Discrete Choice-based Equilibrium Modeling of Supply Chain Network with Conflicting Objectives and Demand Uncertainty
This PhD thesis discusses several equilibrium problems in supply chain network integration and specifically concentrates on the importance of collaboration under conflicting objective decision-making and uncertainty management in a supply chain network. In particular, discrete choice models are introduced into supply chain equilibrium models to bridge the conflicting objective decision-making in supply chains and customer preference. Furthermore, numerical examples are provided for model illustration, managerial insights, and algorithm performance. Finally, it attempts to explore the tradeoffs between the operation costs, service level, and time issues in a supply chain, considering customer preference and demand uncertainty. Two conventional assumptions used in both the supply chain network equilibrium model and the newsvendor model are generalized and relaxed in order to obtain more general solutions and methods. First, this PhD thesis adopts Sheffi’s equilibrium condition assumption rather than Wardrop’s network equilibrium condition assumption. Discrete choice models are introduced into supply chain equilibrium models. A probabilistic fashion is used to describe customer choice behavior, because all factors affecting customer choice behavior cannot be observed completely. It assumes equilibrium will be reached when no customer believes that his utility can be improved by unilaterally changing products (or services) provided by supply chains. This assumption is not easy to use in practice, except it can be characterized and formulated as equilibrium conditions mathematically. Next, the equilibrium conditions are formulated as multinomial logit- and newsvendor model-based variational inequalities. Second, the assumption in the newsvendor model that unmet demand is lost implies that customers are stockout neutral. This study assumes the customers are stockout aversion. This work generalizes the implied assumption in the newsvendor model and introduces it into the supply chain equilibrium model. This PhD thesis has several contributions to the supply chain network integration with a focus on the collaboration under conflicting objective decision-making and uncertainty management in a supply chain network. First, discrete choice models are incorporated into supply chain equilibrium models to bridge the conflicting objective decision-making in supply chains and customer preference. It brings several technical problems. A variety of corollaries, theorems, and propositions are provided to illustrate the models and problems. Hence, the model can optimize supply chain profits without multi-objective conversion at the firm level. Second, heterogeneous customers’ discrete choice behaviors are considered in the model. Most existing supply chain network equilibrium models are capable of providing equilibrium solutions in a supply chain network, only under the assumption that customers are homogeneous. This assumption can be extended to heterogeneous customers by using a supply chain network economic or equilibrium models integrated with the multinomial logit model and data at the level of the customer individual. Third, this work assumes that customers are stockout aversion and introduce the newsvendor model to solve the issue that uncertain demand depends on both price and service level in a supply chain network for joint products. The newsvendor model-based variational inequality problems are given to formulate the equilibrium conditions.
supply chain network, equilibrium model, discrete choice model
Ma, J. (2021). Discrete Choice-based Equilibrium Modeling of Supply Chain Network with Conflicting Objectives and Demand Uncertainty (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.