Computational and Experimental Market Design

This dissertation contributes to the literature on the market design of auctions. I use computational and experimental techniques to make two types of contributions to the literature. First, I provide a program that implements a state-of-the-art algorithm for solving multi-unit auctions with asymmetric bidders. This methodological contribution can be used by other economists to solve a variety of auction problems not considered in this dissertation. Second, I undertake the study of one auction environment in particular, utilizing my program to generate hypotheses when bidders participate in a particular sealed-bid, asymmetric multi-unit auction. These hypotheses are then tested in an experimental setting

Optimal Global Supply Chain and Warehouse Planning under Uncertainty

A manufacturing company\u27s inbound supply chain consists of various processes such as procurement, consolidation, and warehousing. Each of these processes is the focus of a different chapter in this dissertation. The manufacturer depends on its suppliers to provide the raw materials and parts required to manufacture a finished product. These suppliers can be located locally or overseas with respect to the manufacturer\u27s geographic location. The ordering and transportation lead times are shorter if the supplier is located locally. Just In Time (JIT) or Just In Sequence (JIS) inventory management methods could be practiced by the manufacturer to procure the raw materials and parts from the local supplier and control the inventory levels in the warehouse. In contrast, the lead time for the orders placed with an overseas supplier is usually long because sea-freight is often used as a primary mode of transportation. Therefore, the orders for the raw materials and parts (henceforth, we collectively refer to raw material and part by part) procured from overseas suppliers are usually placed using forecasted order quantities. In Chapter 2, we study the procurement process to reduce the overall expected cost and determine the optimal order quantities as well as the mode of transportation for procurement under forecast and inventory uncertainty. We formulate a two-stage stochastic integer programming model and solve it using the progressive hedging algorithm, a scenario-based decomposition method. Generally, the orders are placed with overseas suppliers using weekly or monthly forecasted demands, and the ordered part is delivered using sea-containers since sea-freight is the primary mode of transportation. However, the end manufacturing warehouse is usually designed to hold around one to two days of parts. To replenish the inventory levels, the manufacturer considered in this research unloads the sea-container that contains the part that needs to be restocked entirely. This may cause over-utilization of the manufacturer\u27s warehouse if an entire week\u27s supply of part is consolidated into a single sea-container. This problem is further aggravated if the manufacturer procures hundreds of different parts from overseas suppliers and stores them in its warehouse. In Chapter 3, we study the time-series forecasting models that help predict the manufacturing company\u27s daily demand quantities for parts with different characteristics. The manufacturer can use these forecasted daily demand quantities to consolidate the sea-containers instead of the weekly forecasted demand. In most cases, there is some discrepancy between the predicted and actual demands for parts, due to which the manufacturer can either have excess inventory or shortages. While excess inventory leads to higher inventory holding costs and warehouse utilization, shortages can result in substantially undesirable consequences, such as the total shutdown of production lines. Therefore, to avoid shortages, the manufacturer maintains predetermined safety stock levels of parts with the suppliers to fulfill the demands arising from shortages. We formulate a chance-constraint optimization model and solve it using the sample approximation approach to determine the daily safety stock levels at the supplier warehouse under forecast error uncertainty. Once the orders are placed with the local and overseas suppliers, they are consolidated into trailers (for local suppliers) and sea-containers (for overseas suppliers). The consolidated trailers and sea-containers are then delivered to the manufacturing plant, where they are stored in the yard until they are called upon for unloading. A detention penalty is incurred on a daily basis for holding a trailer or sea-container. Consolidating orders from different suppliers helps maximize trailer and sea-container space utilization and reduce transportation costs. Therefore, every sea-container and trailer potentially holds a mixture of parts. When a manufacturer needs to replenish the stocks of a given part, the entire sea-container or trailer that contains the required part is unloaded. Thus, some parts that are not imminently needed for production are also unloaded and stored inside the manufacturing warehouse along with the required parts. In Chapter 4, we study a multi-objective optimization model to determine the sea-containers and trailers to be unloaded on a given day to replenish stock levels such that the detention penalties and the manufacturing warehouse utilization are minimized. Once a sea-container or trailer is selected to replenish the warehouse inventory levels, its contents (i.e., pallets of parts) must be unloaded by the forklift operator and then processed by workers to update the stock levels and break down the pallets if needed. Finally, the unloaded and processed part is stored in the warehouse bins or shelves. In Chapter 5, we study the problem of determining the optimal team formation such that the total expected time required to unload, process, and store all the parts contained in the sea-containers and trailers selected for unloading on a given day is minimized

Foundational Economic Theories for Political-Scientific Inter-Branch Studies

Economic theories are increasingly popular in political science, and in particular in research on the relations between the legislative, the executive, and the judicial branches of government. Among these theories, principal-agent (´PA´) and transaction cost economics (´TCE´) feature particularly high in our research agenda. Yet, pushed by the view that "the content of ´science´ is primarily the methods and rules" (King et al. 1994: 9), and working with limited resources, political scientists have tended to neglect careful theorizing. PA and TCE are taken off-the-shelf without much prior scrutiny, and past conceptual mistakes are perpetuated. This paper aims at introducing and explaining the real PA, positive agency, TCE, and incomplete contracts theories for the purposes of political analysis. In a companion paper, I show the serious mistakes perpetuated by political scientists, and I argue that, faced with a choice between those four economic theories, we should place our bets on a revised version of TCE.Theory of delegation, political science, principal-agent models, transaction costs economics

Competitive impact of scoring design in public sector invitations to tender

Public procurement represents a field where significant public funds are expended to provide services to the general populace. Improving public procurement methods has been identified as a potential means of reducing public spending. While public procurement has long been in the interest of academics, empirical research literature about tender scoring practices remains scarce, particularly in terms of its competitive impact. This thesis examines scoring design and its relation to competition in public procurement invitations to tender (ITT). The study was conducted as a sequential mixed methods case study of HUS medical devices and supplies (CPV-33) procurement. The specific research questions posed are: 1) What kind of scoring design and -criteria are used in Finnish healthcare ITTs, and 2) How are scoring criteria associated with competition in such ITTs? These questions are addressed in two sequential research stages. The first stage of research is an exploratory content analysis of HUS ITT documents. The content analysis aims to collect, categorize, and analyze the scoring criteria in single lot sealed bid auction ITTs from 2019-2022. This thesis discovers that the scoring has been conducted using either the Lowest Price or the Economically Most Advantageous Tender (EMAT) scoring methods. In the case of EMAT, the weight of price criteria has ranged from 40% to 100%, with an average of 3.7 quality criteria per ITT. The first stage results also indicate potential instances of human bias in the design of scoring rules. The second research phase begins by testing the difference in the number of bidders between Lowest Price and EMAT scoring. It appears that EMAT scoring tends to correlate with fewer bidders. This phase then presents a regression analysis of scoring criteria data gathered in the first research phase. The outcome variable in this analysis is the number of bidders, which corresponds to the number of bids, as the final sample considers only single lot ITTs. The results of the regression analysis are somewhat limited, largely due to the restricted data sample. The empirical findings of this thesis suggest that real-world scoring practices in public procurement have potential for improvement. Theoretical perspectives on different scoring practices diverge, warranting further research to create a more comprehensive understanding of the actual implications of various scoring details on competition, as well as other procurement outcome measures