Literature DB >> 23508851

An empirical investigation of theoretical loss and gambling intensity.

Michael Auer1, Mark D Griffiths.   

Abstract

Many recent studies of internet gambling-particularly those that have analysed behavioural tracking data-have used variables such 'bet size' and 'number of games played' as proxy measures for 'gambling intensity'. In this paper it is argued that the most stable and reliable measure for 'gambling intensity' is the 'theoretical loss' (a product of total bet size and house advantage). In the long run, the theoretical loss corresponds with the Gross Gaming Revenue generated by commercial gaming operators. For shorter periods of time, theoretical loss is the most stable measure of gambling intensity as it is not distorted by gamblers' occasional wins. Even for single bets, the theoretical loss reflects the amount a player is willing to risk. Using behavioural tracking data of 100,000 players who played online casino, lottery and/or poker games, this paper also demonstrates that bet size does not equate to or explain theoretical loss as it does not take into account the house advantage. This lack of accuracy is shown to be even more pronounced for gamblers who play a variety of games.

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Mesh:

Year:  2014        PMID: 23508851     DOI: 10.1007/s10899-013-9376-7

Source DB:  PubMed          Journal:  J Gambl Stud        ISSN: 1050-5350


  3 in total

1.  Real limits in the virtual world: self-limiting behavior of Internet gamblers.

Authors:  Sarah E Nelson; Debi A LaPlante; Allyson J Peller; Anja Schumann; Richard A LaBrie; Howard J Shaffer
Journal:  J Gambl Stud       Date:  2008-08-12

2.  Inside the virtual casino: a prospective longitudinal study of actual Internet casino gambling.

Authors:  Richard A Labrie; Sara A Kaplan; Debi A Laplante; Sarah E Nelson; Howard J Shaffer
Journal:  Eur J Public Health       Date:  2008-04-23       Impact factor: 3.367

3.  Virtual harm reduction efforts for Internet gambling: effects of deposit limits on actual Internet sports gambling behavior.

Authors:  Anja Broda; Debi A LaPlante; Sarah E Nelson; Richard A LaBrie; Leslie B Bosworth; Howard J Shaffer
Journal:  Harm Reduct J       Date:  2008-08-06
  3 in total
  9 in total

1.  Consumer Profile Segmentation in Online Lottery Gambling Utilizing Behavioral Tracking Data from the Portuguese National Lottery.

Authors:  Bernardo T Chagas; J F S Gomes; Mark D Griffiths
Journal:  J Gambl Stud       Date:  2021-09-13

2.  Conceptual Issues Concerning Internet Addiction and Internet Gaming Disorder: Further Critique on Ryding and Kaye (2017).

Authors:  Mark D Griffiths
Journal:  Int J Ment Health Addict       Date:  2017-10-17       Impact factor: 3.836

3.  Self-Reported Losses Versus Actual Losses in Online Gambling: An Empirical Study.

Authors:  Michael Auer; Mark D Griffiths
Journal:  J Gambl Stud       Date:  2017-09

4.  Digital Traces of Behaviour Within Addiction: Response to Griffiths (2017).

Authors:  David A Ellis; Linda K Kaye; Thomas D W Wilcockson; Francesca C Ryding
Journal:  Int J Ment Health Addict       Date:  2018-01-03       Impact factor: 3.836

5.  Understanding Online Voluntary Self-Exclusion in Gambling: An Empirical Study Using Account-Based Behavioral Tracking Data.

Authors:  Maris Catania; Mark D Griffiths
Journal:  Int J Environ Res Public Health       Date:  2021-02-19       Impact factor: 3.390

6.  A Normative Feedback Intervention on Gambling Behavior-A Longitudinal Study of Post-Intervention Gambling Practices in At-Risk Gamblers.

Authors:  Jonas Berge; Tove Abrahamsson; Axel Lyckberg; Katja Franklin; Anders Håkansson
Journal:  Front Psychiatry       Date:  2022-03-31       Impact factor: 4.157

7.  The use of personalized behavioral feedback for online gamblers: an empirical study.

Authors:  Michael M Auer; Mark D Griffiths
Journal:  Front Psychol       Date:  2015-09-23

8.  Personalized Behavioral Feedback for Online Gamblers: A Real World Empirical Study.

Authors:  Michael M Auer; Mark D Griffiths
Journal:  Front Psychol       Date:  2016-11-28

9.  Cognitive Dissonance, Personalized Feedback, and Online Gambling Behavior: An Exploratory Study Using Objective Tracking Data and Subjective Self-Report.

Authors:  Michael Auer; Mark D Griffiths
Journal:  Int J Ment Health Addict       Date:  2017-09-20       Impact factor: 3.836

  9 in total

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