Self-induced learning vs. project-based supplier development for production ramp-up with two supply options

Abstract

Due to the important role suppliers play in the generation of customer value today, supplier development has attracted the attention of many companies in recent years. One challenge companies wishing to engage in supplier development face is to select both the right suppliers for supplier development as well as adequate supplier development measures and to align supplier development initiatives with the company's remaining sourcing activities. This problem becomes even more pressing during production ramp-up, where an increasing customer demand forces companies to expand the capacities of their supplier base as well. Albeit research on supplier development has enjoyed an increasing popularity in recent years, only a few mathematical models exist to date that support companies in making optimal supplier development decisions. The paper at hand contributes to closing this research gap by developing a decision support model that assists companies in selecting suppliers, in scheduling supplier development projects and in assigning order quantities to selected suppliers. In developing the proposed model, the paper accounts for the fact that suppliers often improve their performance also in the absence of supplier development, and thus considers both self-induced performance improvements at the suppliers as well as performance improvements induced by supplier development projects. The results of a numerical experiment imply that the supplier selection, order allocation and supplier development decisions are subject to complex interactions. The model proposed in this paper supports companies in fitting their supplier development activities to the requirements of the sourcing scenario they face with the intention to maximize profit.