: Cause for concern? In J.L. Derevensky, D.T.L. Shek & J. Merrick (Eds.), Youth Gambling: The Hidden Addiction (pp. 125-143). Berlin: DeGruyter.

Griffiths, M.D., Wardle, J., Orford, J., Sproston, K. & Erens, B. (2009). Socio-demographic correlates of internet gambling: findings from the 2007 British Gambling Prevalence Survey. CyberPsychology and Behavior, 12, 199-202.

Griffiths, M.D., Wardle, J., Orford, J., Sproston, K. & Erens, B. (2011). Internet gambling, health. Smoking and alcohol use: Findings from the 2007 British Gambling Prevalence Survey. International Journal of Mental Health and Addiction, 9, 1-11.

Kuss, D. & Griffiths, M.D. (2012).  Internet gambling behavior. In Z. Yan (Ed.), Encyclopedia of Cyber Behavior (pp.735-753). Pennsylvania: IGI Global.

Parke, J. & Griffiths, M.D. (2007). The role of structural characteristics in gambling.  In G. Smith, D. Hodgins & R. Williams (Eds.), Research and Measurement Issues in Gambling Studies. pp.211-243. New York: Elsevier.

Wardle, H. & Griffiths, M.D. (2011). Defining the ‘online gambler’: The British perspective. World Online Gambling Law Report, 10(2), 12-13.

Wardle, H., Moody, A., Griffiths, M.D., Orford, J. & and Volberg, R. (2011). Defining the online gambler and patterns of behaviour integration: Evidence from the British Gambling Prevalence Survey 2010. International Gambling Studies, 11, 339-356.

In for a penny? Why online penny auctions are a form of gambling

Yesterday, I was quoted in The Observer about activity on online penny auction sites such as ‘Madbid’ and whether they were a form of gambling. My first thought when looking at what people do on these sites was basically gambling. To me they are all but gambling in name and they don’t seem to be regulated by any gambling organization or authority.

The basic idea behind online penny auctions is perhaps laudable. They offer the chance to buy brand new products at very competitive prices. On sites like Madbid, a bid is raised by one penny at the time, so when the current price of a product is (for example) £1.10, the bid is raised to £1.11. There is no time limit as such for the sales time, instead whenever no additional bids are made during a product specific time limit (e.g., five minutes) the auction is automatically closed. To give an example, if a bid is made at 1:06pm and there is a five-minute time limit, at 1:11pm the auction is closed, assuming no other bids are made. The opening times of the auctions are often product specific (e.g., 10am-10pm). Should the product not have been sold by 10pm the auction continues again the following morning.

In order for a person to participate in a penny auction, they need to place a bid in an ongoing auction. They can do this by (a) placing a bid by sending a text message from their mobile phone (at £1.50 a bid plus operator’s costs) or (b) placing a bid through the creation of an online account where the person buys a ‘bundle’ of bids (at 75p to £1.40 a bid depending on how big a bundle they buy in advance). To bid by text message, a person sends a message with the code for the specific product that they want to bid on. To bid using an online account, a person clicks on ‘Register’ and follows the online instructions. There is no limit to how many bids that can be submitted on the same auction product. There is also no limit on how many different products can be bid on at any one time.

Here’s an example of a real winning bid. A PlayStation videogame console (retail price of over £300) was won in a penny auction for £8.34. To the winner of the auction this was won at a hugely discounted price. However, what this really means is that there were 834 separate bids for this item all costing between 75p and £1.50 per bid (depending whether it was done online or via mobile phone). Looking at the ‘bid history’, most of the final 50 bids were made by just two individuals who at a minimum spent at least £30 in those final bids trying to secure the item. Although one person won the console, the other person spent a lot of money and got nothing. I think there are many reasons as to why online penny auctions are akin to gambling. Below are some (but not all) of the main similarities between penny auctions and gambling:

• In penny auctions, winning is essentially chance-determined: There may be limitations on the number of text messages operators allow per month but theoretically a person can bid again and again (on either a single product or multiple products) with no certainty that they will ever win the product. In short, a person could make 10 bids for an item on their mobile phone at £1.50 a bid and end up with nothing. Whether a bidder wins the auction or not, it does not seem to depend on any discernable skill and is more like a chance-based lottery. If there is no real skill in participating and is essentially a chance activity, how is this not a form of gambling.

• Penny auction websites utilise the ‘availability bias’: The availability bias occurs when a person evaluating the probability of a chance event makes the judgement in terms of the ease with which relevant instances come to mind (Griffiths, 1994). For instance, lottery winners are highly publicised. This perpetuates the idea that wins are regular and commonplace. Penny auction websites display the winners of each item. This is a way of emphasising winning and minimising the act of losing. Similarly, penny auction websites have a ‘Meet the winners’ webpage highlighting people that have won very expensive items (like a car) for incredibly low amounts of money. These instances are very rare but by publicising them it makes them appear a more common occurrence.

• Multiple staking for no reward is commonplace in penny auctions: It is clear from looking at almost any of the item bidding histories that many people make multiple bids without ever winning the product. Here, peoples’ multiple bids are similar to putting down multiple stakes when there is a high jackpot prize to be won (e.g., buying lots of lottery tickets during a ‘rollover’ week). In penny auctions, all the bidders bar one on each auction fail to win the product (prize).

• Penny auction websites provide tips for winning: As with many Internet gambling websites (especially online poker websites), penny auction website operators feature webpage sections providing tips on winning for its clientele (e.g., “What can I do to improve my chances of winning?”).

• Penny auction websites have responsible gambling-like policies: Instead of ‘responsible gambling’ policies, the more ethically and responsibly minded penny auction websites have ‘responsible bidding’ policies. For instance, Madbid has a helpful FAQ section that included the question “Is there a risk of addiction to the service?” and provided a link to their ‘Responsible Bidding’ page which gives the following advice:

• Take regular breaks between buying activities.
• Decide a monthly budget in advance as your own personal limit. Do not increase the maximum limit that you have decided for yourself later on.
• Before you start participating in a product purchase, decide the number of bids you are willing to place or determine a price at which you will not raise the bid further.
• Never participate under the influence of alcohol or medication, or if you are in a depressive mood.
• Bid only when you are fully rested and concentrated.

This list looks as though the operators have read the responsible gambling guidelines at an online gambling website and simply replaced the words ‘gamble’ and gambling’ with the words ‘bid’ and ‘buying’.

I have tried to argue that penny auction websites are Internet gambling websites in all but name. They appear to be unregulated and there is no gambling watchdog or regulatory body that oversees their operation. At the very least, the British Gambling Commission should at least do their own investigation to determine whether penny auction websites should come under their regulatory jurisdiction. I also think it would be more socially responsible if penny auction websites listed the total amount spent on bids by the person who got the winning item rather than what the final winning bid was.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D. (2009). Online ‘penny auction’ sites: Regulation needed. World Online Gambling Law Report, 8(1), 3-5.

Griffiths, M.D. & Wood, R.T.A. (2001). The psychology of lottery gambling.  International Gambling Studies, 1, 27-44.

Griffiths, M.D. & Wood, R.T.A. (2008). Responsible gaming and best practice: How can academics help? Casino and Gaming International, 4(1), 107-112.

Parke, J. & Griffiths, M.D. (2007). The role of structural characteristics in gambling.  In G. Smith, D. Hodgins & R. Williams (Eds.), Research and Measurement Issues in Gambling Studies. pp.211-243. New York: Elsevier.

Touchpoint (2011). Penny auctions: Costly pastime or online gambling? February 18. Located at: http://www.nsgamingfoundation.org/publications/touchpoint/Touchpoint%20February%2018,%202011.pdf

Gambling online, social responsibility and ‘foot-in the-door’ practices

Bill Gates arrives at the port to heaven and hell. Petrus says “You see Bill, we don’t know what to do with you. You may choose heaven or hell”. Bill peeks in heaven and sees a couple of old boring men sitting around at a table. Bill takes a look in hell and sees really beautiful women, sex, drugs, rock and roll, and most of all, gambling. Bill says “I am a gambling man, I want to go to hell!” Once in hell, Bill is immediately thrown into the fire. Bill says “Hey, what the hell is this, I saw all the gambling, women, and sex?” The devil says ‘That was just a demo version.”

Hopefully this opening joke highlights that online gamblers need to be aware that commercial operators often use subtle psychological ploys to get them to part with their money. For the online gambling industry, it also raises issues around social responsibility and the extent to which operators should be using such tactics.

One of the most common ways that gamblers can be facilitated to gamble online is when they try out games in the ‘demo’, ‘practice’ or ‘free play’ mode. At one level, most would argue that playing for points rather than money is little more than innocuous fun and ‘good value’ to the player. Furthermore, playing games for free online is akin to ‘skill schools’ that exist offline, such as learning poker or blackjack in a casino. Offline, there are many constraints to ‘learning to play’ as the free opportunities may only be available on certain days and at certain times. On internet gambling sites there is a lot of scope for players to practice games for free before they play with real money. However, gaming operators need to realise that in terms of their social responsibility, games – even the ‘demo’ versions – need to be fair to players. Despite the undoubted positives, there are other not so positive aspects that have been identified in the scientific literature.

The use of ‘greater than chance’ win probabilities during ‘demo’ games is one example of the many tried and tested psychological ‘foot-in-the-door’ techniques used widely in the commercial sector. Some research carried out by psychologists at the University of Laval in Canada showed it was significantly more commonplace to win while ‘gambling’ on the first few goes on a ‘demo’ or ‘free play’ game. They also reported that it was commonplace for gamblers to have extended winning streaks during prolonged periods while playing the ‘demo’ version. Obviously, once gamblers to play for real, the odds of winning may be considerably reduced. Related to this are the urban myths that develop around online gambling. For instance, a very common myth is that a gambler’s first bet after opening an online account is very often a winning one.

There is now a growing number of studies highlighting that playing for free online is popular among teenagers. ‘Money free’ gambling appears to play an important role for adolescents in conceptualising and experiencing Internet gambling. In the 2009 British study of gambling among nearly 9000 adolescents aged 11-to 15-years, Ipsos MORI reported that just over a quarter of them had played in ‘money-free mode’ on internet sites in the week preceding the survey. Further analysis of these data by researchers at Salford University showed that gambling in the money-free mode was the single most important predictor of whether the child had gambled for money, and one of the most important predictors of children’s problem gambling. However, the possibility and extent to which money-free gambling is responsible for real gambling participation and gambling-related risk and harm needs further research.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Forrest, D. K, McHale, I  & Parke, J. (2009). Appendix 5: Full report of statistical regression analysis. In Ipsos MORI (2009)British Survey of Children, the National Lottery and  Gambling 2008-09: Report of a quantitative survey. London: National Lottery Commission.

Griffiths, M.D. & Parke, J. (2010). Adolescent gambling on the Internet: A review. International Journal of Adolescent Medicine and Health, 22, 59-75.

King, D.L., Delfabbro, P.H. & Griffiths, M.D. (2010). The convergence of gambling and digital media: Implications for gambling in young people. Journal of Gambling Studies, 26, 175-187.

Sevigny, S., Cloutier, M., Pelletier, M. & Ladouceur, R. (2005). Internet gambling: Misleading payout rates during the “demo” period. Computers In Human Behavior, 21, 153-158.

 

Is online gambling more ‘dangerous’ than offline gambling?

A question that is often asked by policymakers is whether online gambling is more ‘dangerous’ or ‘harmful’ than offline gambling. The answer to this question depends on what the definitions are of ‘harmful’ or ‘dangerous’ or (more importantly) whether online gambling is more harmful or dangerous to particular kinds of people (e.g., problem gamblers). There has been much debate in both the media and academic research outlets related to this question. This is an issue that Michael Auer and I recently examined in more detail in an article in Casino and Gambling International (CGI).

In our CGI article, we noted that there have also been a number of different approaches to collecting information about online gamblers. We argued that most published studies concerning online gambling have used one of two approaches – behavioural tracking studies (e.g., studies that collect data based on real online gamblers’ data typically supplied by online gaming operators to academic researchers) and self-report studies (e.g., studies that collect data via surveys, focus groups and/or interviews). Studies using self-report methods have tended to argue that problem gambling is more prevalent among online gamblers compared to offline gamblers. Studies using behavioural tracking data have tended to argue that online gambling is no more dangerous than offline gambling. At face value, this suggests that findings (relating to ‘dangerousness’ of the gambling medium) appear to depend upon the methodology used.

Both of these approaches have advantages and disadvantages. In our CGI article, we noted the following key differences between these two methods:

• Behavioural tracking data provides a totally objective record of an individual’s gambling behaviour on a particular online gambling website (whereas individuals in self-report studies may be prone to social desirability factors, unreliable memory, etc.).
• Behavioural tracking data provide a record of events and can be revisited after the event itself has finished (whereas self-report studies cannot).
• Behavioural tracking data usually comprise very large sample sizes whereas self-report studies are based on much smaller sample sizes.
• Behavioural tracking data collects data from only one gambling site and tells us nothing about the person’s Internet gambling in general (as Internet gamblers typically gamble on more than one site)
• Behavioural tracking data always comes from unrepresentative samples (i.e., the players that use one particular internet gambling site) whereas the very best self-report studies (e.g., the British Gambling Prevalence Surveys in Great Britain) use random and nationally representative samples
• Behavioural tracking data does not account for the fact that more than one person can use a particular account
• Behavioural tracking data tell us nothing about why people gamble (whereas self-report data can provide greater insight into motivation to gamble)
• Behavioural tracking data cannot be used for comparing online and offline gambling or for making comparisons about whether online gambling is safer or more dangerous than offline gambling as data are only collected on one group of people (i.e., online gamblers).
• Self-report methods can be used to compare two (or more) groups of gamblers and is the only method we currently have to infer to what extent one medium of gambling may or may not be more or less safe.
• Some self-report studies have the potential to use nationally representative samples of gamblers whereas behavioural tracking studies rely on self-selected samples of gamblers who use the online gambling website in question.
• Behavioural tracking data tell us nothing about the relationships between gambling and other behaviours (e.g. the relationship between gambling and alcohol or the relationship between gambling and tobacco use).
• Behavioural tracking data cannot examine problem gambling using current diagnostic criteria (whereas self-report studies can). In fact, behavioural tracking data studies cannot tell us anything about problem gambling as this is not a variable that has been examined in any of the published studies to date.

To date, one team of researchers affiliated to Harvard University have been given access to a large behavioural tracking data set of over 47,000 online gamblers by the Austrian gaming company bwin. This has led to many papers examining the actual behaviour of online gamblers based on behavioural tracking data. These data have been used to make claims along the lines that online gambling is no more problematic than offline gambling.

However, comparative statements relating to whether one medium of gambling is more problematic than another can only be made if actual gambling behavior is studied across different forms of gambling (e.g., direct comparison of internet gambling with [say] land-based casino gambling). None of the various publications by the Harvard-affiliated research team have empirically compared different forms of gambling. Nor have they examined ‘problem gambling’ as no problem gambling screens were given to any online gambler included in their studies. Therefore, conclusions about the harmfulness of online gambling in comparison to other forms of gambling cannot be drawn from these particular studies. Furthermore, none of the publications focusing on online gambling examine overall gambling behavior. All the publications have tended to examine a single type of game (e.g., sports betting, casino games, poker).

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D.  (2011). Empirical internet gambling research (1996-2008): Some further comments. Addiction Research and Theory, 19, 85-86.

Griffiths, M.D. & Auer, M. (2011). Approaches to understanding online versus offline gaming impacts. Casino and Gaming International, 7(3), 45-48.

Griffiths, M.D., Wardle, J., Orford, J., Sproston, K. & Erens, B. (2009). Socio-demographic correlates of internet gambling: findings from the 2007 British Gambling Prevalence Survey. CyberPsychology and Behavior, 12, 199-202.

Griffiths, M.D., Wardle, J., Orford, J., Sproston, K. & Erens, B. (2011). Internet gambling, health. Smoking and alcohol use: Findings from the 2007 British Gambling Prevalence Survey. International Journal of Mental Health and Addiction, 9, 1-11.

LaBrie, R.A., Kaplan, S., LaPlante, D.A., Nelson, S.E., & Shaffer, H.J. (2008). Inside the virtual casino: A prospective longitudinal study of Internet casino gambling. European Journal of Public Health, 18(4), 410-416

LaBrie, R.A., LaPlante, D.A., Nelson, S.E., Schumann, A. & Shaffer, H.J. (2007). Assessing the playing field: A prospective longitudinal study of internet sports gambling behavior. Journal of Gambling Studies, 23, 347-363.

LaPlante, D.A., Kleschinsky, J.H., LaBrie, R.A., Nelson, S.E. & Shaffer, H.J. (2009). Sitting at the virtual poker table: A prospective epidemiological study of actual Internet poker gambling behavior. Computers in Human Behavior 25, 711-717.

LaPlante, D. A., Schumann, A., LaBrie, R. A., & Shaffer, H. J. (2008). Population trends in Internet sports gambling. Computers in Human Behavior, 24(5), 2399–2414.

Shaffer, H.J., Peller, A.J., LaPlante, D.A., Nelson, S.E., & LaBrie, R.A. (2010). Toward a paradigm shift in Internet gambling research: From opinion and self-report to actual behavior. Addiction Research and Theory, 18, 270–283.

Wardle, H. & Griffiths, M.D. (2011). Defining the ‘online gambler’: The British perspective. World Online Gambling Law Report, 10(2), 12-13.

Wardle, H., Moody, A., Griffiths, M.D., Orford, J. & and Volberg, R. (2011). Defining the online gambler and patterns of behaviour integration: Evidence from the British Gambling Prevalence Survey 2010. International Gambling Studies, 11, 339-356.

Xuan, Z.M. & Shaffer, H.J. (2009). How do gamblers end gambling: Longitudinal analysis of internet gambling behaviors prior to account closure due to gambling related problems. Journal of Gambling Studies, 25, 239-252.

 

 

(Don’t) Get Off My Cloud! Where will Cloud Computing take the Gaming Industry?

Over the last 18 months, I’ve been asked on more than one occasion what I think about Cloud Computing (CC) and implications for the gaming industry. To be very honest, I had been bluffing my way through these conversations for some time and it wasn’t until I was at a video game conference in Malta earlier this year that I really got to grips with what CC is all about.

For those of you who still have no idea what I am talking about, at a very basic level, CC means that users obtain or use information from another server. In practical terms it refers to software hosted and accessed online, rather than on physical hardware or servers (Google Docs being the software application that I am – and probably most other academics I know are – most familiar with). In essence, CC involves an external third party storing and/or hosting data and/or applications for the company using the service. Although CC is a relatively new term, the underlying idea (and arguably the technology) has been around for some time.

So what does this all mean for the gaming industry? In the last decade online gambling has started to take off and is slowly displacing offline gambling activity. Although the number of people who gamble online are in a small minority, internet access has become cheap and other external factors (such as national smoking bans and online gambling being seen as providing ‘good value’ for players) are starting to impact on the offline leisure industry (including gambling).

There are of course a number of reasons why gaming companies are moving into Cloud Computing. Advocates of CC are almost evangelical in their praise for what it can offer companies. Many commentators refer to CC as “a game changer”. In relation to video gaming, I have even seen CC described as a “console killer” as gamers will be able to play from anywhere on any device that has internet access (such as their iPads). In this context, “cloud gaming” can stream ‘on-demand’ games to players who don’t want to buy expensive and/or bespoke hardware. For instance, the millions of Farmville players on the social networking site Facebook shows the impact of games using CC can potentially have. Furthermore, as Eric Knipp (Principal Research Analyst at Gartner Research) says:

“Companies use a variety of tactics to crack the golden egg. Some include basic table stakes – easy to use, well-documented programming and/or packaging interfaces, reliable monetization mechanisms, digital rights management, and reasonable revenue splits with game publishers and developers. Additional tricks of the trade include support for game-enriching hosted capabilities (like multiplayer, matchmaking, player-to-player relationship management (a.k.a. “friends”), product recommendation engines, and player ranking systems). Marketplaces must balance their efforts to attract both the gamer and the creator” (http://gametheoryonline.com/2010/09/03/cloud-computing-changes-video-games/)

Almost every article I have read typically asserts that if implemented and used correctly, CC brings a number of immediate benefits to commercial online companies to help them “stay ahead of the curve and the competition” including (i) increased performance and efficiency savings, (ii) enhanced security, (iii) increased reliability, and – arguably the most important – (iv) reduced financial costs. The reduced costs primarily come from companies being able to try out new applications without having to invest in potentially expensive information technology infrastructure. Additionally, company start-up costs are likely to be lower, and the cost of using CC storage and services are likely to be cheaper than the cost of maintaining its own servers.

Gaming businesses will need to offer services in the way that customers want them. In the gambling market, the most obvious application will be when large amounts of people want to gamble or bet on a particular high profile sporting event simultaneously and/or at short notice such the FA Cup final or the Grand National. The other area where CC is likely to be of help in the gambling arena is for gamblers who play games in multiple media including the internet, mobile phones, and interactive television. CC allows gambling to be available 24/7 even when people are on the move. Other benefits include (i) the opportunity for social gameplay (i.e., playing along with many other gamblers), (ii) the opportunity for servers to be added on a daily basis, (iii) games can be reconfigured automatically, and (iv) services can be corrected with relative ease.

The move towards cloud computing in the gaming industry is starting to happen. Earlier this year, Bet 365 (the British online casino operator) adopted a cloud computing solution to reduce the latency of its core betting system as a way of improving gamblers’ experiences on its website. In layman’s terms, it speeds things up for those accessing the website and can handle large simultaneous demand. The use of CC in Bet 365’s ‘In-Play’ betting system now means that punters can increase their stake in less than two seconds and can support up to a few million gamblers concurrently.

Successful gaming companies are likely to be those that cater for what their customers want. There appears to be a demand from gamblers for access to a much larger number of events and markets. Cloud Computing appears to provide the infrastructure for how the demand can be met – even if it is unpredictable!

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D. (2011). Technological trends and the psychosocial impact on gambling. Casino and Gaming International, 7(1), 77-80.

Griffiths, M.D. (2011). Gaming convergence: Further legal issues and psychosocial impact. Gaming Law Review and Economics, 14, 461-464.

King, D.L., Delfabbro, P.H. & Griffiths, M.D. (2010). The convergence of gambling and digital media: Implications for gambling in young people. Journal of Gambling Studies, 26, 175-187.

What is an online gambler? Some surprising findings from the latest British Gambling Prevalence Survey

Things have come a long way since I published my first academic paper on internet gambling back in 1996. Despite a large increase in online gambling research over the last decade, much of the published work to date seems to suggest that differentiating (say) online casino gamblers from online poker players is relatively easy and that there are discrete types of online gambler. However, this isn’t necessarily the case.

Earlier this year, I (along with Heather Wardle who led the research for the latest British Gambling Prevalence Survey) published an article examining what an online gambler actually is. This question may appear somewhat strange and/or self-evident. In fact, many of you reading this may have already reached the conclusion that it is obvious what an online gambler is (i.e., someone who has gambled online). However, those of us who carry out research into online gambling have to be very specific and operationally define what we mean by an “online gambler” in every piece of research that we carry out. For instance, is it right to call someone who gambles a few times a year at an online casino but also gambles on slot machines every week at an amusement arcade an “online casino gambler”?

Most of the published research talks about “online gamblers” as if everyone is totally clear as to what is being referred to when findings are reported. Many of the published research studies in the area (including many of my own) have compared ‘online gamblers’ and ‘offline gamblers’. For instance, in our secondary analyses of the British Gambling Prevalence Survey (BGPS) 2007 data (published in a number of papers between 2009 and 2011), online gamblers were simply defined as anyone who had gambled online (e.g., gambled at an online casino, used an online betting exchange, had made a bet online, etc.) but excluded those who had bought online lottery tickets. Our research reported that the problem gambling prevalence rate amongst those who had gambled online was 5% compared to 0.5% for those who had never gambled online. This led to the conclusion that either gambling in an online medium is more ‘dangerous’ and/or problem inducing for gamblers than land-based gambling, and/or that vulnerable gamblers may be more susceptible to developing problems online because of factors such as 24/7 access and convenience factors.

One of the main problems with this is that online gamblers typically gamble offline also. In the 2007 BGPS, of the 9003 participants, a small minority (476 people) reported gambling online in the past year. Of these, only nine people didn’t take part in any other kind of ‘offline’ gambling activity. In other words, the vast majority of online gamblers (98%) also gambled offline. These data suggest that in Britain, ‘online only’ gambling is a low prevalence activity (i.e. 5% of BGPS respondents had gambled online in the last year but only 0.1% had only gambled online in the past year).

According to the latest BGPS published in February 2011, the number of ‘online only gamblers’ had slightly increased to 2% but our data suggest there are a number of distinct ways to categorize gamblers based on the medium in which they gamble and what activities they gamble on in those mediums. This month, we published our secondary analysis of the online gambling data from the latest BGPS in the latest issue of the journal International Gambling Studies. The 2011 BGPS report surveyed 7756 adult gamblers. Approximately one in seven respondents (14%) had gambled online in the past year (i.e., had gambled on at least one gambling activity such as gambling at online casinos and/or playing the lottery online). However, for the first time ever, we created four new groups of gamblers for comparison. These were those that:

• Gambled offline only (i.e., had gambled on at least one activity such as buying a lottery ticket in a shop or playing roulette at an offline casino but hadn’t gambled online in the past year)
• Gambled online only (i.e., had gambled on at least one activity such as gambling on a betting exchange or gambling at an online casino but hadn’t gambled offline in the past year)
• Gambled both online and offline but on different activities (i.e., had gambled on at least one activity online and one activity offline but were different activities such as gambling on a slot machine in an amusement arcade and playing blackjack in an online casino).
• Gambled both online and offline but on the same activities (i.e., had gambled on at least one activity both online and offline such as gambling at both an online and offline casino)

Perhaps unsurprisingly, of all gamblers, the largest group were those who only gambled offline only (80.5%) and the smallest group were those who gambled online only (2.1%). Of far more interest were the rates of problem gambling among these four groups. The highest prevalence rates of problem gambling were amongst mixed mode gamblers who gambled on different activities (4.3%), followed by mixed mode gamblers who gambled on the same activities (2.4%), those who only gambled offline (0.9%), and those who only gambled online (0%).

The most interesting statistic is arguably the fact that there wasn’t a single case of problem or pathological gambling among those gamblers who only gambled online. Extreme caution must be given as the player base for ‘online only’ gamblers is very small when compared to the other groups. However, this certainly opens up an area for future research as to whether those who only gamble online are more resilient to developing gambling problems than those who engage in mixed modes of gambling. Socio-demographic information from the BGPS studies suggest that those who gamble online are more educated and in better occupations than those who have never gambled online. Maybe, these demographic factors are also protective factors when it comes to the development of gambling problems?

The more refined analysis that we have carried out using the latest BGPS data demonstrates that direct comparisons between online and land-based gamblers typically ignores the more complex nature of how people gamble in and across different media and gambling activities. However, our secondary analysis aimed to demonstrate that these very basic distinctions, using the mode and type of gambling as the primary discriminators, produces a wide range of gambling sub-types for future analysis and demonstrates that the concept of ‘online gambler’ isn’t homogenous.

At present, policy decisions surrounding online gambling – particularly in relation to problem gambling – are often made by conceptualizing online gambling as a single entity. Our research findings based on just a few basic variables including the medium in which people gamble, the type and number of activities engaged in, and the regularity with which people gamble, produces a complex picture of online gambling and demonstrates its heterogeneity.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, NG1 4BU

Further reading

Griffiths, M.D., Wardle, J., Orford, J., Sproston, K. & Erens, B. (2009). Socio-demographic correlates of internet gambling: findings from the 2007 British Gambling Prevalence Survey. CyberPsychology and Behavior, 12, 199-202.

Griffiths, M.D., Wardle, J., Orford, J., Sproston, K. & Erens, B. (2011). Internet gambling, health. Smoking and alcohol use: Findings from the 2007 British Gambling Prevalence Survey. International Journal of Mental Health and Addiction, 9, 1-11.

Wardle, H. & Griffiths, M.D. (2011). Defining the ‘online gambler’: The British perspective. World Online Gambling Law Report, 10(2), 12-13.

Wardle, H., Moody, A., Griffiths, M.D., Orford, J. & and Volberg, R. (2011). Defining the online gambler and patterns of behaviour integration: Evidence from the British Gambling Prevalence Survey 2010. International Gambling Studies, 11, 339-356.