This dissertation studies fundamental problems that arise during the interaction and collaboration processes between supply chain partners. With focuses on procurement and retailing environments, we utilize both analytical and experimental methods to offer decision support toolkits to the decision makers. In Chapter 2, we study a re-sourcing setting in which a qualified supplier (the incumbent) and multiple suppliers who have not yet been qualified (the entrants) compete in an open-bid descending auction for a single-supplier contract. Conventionally, the buyer would screen entrants before running an auction, i.e., the pre-qualification strategy (PRE). We explore an alternative approach called post-qualification strategy (POST), in which the buyer first runs an auction and then conducts qualification screenings based on the suppliers’ auction bids. We find that using the cheaper option between PRE and POST not only provides significant cost-savings over the conventional PRE-only approach but also captures the majority of the benefit an optimal mechanism can offer over PRE. In Chapter 3, we consider a supply base rationalization process, where the supply base includes both qualified suppliers and potential suppliers whose qualification statuses are unknown. Before conducting a procurement auction that includes either only qualified suppliers or both qualified and all remaining potential suppliers, the buyer sequentially decides whether or not to screen another potential supplier. We characterize the structural properties of the optimal stopping policies for a general class of auction formats and test our analytical results on Amazon Mechanical Turk using human subjects. The experimental results show that the differences between treatments are qualitatively consistent with our theorems, but the average number of qualified suppliers is less extreme than the theoretical predictions. In Chapter 4, we explore a reward-based crowdfunding campaign in which backers arrive following a non-homogeneous Poisson process. We characterize the optimal pricing strategies for different scenarios and summarize situations that no pricing strategy could achieve the campaign target. We also offer a searching algorithm that guarantees to find the optimal price or report no solution.