Determinants of Service Supply Chain Performance: Agent-based Modeling Approach to the Motion Picture Industry
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Researchers have emphasized the dynamic nature of the service supply chain of the motion picture industry but had difficulty studying the dynamics because traditional research methodologies were limited. This study explores interaction and competition among the supply chain participants and focuses on capturing the dynamics by using agent-based modeling. An agent-based model has been developed based on the decision-making rules of moviegoers and theaters. Transitional probabilities and a multinominal logit model have been applied to moviegoers' decision-making process. Results of the Chi-square test of market share among the movies released in 2000 show that the research model can explain supply chain dynamics. After validating the model, research propositions are suggested by conducting a scenario analysis in perspective of market size and product diversity, as well as theater performance. This research can be used to forecast the performance of a movie based on pre-release information.
Abstract
Researchers have emphasized the dynamic nature of the service supply chain of the motion picture industry but had difficulty studying the dynamics because traditional research methodologies were limited. This study explores interaction and competition among the supply chain participants and focuses on capturing the dynamics by using agent-based modeling. An agent-based model has been developed based on the decision-making rules of moviegoers and theaters. Transitional probabilities and a multinominal logit model have been applied to moviegoers' decision-making process. Results of the Chi-square test of market share among the movies released in 2000 show that the research model can explain supply chain dynamics. After validating the model, research propositions are suggested by conducting a scenario analysis in perspective of market size and product diversity, as well as theater performance. This research can be used to forecast the performance of a movie based on pre-release information.
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