Optimal behaviour towards suppliers in automotive industry

Abstract

Decision-making is intrinsic to many organizations and individuals who utilize methods to assess the impact on the company, themselves, and the environment. Decisions can vary considerably depending on the level of certainty or uncertainty the decision-maker encounters. Also, the framework of the decisions may change over time, so that conditions decided today may be decidedly different in the future. This variation over time shows that decision making is dynamic and not static. Using an actual example from the automotive industry, we examine how changes in cost management can be influenced before and after a supplier selection. Tools are presented that show how to avoid costs and then how to prioritize using the tools before and after a supplier selection. The goal of this dissertation is to understand the behavior of automotive companies when negotiating new contracts with suppliers and then to analyze whether the timing of decisions affects the overall cost, concluding with optimizing the negotiation strategy and negotiation process. In this example, the framework conditions change over time, and the decisions made change depending on which phase the decision-maker is in. The components change considerably from a supplier selection through to the start of production and dealing with these change costs presents a big problem for the car manufacturers. The changes occur after the nomination and then have to be renegotiated at that time. The key moment is the signing of the contract when the position of power shifts from the car manufacturers to the suppliers. For this purpose, a survey was carried out at an automobile manufacturer, which, in addition to macroeconomic uncertainties, also serves as motivation to present the results in this doctoral thesis. In this thesis, a decision model under various conditions of uncertainty and for both pre- and post-contracting situations with suppliers is developed. Specifically, the Fuzzy-AHP, FuzzyPROMETHE and SMAA-AHP methods were used. The results are thoroughly discussed and compared with each other.