UTFacultiesBMSEventsPhD Defence Ines Schulze Horn

PhD Defence Ines Schulze Horn

mechanism design theory in buyer-supllier negotiations - designing incentive systems to achieve price reduction

Ines Schulze Horn is a PhD student in the research group Technology Management & Supply. Her supervisor is Prof.Dr.habil. H. Schiele from the Faculty of Behavioural, Management and Social Sciences.

Mechanism design theory constitutes a branch of game theory and proposes that economic incentives can be developed and implemented to achieve desired objectives. In terms of buyer-supplier negotiations, this theory represents the underlying rationale for the idea that purchasers can develop individualized negotiation rules adapted to the specific sourcing situation. This approach aims at increasing competition between suppliers in industrial sourcing situations, ultimately leading to reduced purchasing prices. In recent years, it could be observed that many buying organizations extended their traditional negotiation repertoire by conducting mechanism design-based negotiations. Yet, scientific literature on this negotiation approach remained scarce and is mainly focussed on procurement auctions. Therefore, this research centers around the question how buying organizations can benefit from the application of mechanism design theory in negotiations. To answer this research question, five studies have been conducted. The first study sets off by providing an introduction into game theory and mechanism design theory and explains how the latter can be applied in negotiations. Building on these findings, the second study provides a decision model for identifying products and services qualified for this negotiation method. The third study sheds further light on the mechanisms which can be used by buying organizations to incentivize suppliers to reveal their reservation prices. Due to the complexity of this negotiation approach, the fourth study compares the effectiveness of individualized and standardized negotiation rules. The results highlight that rules which are optimally adapted to the negotiation context apparently lead to higher price reductions. Hence, the final study illustrates application opportunities of artificial intelligence and thereby somewhat facilitates the implementation of mechanism design-based negotiations for buying organizations.