Abstract
Besides product quality and costs, the logistics performance is increasingly focused on supplier development activities in the automotive industry. This is because inbound logistics networks in the automotive industry are very large and many process disruptions occur. These disruptions lead to additional handling efforts and should be avoided. Existing approaches of supplier development concentrate on the development of single suppliers. Interdependencies between suppliers are not considered. However, especially in the inbound logistics there are network effects. For instance, a delay at one supplier affects the timeliness of all other suppliers on the same route. Therefore, it could be beneficial to develop a supplier with a relatively small importance for the automotive manufacturer (OEM) but with strong impact on the other suppliers. Accordingly, we introduce an approach that assigns improvement measures to suppliers, taking into account the interdependencies in the automotive inbound logistics. We introduce a two-stage approach to evaluate the effect of improvement measures in the first step and to assign these measures to suppliers optimally under the OEM’s budget constraints in the second step, using Monte Carlo Simulation and a knapsack model. A first numerical example shows great potential compared to an approach with a state-of-the-art decision rule for supplier development.
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