An Empirical Analysis of Regulation Policy Effects on Social Casino Using Vector Autoregression

The objective of this study is to examine the effects of regulation policy on online gambling, an increasingly popular type of entertainment in the online game industry. Prior information systems (IS) studies on online game focus primarily on user behavior. However, there is a growing need to investigate the effects of regulation policy on dynamic changes of games or service providers instead of ad hoc heuristic approaches on individual behavior. Going beyond the approaches of previous studies, this study empirically test the regulation policy effect with three theoretical perspectives: social influence, prior experience and perceived switching cost. A vector autoregression (VAR) methodology is used to forecast game usage and to model several patterns of the co-movement of online games. Evidence is also provided of strong Granger-causal interdependencies within games and service providers. This study provides one of the first empirical evidences that examine the effects of regulation policies on online game. In research methodology aspect, this study also introduce an exposition of VAR methodology in IS research. Therefore, it provides advanced knowledge on gambling behavior and helps develop suitable regulation policy to protect users of online gambling as well as to satisfy policy makers.