Business simulations are defined as serious games in which attendees play the role of managers or firm owners competing to sell their goods to the consumers against other companies on the market. Business games are widely used for the development of individual decision making or organization capabilities in universities and companies. Such business simulation games also provide an extensive view of the complexity of a business situation and allow players to get a multidimensional insight of the real-life business process and problematic. A business strategy game is a more special case of a business simulation or business game. With such a type of game, different types of markets can be simulated, to force the participants of the game to develop or test different strategies like cost leadership, differentiation or focus and make appropriate strategic decisions. The problem, of modeling the marketplace or buyers-market for the game, is perhaps the most central and unavoidable issue of a business simulation game. The algorithms that are responsible for calculating the market and firm demand have been evaluated as the most complex and important algorithms of a business simulation game. In this thesis an agent-based model approach is used to model the market at a consumer detailed level for the implementation of a web-based strategic business game. The flexible composition of the market, which results from the usage of the agent-based model approach allows simulating different scenarios in the strategic business game and overcomes the lack of flexibility of the standard models. The results of the implemented artifact in this thesis provided some evidence to sustain the hypothesis that an agent-based model can provide additional information and advantages in a strategic business simulation game. Moreover, the agent-based model approach allowed the modeling of different market compositions on a micro-level compared to other standard models, allowing the investigation of the market and strategic alignment of the participants in the game.