Optimization of Supplier Development under Market Dynamics

Abstract

Over the last decades, supplier development has become an increasingly important concept to remain competitive in today’s markets. Therefore, manufacturers invest resources in their suppliers to increase their abilities and, ultimately, to reduce their product prices. Thereby, most approaches found in the literature focus on long-term supplier development programs. Nevertheless, today’s volatile and dynamic markets require flexible approaches to deal with this complexity. We apply Model Predictive Control to optimize the number of supplier development projects in order to achieve flexibility while maintaining a certain level of security for all parties. Thereby, the article focusses on a multimanufacturer scenario, where two manufacturers aim to develop the same supplier. These manufacturers can establish different levels of horizontal collaboration. While previous results already show the benefits of applying this approach to a static scenario, this article extends this formulation by introducing market dynamics in the numerical simulations as well as into the optimization approach. Thus, the article proposes to derive regression models using real-world data. The article evaluates the effects of real-world market dynamics on two use cases: an automotive use case and a use case from the mobile phone sector. The results show that assuming market dynamics during the optimization leads to increased or at least close-to-equal revenues across the involved partners. The average increase ranges from approximately 1% to 5% depending on the type and magnitude of the dynamics. Thereby, the results differ depending on the selected collaboration scheme. While a full-cooperative collaboration scheme benefits the least from regarding dynamics in the optimization, it results in the highest overall revenue across all partners.

A Numerical Study on the Effects of Trust in Supplier Development

“…However, we could not identify research in the context of manufacturer/manufacturer relationships. Previous studies show that manufacturers can achieve considerable benefits from collaborating and, especially, from cooperating within their supplier development programs [1,2]. Nevertheless, these studies did not regard the effects of trust.…”

“…with T ∈ R Figure 1 shows the overall structure of the proposed approach to include the notion of trust in the optimization of supplier development programs. In this study, we adopted the Model Predictive Control (MPC) scheme applied in [1,2]. This scheme enables coping with highly dynamic systems where actors cannot anticipate the full extent of these dynamics, for instance the multi-OEM scenarios regarded in this article.…”

“…if the current scheme is simultaneous 5As a baseline for the optimization, this model applies the same cost function (Equation (6)) used in previous studies [1,2] and introduced by Proch et al [61] to optimize the revenue for each OEM:…”

“…Despite the close cooperation these programs require, OEMs need to continuously revise these programs, e.g., due to quickly changing market dynamics or simply because future investments might not yield the expected results. Previous studies showed that collaboration or even cooperation between multiple manufacturers provides extensive advantages concerning their respective supplier development programs [1,2].…”

“…Therefore, it first presents a broad literature review on trust factors in manufacturer-supplier relationships and transfers those which are applicable to the manufacturer-manufacturer setting regarded in this study. In fact, this study takes one step further than the authors of [1,2] by considering the effects of trust in collaborative supplier development investments. The primary objective of this article is to propose a generalized model to quantify trust in manufacturer-to-manufacturer relationships and, furthermore, to integrate trust into the optimization of supplier development programs.…”