Author List: Ma, Xiao; Kim, Seung Hyun; Kim, Sung S.;
Information Systems Research, 2014, Volume 25, Issue 3, Page 511-527.
The objective of this work is to examine various psychological forces underlying the behavior of people’s online gambling, an increasingly popular form of entertainment in the gaming industry. Drawing on extant theories, we first developed a model of how cumulative outcomes, recent outcomes, and prior use affect online gambling behavior differently. We empirically tested the model using longitudinal panel data collected over eight months from 22,304 actual users of a gambling website. The results of a multilevel panel data analysis strongly supported our hypotheses. First, consistent with gambling theory, individuals' online gambling was found to increase with any increase in a cumulative net gain or cumulative net loss. Second, as the availability heuristic prescribes, a recent loss reduced online gambling, whereas a recent gain increased it. Third, consistent with the literature on repeated behavior, regular use and extended use moderated the relationship between current and subsequent gambling. Taken together, the present study clarifies how people react differently to immediate and cumulative outcomes and also how regular use and extended use facilitate routine behavior in the context of online gambling. In general, our findings suggest that the three perspectives, i.e., gambling theory, the availability heuristic, and repeated behavior, should be taken into account to understand online gambling, which is in essence a series of risk-taking attempts with the potential of eventually becoming routine behavior. This study is expected to offer valuable insights into other types of online games that could engage people in risking real or cyber money and, at the same time, could be easily enmeshed with everyday life (e.g., fantasy sports, online virtual worlds).
Keywords: online user behavior;online gambling;repeated behavior;decision making under uncertainty;panel data;multilevel analysis;hierarchical analysis
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#75 0.261 behavior behaviors behavioral study individuals affect model outcomes psychological individual responses negative influence explain hypotheses expected theories consequences impact theory
#130 0.193 online users active paper using increasingly informational user data internet overall little various understanding empirical despite lead cascades help availability
#108 0.153 model research data results study using theoretical influence findings theory support implications test collected tested based empirical empirically context paper
#174 0.099 use support information effective behaviors work usage examine extent users expertise uses longitudinal focus routine revealed volume constructs contributes operations
#171 0.081 markets industry market ess middle integrated logistics increased demand components economics suggested emerging preference goods interesting form recent vertically chinese
#106 0.054 integration present offer processes integrating current discuss perspectives related quality literature integrated benefits measures potential regarding issues finally taken propose
#121 0.054 human awareness conditions point access humans images accountability situational violations result reduce moderation gain people features presence increase uses means