Supply Chain Engineering
Final Report Abstract
Supply chain management analyzes the coordination of actions across companies. Traditional supply chain models assume expected profit-maximizing decision makers and analyze coordination mechanisms that optimize decision making under this assumption. However, recent studies using laboratory experiments suggest that actual decisions deviate from predictions of those traditional models. During the first phase of the project, we analyzed one of the main coordination mechanisms, supply contracts, in detail. We studied the role of cognitive limitations and decision biases, such as anchoring, and motivations such as risk- and loss aversion in individual decision making and social preferences, such as fairness and trust, in social contexts for supply chain models. In our research on service level contracts, for instance, we studied the anchoring bias, and in our research on wholesale price contracts and forecast sharing we studied social preferences and the role of fairness concerns on decision making. The results of the first funding period have provided us with a solid understanding of the decision biases and preferences that are relevant in supply chain management. In the second phase, we used these insights to engineer actual contracts and incentive systems and we analyzed how negotiations of contracts should be structured to improve overall efficiency. In Subproject A.1 we conducted a randomized field experiment with 66 store managers of a major German retailer and analyzed how information should be pre-processed to reduce decision biases. We found that the store managers were not able to perform better than the optimal model which means that local information that is not covered by the algorithm did not outweigh decision biases. In Subproject A.2 we investigated the effect of sales incentive schemes on forecasting in the field. In cooperation with the corporate supply chain department at a Western European pharmaceutical company, we introduced a bonus for forecast accuracy into the incentive system of Sales. Even though the overall financial impact on sales people was relatively small we found significant improvements in forecasting performance as predicted by Scheele, Thonemann, and Sikker (2017). In Subproject B.1. we investigated contract negotiations in supply chains. We observed that bargaining protocols affect fairness and efficiency in supply chains. Overall, negotiations lead to more fairness and efficiency than “take it or leave it” offers. In Subproject B.2. we analyzed how bargaining protocols influence behavior in settings with incomplete contracts. One of the major findings was that transfer prices should be negotiated before orders have been placed, to increase the likelihood of successful negotiations. In Subproject C.1 we analyzed the impact of a dummy evaluation scale on employees’ performance. We find that the kindness of an evaluation scale matters rather than the kindness of an individual evaluation. Most interestingly, we find that commonly used evaluation scales are in accordance with our findings. In Subproject C.2 we studied the impact of naïve diversification when employing sub-budgets on project selection. We find that a) naïve prediction influences project selection, and b) designing strategic bucket policies (even without enforcing compliance) may be an instrument for executives to influence a company’s project portfolio.
Publications
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(2016). Reference points in revenue sharing contracts – How to design optimal supply chain contracts. European Journal of Operational Research, 249(3), 1033-1049
Becker-Peth, M., and U. W. Thonemann
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(2017). A note on the risk-aversion of informed newsvendors. Journal of the Operational Research Society
Becker-Peth, M., U. W. Thonemann, and T. Gully
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(2017). Equivalent inventory metrics: A behavioral perspective. Manufacturing & Service Operations Management, 19(3), 472-488
Stangl, T., and U. W. Thonemann
