An Econometric Analysis of Finished Goods Inventory in the U.S. Automotive Industry: Bayesian and Classical Approaches
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This dissertation examines the finished-goods inventory in the U.S. automobile industry using several econometric methods -- including OLS, the Bayesian approach, the variable mean response estimation, and the simultaneous equation system. The research starts with the classical economic order quantity (EOQ) model. The EOQ model is an important, well-known, and widely-taught inventory management model found in most Operations Management textbooks. The design of the classical EOQ model is based on several fundamental assumptions. The extension of the EOQ model has been doing by testing and adjusting the assumptions. The goal of this dissertation is to investigate inventory problems arising from violations of the rather unrealistic assumptions underlying the EOQ model, such as the constant demand. In this research, five models are developed and applied empirically to the U.S. automotive industry. The objectives of the models are to answer the following research questions: (1) We would like to test the EOQ model empirically under its assumptions. Can the EOQ model stay consistent within its specifications? (2) Should the demand in the EOQ model be random rather than constant? (3) If the demand is random, is demand stochastic and dynamic in terms of the coefficient of demand uncertainty when incorporated with the EOQ variables? (4) Is the demand endogenous rather than exogenous? If the demand is endogenous, are the demand and the order quantity in the EOQ model correlated and jointly determined? (5) Do the service rate effect and demand-stimulation effect exist simultaneously in U.S. auto dealerships? Overall, the empirical results demonstrate many avenues for considering new inventory policies to incorporate with the classical EOQ model. From the specifications, the proposed methodologies and models can provide inventory decision-makers with different managerial implications and strategic improvements. Finally, this research should contribute to the literature on the methodological and empirical fronts.