Seller’s Optimal Credit Period and Delivery Number in EPQ Models when Production Costs have the Learningby- Experience Effects

Abstract

實務上賣家經常給買家固定的信用交易期間，以無息付款來刺激銷售量和市場的競爭力。此外，從經驗學習效應來看，銷售量愈大則生產量也愈大，而生產量增加則學習效應高，促使每單位生產成本跟著降低。因此，從賣家觀點，提供信用交易，不但增加銷售量，也帶來具有學習效應的單位生產成本降低。另一方面，給予信用交易不只增加信用期間的利息損失，還有增加違約風險率。現有文獻鮮少注意到這個事實。本研究配合信用交易對銷售和學習生產成本有正面影響，但對利息損失和違約風險卻有負面衝擊，建立生產系統中賣家最佳的信用交易期間和交貨次數模型來達到利潤最大化，這是混合整數規劃問題，本研究透過電腦軟體去解決。為簡化，論文中提出一優化啟發演算法，最後，用敏感度分析顯示一些觀點洞見和可顯著增加賣家的信用期間和總利潤的經驗學習效應。

To stimulate sales and remain competitive, the seller usually offers the buyer a credit period to settle the purchase amount with no interest charges. In addition, the more quantity produced and sold, the cheaper the unit production cost due to the learning-by-experience effect. Therefore, from the seller`s perspective, offering trade credit increases sales volume, resulting in lower unit production cost. On the other hand, granting trade credit increases not only interest loss during credit period but also default risk. However, relatively little attention has been paid to the fact that trade credit increases sales volume and reduces the production cost due to the learning-by-experience effect. In this paper, we develop the seller`s optimal credit period and number of deliveries in an Economic Production Quantity model in which trade credit has positive impacts on sales and learning production cost while it has negative impacts on interest loss and default risk. We then formulate the problem as a mixed integer programming problem, and solve it by computer software. For simplicity, we propose a remarkably good heuristic algorithm. Finally, we use sensitivity analysis to show several managerial insights, and that the learning-by-experience effect can significantly increase the seller`s credit period and total profit.