Decision Behavior In Capacity Allocation Games

The essence of the decision making in capacity allocation games belongs to aclass of gaming problem, for which theoretical studies based on the Nash theory hasbeen developed. However, due to the assumptions on the human decision behavior, thetheoretical results are limited. Specifically, theoretical model simplifies the human de-cision maker as a perfect optimizer which has perfect power of information acquisitionand processing. Due to the gaps between these fundamental assumptions and the prac-tical managerial decisions, theoretical findings are restricted when applying into thepractical supply chain management. For these reasons, this thesis introduces studies ofbehavioral decisions into capacity allocation games. By focusing on the retailer’s de-cision behavior, both theoretical and experimental methods are applied to develop thebehavioral decision research. This thesis investigates two modes of capacity allocationgames namely the complete information and incomplete information of the demand onthe game, which are arranged respecting to two kinds of allocation rules, namely theproportional and the smallest-order-first on the allocation rule. Based on experimentaldata, the behavioral regularities are refined, and the corresponding behavioral modelsare established to characterize the key factors that influence the retailers’ decision be-havior. Comparisons between the behavioral models and the standard models facilitatemore understanding about the limited representation capabilities in the standard theory,and further reveal the underlying mechanisms of these limitations.In the complete information capacity allocation games, experimental data revealsystematic deviations between the subject’s ordering behavior and the standard Nashequilibrium, also learning efects as the subjects repeatedly play the game. Throughstructural analyses of the data, the influences of diferent allocation rules and diferentoperational costs on the subject’s ordering decision and the supply chain performanceare refined. Through quantitative analyses, a novel behavioral decision model are pro-posed based on the Quantal Response equilibrium, from which bounded rationality in the strategic interactions and learning efects in the repeatedly games are captured.Finally, the predictive power of the behavioral model is validated.In the incomplete information capacity allocation games, not only bounded ratio-nality in subjects’ strategic interactions but also diferentiated mental perceptions ofthe operational costs exist in subjects’ decision behavior. Based on the mental account-ing theory and the quantal response equilibrium, the corresponding behavioral modelis established, with which structural estimates reveal that the regularities of subjects’diferentiated mental accounts on the underage and overage costs vary with diferentoperational-cost conditions and diferent decision rounds. Finally, supply chain perfor-mance is analyzed and the predictive power of the behavioral model is validated.The comparisons of the two allocation rules in the two typical games demonstratethe properties and several advantages of the smallest-order-first rule, which have yetbeen rarely studied: first, the ordering decisions of subjects approximate to the stan-dard Nash theory more than those of the proportional allocation rule; second, subjects’decisions are robust with respect to diferent operational costs; finally, the supply chainperforms better with the smallest-order-first rule. The above properties illustrate thatsmallest-order-first could be a valuable candidate for applications in certain practices.This thesis establishes a framework of studying the behavioral decisions in capac-ity allocation games, proposes and establishes an efective behavioral decision model,which provides foundation for further supply chain optimization and the mechanismdesign in future.