Association of Marketing Theory and Practice Proceedings 2011


Dimensions of Problem Gambling Behavior Associated with Purchasing Sports Lottery

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Conference Proceeding

Conference Track

Sport Marketing

Publication Date



Sport gambling is a major segment of the sport industry. Although various forms of sport gambling may help generate revenues, increase governmental tax income, and advance social and economic development, it has the potential to cause social, family, and individual problems, thus imposing cost and burden to a community. In recent years, problem gambling associated with purchasing sports lottery has gradually emerged as a major social issue in China. Problem gambling is often referred as all patterns of gambling behavior that compromise, disrupt, or damage personal, family, or vocational pursuits (Lesieur, 1988). From this perspective, pathological gambling can be regarded as a sub-category, or one end of a continuum, of gambling-related problems. The term of problem gambling can also be used to denote a level of gambling, ranging from an early stage of on-site problems to compulsive or pathological gambling as diagnosed by applying the DSM-IV diagnostic instrument (Moore, 2002; Raylu & Oei, 2002; Rosenthal, 1989; Volberg, 2001). When people refer to problem gambling, it typically means subclinical level of gambling problems. While many studies have been conducted on general problem gambling, few have focused on issues that are primarily caused by sports betting. Furthermore, previous studies on problem gambling have mainly been conducted in western countries, such as the U.S., Australia, Britain, and Canada; research findings from these studies are limited in their applicability to China due to historical, social, and cultural differences. For instance, the government-run sports lottery in China has existed for merely 20 years and because of the absence of other gambling forms in mainland China, sports lottery is the primary outlet of gambling with a large participation rate among Chinese residents. Understanding the fundamental issues caused by sports lottery is precursor to formulating effective strategies for prevention, intervention, or even rehabilitation.

The purpose of this study was to identify and examine the dimensions of problem gambling behaviors associated with purchasing sports lottery in China. This was accomplished through the development and validation of the initial Scale of Assessing Problem Gambling (SAPG). The SAPG was initially developed through conducing a comprehensive review of literature (e.g., Custer, 1982; Lesieur & Blume, 1987), conducting open-ended interviews of gamblers (n = 20), administrators of sports lottery programs (n = 40), and retail store managers (n = 20), and summarizing telephone transcripts of a hotline for problem gambling. Through these procedures, a total of 45 items were identified, which was submitted to a panel of experts in gambling research or administration (n = 9) for a test of content validity. A total of 32 items were retained and phrased into a Likert 5-point scale. A survey packet was prepared that contained an informed consent letter, the SAPG items, and demographic variables. Research participants (N = 4,991) were Chinese residents who have purchased sports lottery tickets in the past 12 month. Test administration was carried out in five large cities (Shenyang, Shanghai, Guangzhou, Chengdu and Zhengzhou) with population ranging from 7 million to 15 million. These cities represented the largest lottery market in five geographical regions of China. Within each city, a computer-generated, randomly stratified multistage sampling method was used to survey one out of 10 thousands of local adult population. Following the survey packet, one-on-one interviews was conducted at retailing stores of sports lottery by trained investigators. A total of 5,450 interviews were conducted, and 4,991 participants were willing to complete the survey, representing a response rate of 92%. A sports lottery ticket was used as an incentive to complete the study. Of the respondents, 77.3% were male and 22.7% female. In terms of occupation, 39.1% were professionals,, 20.4% unemployed or retired, 19.3% peasant workers, 12.1% private business owners, and 8.5% students or others. A majority of the participants (i.e., 93%) ranged in age between 20 and 60 years old. Due to the exploratory nature of this study, the total sample was randomly split into two halves (Lattin, Carroll, and Green 2003). The first half was used for conducting an EFA and the second half for a CFA. Both EFA and CFA were examined using weighted least-square means and variance adjusted (WLSMV) estimates, following the procedures in Mplus 5.12 (Muthen and Muthen, 2006). The ‘goodness-of-fit’ approach was adopted to determine the number of factors in the EFA (Fabrigar et al. 1999). An EFA with Geomin for oblique rotation revealed that a four-factor solution was optimal (RMSEA=.04, TLI=.99, CFI=.96), including Harmful Behaviors (9 items), Compulsive Disorders (6 items), Over Expectation (2 items), and Depression Sign (2 items). All factors had low to moderate inter-item correlation (.18-.69). As the EFA findings were data driven, an in-depth examination of content interpretability of the factors revealed that the Harmful Behavior factor contained two distinct concepts and should thus be split into two factors: Social Consequence (4 items) and Financial Consequence (5 items). In the CFA, the five-factor model showed good fit to the data (RMSEA = .050, TLI=.978, and CFI=.922). All factors again showed low to moderate inter-item correlation with each other (.29-.60). Conducting a comparison with the original four-factor structure (RMSEA = .052, TLI=.976, and CFI=.915), the level of model fit for the five-factor structure was significantly (p < .05) superior (χ24 = 65.03). As the Over Expectation and Depression Sign factors had only two items, they were of mediocre composite reliability coefficients (.60 and .72) and AVE values (.41 and .43). The composite reliability coefficients for the remaining three factors were greater than .80 and AVE values greater than .50, respectively, indicating good convergent validity. Consequently, the SAPG scale with a total of 19 items under five factors (i.e., Social Consequence, Financial Consequence, Harmful Behavior, Compulsive Disorder, and Depression Sign) was formulated with good measurement properties to assess problem gambling of sports lottery consumers in China. This study represents an initial effort to understand the dimensions of problem gambling associated with Chinese sports lottery. The developed scale may be adopted by researchers and practitioners to examine problem gambling behaviors and develop effective prevention and intervention procedures based on tangible evidence. With proper adaption, modification, and validation, the SAPG has the potential to be adopted in other socio-cultural contexts, such as North America, where behavioral problems associated with sport gambling likely exist among sport gamblers and yet, few specific measurement tools are available.

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