This study investigated the lucrative potential of late life gamblers in terms of spending, switching, travel, and economic impact. It further offered comparisons with the non—late life cohort. A rigorous process of statistical testing indicated both similarities and dissimilarities between the older and the younger cohorts. Switching emerged as a significant predictor of spending. The economic impact model using IMPLAN software afterward indicated significant economic potential of the late life market in terms of direct, indirect, and induced impacts.
Black Hawk County Survey. (2004). Gambling behavior. Cedar Falls: Sustainable Tourism Environment Program, University of Northern Iowa.
2.
Campbell, F. (1976). The future of gambling: The futurist. Bethesda, MD: World Future Society.
3.
Chhabra, D. (2007). Estimating benefits and costs of casino gambling in Iowa, United States. Journal of Travel Research, 46, 173-182.
4.
Iowa Gambling Treatment Program. (2006). Behavioral risk factor surveillance system report. Retrieved August 18, 2007, from http://www.1800betsoff.org/information.asp#reports_studies
5.
Iowa Racing and Gaming Association. (2005). Statistical information. Retrieved December 15, 2004, from http://www.3.state.ia.us/irgc
6.
Iowa Welcome Centers. (2004). Survey results. Des Moines: Iowa Department of Economic Development Tourism Office.
7.
Lucas, A., & Brewer, K. (2001). Managing the slot operations of a hotel casino in the Las Vegas locals' market. Journal of Hospitality & Tourism Research, 25, 289-301.
8.
McNeilly, D.P., & Burke, W.J. (2000). Late life gambling: The attitudes and behaviors of older adults. Journal of Gambling Studies, 16, 393-415.
9.
Moufakkir, O. (2006). An analysis of elderly gamers' trip characteristics and gambling behavior: Comparing the elderly with their younger counterparts . UNLV Gaming Research and Review Journal, 10, 63-76.
10.
National Opinion Research Center. (1999). Gambling impact and behavior study. Report to the National Gambling Impact Study Commission. Chicago: University of Chicago, Gemini Research, The Lewin Group, and Christiansen/ Cummings Associates. (Available as part of the NGISC's final report issued June 18, 1999, at www.ngisc.gov.)
11.
Norusis, M. (2005). SPSS 14.0 statistical procedures companion. Chicago: SPSS.
12.
Ryan, T., & Speyrer, J. (1999). Gambling in Louisiana: A benefit/cost analysis. A report prepared for the Louisiana Gaming Control Board. New Orleans: University of New Orleans.
13.
Shaffer, H. (1997). Estimating the prevalence of disordered gambling behavior in the United States and Canada: A meta-analysis. Cambridge, MA: Harvard Medical School Division on Addictions, Harvard University.
14.
Stitt, G., Nichols, M., & Giacopassi, D. (2002). Casino gambling as a catalyst of economic development: Perceptions of residents in new casino jurisdictions . Tourism Economics, 8, 59-75.
15.
Stitt, G., Nichols, M., & Giacopassi, D. (2005). Perception of casinos as disruptive influences in USA communities. International Journal of Tourism Research, 7, 187-200.
16.
Stone, K., Otto, D., & Siegelman, H. (2004). Analysis of the Iowa gaming industry: Market patterns, economic impact and the likely effects of an expansion in the number of licensees . Des Moines, IA: Strategic Business Group.
17.
Titz, K., Miller, J., & Andrus, D. (1998). Hedonic scales used in a logit model to explore casino game choice. Journal of Hospitality &Tourism Research , 22, 129-141.
18.
Waterloo/Cedar Falls Tourism Advertisement Conversion Study. (2004). Mail-out survey report. Cedar Falls: Sustainable Tourism Environment Program, University of Northern Iowa.
