Optimierung der Beschaffungsstrategien durch Netzwerkanalyse am Beispiel eines Landmaschinenherstellers

Abstract

The increasing volatility of global markets confronts companies with challenges in the design and management of their supply chains. Geopolitical conflicts, natural disasters or infrastructural bottlenecks have an impact on the stability of internationally interconnected value chain networks. The ability to counter these uncertainties is increasingly becoming a success factor for companies. The main problem in overcoming such challenges is the lack of transparency regarding the company's own supply chain structure. For most companies, upstream supply tiers remain largely hidden. These information gaps make it difficult to identify potential weaknesses in the network at an early stage. The aim of this thesis is to investigate the extent to which network theory methods can help to identify critical nodes in the supply network and derive procurement decisions to increase supply security. This thesis is divided into a theoretical and a practical part. Firstly, the term value network is defined and its meaning is presented. The components of a network are explained, the history of value chain network management is presented and the procurement of resources within the network is discussed. Furthermore, reasons for the increasing complexity and ways to reduce it are listed, and approaches to measuring such networks using social network analysis are explained. The support of value creation networks with digital technologies to reduce complexity and increase efficiency is also explored. The network of the agricultural machinery manufacturer John Deere is then analyzed. In addition to literature research, the methodology includes mapping John Deere's value chain network, conducting a network analysis to evaluate the network and an expert interview to validate the results. Supply chain mapping makes it possible to visualize value chain networks and make connections and dependencies across several supply stages visible. Key figures such as betweenness and eigenvector centrality can be used to identify “hidden” key players whose disruption can have far-reaching consequences for the entire network, even if there is no direct connection to the focal company. The network analysis can be used to supplement the procurement strategy with risk-based criteria. The analysis also shows which suppliers are positioned independently of each other in the network and are therefore suitable for a geographically diversified sourcing strategy. Findings from an expert interview with a purchasing manager of an agricultural machinery manufacturer confirm the relevance of transparency, data access and digital tools.

Date of Award	2025
Original language	German (Austria)
Supervisor	Günther Gfrerrer (Supervisor)