Chair of Logistics and Quantitative Methods

Konstantin Kloos Conferred Doctorate


Konstantin Kloos, researcher at the Chair of Logistics and Quantitative Methods, successfully completed his doctoral thesis project. On December 15, 2020, he defended his thesis “Allocation Planning in Sales Hierarchies”. Due to his outstanding innovative work, the board of examiners conferred the distinction “summa cum laude”.

In his paper-based dissertation, Konstantin examined how companies can allocate their available supplies in decentralized global sales hierarchies. His research, which addresses a topic that is highly relevant for companies from different industries, encompasses both methodical contributions, such as novel mathematical solutions and algorithms, and conceptual findings, e.g., on the role of customer heterogeneity and the design of service-level contracts.

Konstantin’s work has already been published in leading international journals, such as OR Spectrum and the European Journal of Operational Research.

Abstract of the Dissertation:

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.