@phdthesis{Siller2023,
  author    = {Siller, Benjamin},
  title     = {Influence of Lead Time and Emission Policies on the Design of Supply Chains - Insights from Supply Chain Design Models},
  doi       = {10.25972/OPUS-29671},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-296713},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2023},
  abstract  = {Companies are expected to act as international players and to use their capabilities to provide customized products and services quickly and efficiently. Today, consumers expect their requirements to be met within a short time and at a favorable price. Order-to-delivery lead time has steadily gained in importance for consumers. Furthermore, governments can use various emissions policies to force companies and customers to reduce their greenhouse gas emissions. This thesis investigates the influence of order-to-delivery lead time and different emission policies on the design of a supply chain. Within this work different supply chain design models are developed to examine these different influences. The first model incorporates lead times and total costs, and various emission policies are implemented to illustrate the trade-off between the different measures. The second model reflects the influence of order-to-delivery lead time sensitive consumers, and different emission policies are implemented to study their impacts. The analysis shows that the share of order-to-delivery lead time sensitive consumers has a significant impact on the design of a supply chain. Demand uncertainty and uncertainty in the design of different emission policies are investigated by developing an appropriate robust mathematical optimization model. Results show that especially uncertainties on the design of an emission policy can significantly impact the total cost of a supply chain. The effects of differently designed emission policies in various countries are investigated in the fourth model. The analyses highlight that both lead times and emission policies can strongly influence companies' offshoring and nearshoring strategies.},
  subject      = {Supply Chain Management},
  language  = {en}
}
@phdthesis{Lauton2021,
  author    = {Lauton, Felix},
  title     = {Three Essays on the Procurement of Essential Medicines in Developing Countries},
  doi       = {10.25972/OPUS-22063},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-220631},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2021},
  abstract  = {The first problem is that of the optimal volume allocation in procurement. The choice of this problem was motivated by a study whose objective was to support decision-making at two procurement organizations for the procurement of Depot Medroxyprogesterone Acetate (DMPA), an injectable contraceptive. At the time of this study, only one supplier that had undergone the costly and lengthy process of WHO pre-qualification was available to these organizations. However, a new entrant supplier was expected to receive WHO qualification within the next year, thus becoming a viable second source for DMPA procurement. When deciding how to allocate the procurement volume between the two suppliers, the buyers had to consider the impact on price as well as risk. Higher allocations to one supplier yield lower prices but expose a buyer to higher supply risks, while an even allocation will result in lower supply risk but also reduce competitive pressure, resulting in higher prices. Our research investigates this single- versus dual-sourcing problem and quantifies in one model the impact of the procurement volume on competition and risk. To support decision-makers, we develop a mathematical framework that accounts for the characteristics of donor-funded global health markets and models the effects of an entrant on purchasing costs and supply risks. Our in-depth analysis provides insights into how the optimal allocation decision is affected by various parameters and explores the trade-off between competition and supply risk. For example, we find that, even if the entrant supplier introduces longer leads times and a higher default risk, the buyer still benefits from dual sourcing. However, these risk-diversification benefits depend heavily on the entrant's in-country registration: If the buyer can ship the entrant's product to only a selected number of countries, the buyer does not benefit from dual sourcing as much as it would if entrant's product could be shipped to all supplied countries. We show that the buyer should be interested in qualifying the entrant's product in countries with high demand first. In the second problem we explore a new tendering mechanism called the postponement tender, which can be useful when buyers in the global health industry want to contract new generics suppliers with uncertain product quality. The mechanism allows a buyer to postpone part of the procurement volume's allocation so the buyer can learn about the unknown quality before allocating the remaining volume to the best supplier in terms of both price and quality. We develop a mathematical model to capture the decision-maker's trade-offs in setting the right split between the initial volume and the postponed volume. Our analysis shows that a buyer can benefit from this mechanism more than it can from a single-sourcing format, as it can decrease the risk of receiving poor quality (in terms of product quality and logistics performance) and even increase competitive pressure between the suppliers, thereby lowering the purchasing costs. By considering market parameters like the buyer's size, the suppliers' value (difference between quality and cost), quality uncertainty, and minimum order volumes, we derive optimal sourcing strategies for various market structures and explore how competition is affected by the buyer's learning about the suppliers' quality through the initial volume. The third problem considers the repeated procurement problem of pharmacies in Kenya that have multi-product inventories. Coordinating orders allows pharmacies to achieve lower procurement prices by using the quantity discounts manufacturers offer and sharing fixed ordering costs, such as logistics costs. However, coordinating and optimizing orders for multiple products is complex and costly. To solve the coordinated procurement problem, also known as the Joint Replenishment Problem (JRP) with quantity discounts, a novel, data-driven inventory policy using sample-average approximation is proposed. The inventory policy is developed based on renewal theory and is evaluated using real-world sales data from Kenyan pharmacies. Multiple benchmarks are used to evaluate the performance of the approach. First, it is compared to the theoretically optimal policy --- that is, a dynamic-programming policy --- in the single-product setting without quantity discounts to show that the proposed policy results in comparable inventory costs. Second, the policy is evaluated for the original multi-product setting with quantity discounts and compared to ex-post optimal costs. The evaluation shows that the policy's performance in the multi-product setting is similar to its performance in the single-product setting (with respect to ex-post optimal costs), suggesting that the proposed policy offers a promising, data-driven solution to these types of multi-product inventory problems.},
  subject      = {Entwicklungsl{\"a}nder},
  language  = {en}
}
@phdthesis{Kloos2020,
  author    = {Kloos, Konstantin},
  title     = {Allocation Planning in Sales Hierarchies},
  doi       = {10.25972/OPUS-19373},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193734},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2020},
  abstract  = {Allocation planning describes the process of allocating scarce supply to individual customers in order to prioritize demands from more important customers, i.e. because they request a higher service-level target. A common assumption across publications is that allocation planning is performed by a single planner with the ability to decide on the allocations to all customers simultaneously. In many companies, however, there does not exist such a central planner and, instead, allocation planning is a decentral and iterative process aligned with the company's multi-level hierarchical sales organization. This thesis provides a rigorous analytical and numerical analysis of allocation planning in such hierarchical settings. It studies allocation methods currently used in practice and shows that these approaches typically lead to suboptimal allocations associated with significant performance losses. Therefore, this thesis provides multiple new allocation approaches which show a much higher performance, but still are simple enough to lend themselves to practical application. The findings in this thesis can guide decision makers when to choose which allocation approach and what factors are decisive for their performance. In general, our research suggests that with a suitable hierarchical allocation approach, decision makers can expect a similar performance as under centralized planning.},
  subject      = {Supply Chain Management},
  language  = {en}
}
@phdthesis{Altmann2014,
  author    = {Altmann, Michael},
  title     = {Environmentally conscious supply chain design},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-107760},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2014},
  abstract  = {Sustainability has become a critical topic in all areas of supply chain management. As discussed earlier, drivers for this development can be identified as both internal and external phenomena. Since customers are one of the key stakeholders in supply chain management, special attention is paid to the impact of costumers´ behavior on sustainable supply chain design decisions. In this context, two main research questions were analyzed: 1.What is the appropriate way to design a supply chain according to environmentally-oriented requirements of customers? 2.What is the impact of customer´s behavior regarding both usage and return of products on supply chain design decisions in an environmentally conscious closed-loop supply chain environment? Therefore, three different optimization models with various main aspects are developed. To illustrate how the presented models can be applied in practical problem cases, guidelines for implementing an environmentally supply chain design project are presented.},
  subject      = {Supply Chain Management},
  language  = {en}
}