Supply chain coordination to optimize manufacturer's capacity procurement decisions through a new commitment-based model with penalty and revenue-sharing

M Shafiq, MM Savino - International Journal of Production Economics, 2019 - Elsevier
M Shafiq, MM Savino
International Journal of Production Economics, 2019Elsevier
In this study a commitment-based revenue-sharing and penalty model is proposed to
coordinate a supply chain with one manufacturer and a retailer facing stochastic demand.
Because of short time to respond to demand and long capacity procurement lead time, the
manufacturer needs to procure capacity in advance. As capacity procurement involves
monetary investment, it may lead to under-estimation if the risk has to be solely borne by the
manufacturer. In contrast, the approach developed within this study induces the retailer to …
Abstract
In this study a commitment-based revenue-sharing and penalty model is proposed to coordinate a supply chain with one manufacturer and a retailer facing stochastic demand. Because of short time to respond to demand and long capacity procurement lead time, the manufacturer needs to procure capacity in advance. As capacity procurement involves monetary investment, it may lead to under-estimation if the risk has to be solely borne by the manufacturer. In contrast, the approach developed within this study induces the retailer to commit not less than the expected demand. At the same time, under-purchase penalty is also introduced to avoid over-commitment. Furthermore, as regards to the existing contract approaches, the retailer is provided of a certain flexibility in terms of under-purchase penalty to avoid transferring the whole demand uncertainty risk on the retailer. On the other hand, the manufacturer is also motivated to produce more through reward in terms of higher revenue percentage for the products demanded more than the commitment. The proposed model is compared with those models based on prevailing revenue-sharing with penalty contracts, in terms of commitment and capacity procurement decisions. Numerical experiments and sensitivity analysis are presented to demonstrate the usefulness of the model and the relative managerial insights.
Elsevier
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