過往供應鏈考量需求不確定研究大多假設需求參數為已知，但在現實中多數情
形則未必符合參數已知假設，而未知參數與需求的隨機性會使供應鏈決策者難以
做出最佳決策。雖然決策者在決策前對於需求參數為未知，但仍可透過資訊獲取
來學習參數為何，而在決策的過程加入考量資訊獲取即稱之為需求學習。本研究
使用斯塔克爾柏格賽局(Stackelberg game)建立一個兩期的供應鏈模型，供應鏈成
員包含製造商與零售商，製造商負責生產產品以及決策批發價格販售給零售商，
零售商則依製造商給定的批發價格決定訂購量以滿足市場需求。在決策的過程中
加入考量需求學習來獲取資訊以降低需求不確定性，並且探討考量需求學習決策
具有的特性以及需求學習給決策帶來是否能帶來正面效益。從文獻中可得知單一
階層的情形下零售商考量學習會增加訂購量，但本研究透過數值範例發現不管是
製造商亦或者是零售商，兩者考量需求學習的決策並不一定具有固定特性，有可
能會出現上升、下降亦或是持平的狀況發生，此外透過數值範例也可得出考量學
習皆可有效提升決策者自身利潤，證實需求學習可為決策者帶來正面效益。

We investigate a supply chain management problem where the demand model is
unknown a priori, but can be learned through information acquisition. A two-period Stackelberg game is adopted for demand learning. In each period, a manufacturer sells a product to a retailer; the retailer then needs to determine an order quantity to maximize her profit based on the posted price determined by the manufacturer. In the inventory control literature, it has been shown that the retailer will set a higher inventory level to avoid shortage event, which is less favorable for demand learning. Motivated by this managerial insight, the goal of this paper is to study the structural results of the manufacturer’s optimal price decision. In our numerical experiments, we find that the manufacturer’s optimal decision will be less or more than the myopic price, which is the optimal decision of the single-period problem. Besides the decision affect, we also find using demand learning can increase revenue.

Agrawal, N., & Smith, S. A. (1996). Estimating negative binomial demand for retail
inventory management with unobservable lost sales. Naval Research Logistics, 43(6),839–861.

Aviv, Y., & Pazgal, A. (2005). A partially observed markov decision process for dynamic pricing. Management Science, 51(9), 1400–1416.

Azoury, K. S. (1985). Bayes solution to dynamic inventory models under unknown demand distribution. Management Science, 31(9), 1150–1160.

Bensoussan, A., & Sethi, S. P. (2009). A note on “the censored newsvendor and the
optimal acquisition of information”. Operations Research, 57(3), 791–794.

Cachon, G. P. (2003). Supply chain coordination with contracts. Handbooks in Operations Research and Management Science, 11, 227–339.

Cachon, G. P., & Lariviere, M. A. (2005). Supply chain coordination with revenue-sharing contracts: strengths and limitations. Management Science, 51(1), 30–44.

Chen, J. (2011). Returns with wholesale-price-discount contract in a newsvendor problem. International Journal of Production Economics, 130(1), 104–111.

Chen, X., Zhang, H., Zhang, M., & Chen, J. (2017). Optimal decisions in a retailer
stackelberg supply chain. International Journal of Production Economics, 187, 260–
270.

Chiu, C.-H., Choi, T.-M., & Tang, C. S. (2011). Price, rebate, and returns supply contracts for coordinating supply chains with price-dependent demands.Production and Operations Management, 20(1), 81–91.

Christopher, M. (1992). Logistics & supply chain management. Pearson UK.

Cooper, M. C., Lambert, D. M., & Pagh, J. D. (1997). Supply chain management: more
than a new name for logistics. The international Journal of Logistics Management,
8(1), 1–14.

Cope, E. (2007). Bayesian strategies for dynamic pricing in e-commerce. Naval Research Logistics, 54(3), 265–281.

Ding, X., Puterman, M. L., & Bisi, A. (2002). The censored newsvendor and the optimalacquisition of information. Operations Research, 50(3), 517–527.

Eeckhoudt, L., Gollier, C., & Schlesinger, H. (1995). The risk-averse (and prudent) newsboy. Management Science, 41(5), 786–794.

Ferguson, M., & Ketzenberg, M. E. (2006). Information sharing to improve retail product freshness of perishables. Production and Operations Management, 15(1), 57–73.

Jerath, K., Kim, S.-H., & Swinney, R. (2017). Product quality in a distribution channel
with inventory risk. Marketing Science, 36(5), 747–761.

Khouja, M. (1999). The single-period (news-vendor) problem: literature review and suggestions for future research. Omega, 27(5), 537–553.

Kouvelis, P., Chambers, C., & Wang, H. (2006). Supply chain management research andproduction and operations management: Review, trends, and opportunities. Productionand Operations Management, 15(3), 449–469.

Kraiselburd, S., Narayanan, V., & Raman, A. (2004). Contracting in a supply chain with stochastic demand and substitute products. Production and Operations Management,13(1), 46–62.

La Londe, B. J., & Masters, J. M. (1994). Emerging logistics strategies: blueprints for the next century. International Journal of Physical Distribution & Logistics Management.

Lariviere, M. A., & Porteus, E. L. (2001). Selling to the newsvendor: An analysis of
price-only contracts. Manufacturing & Service Operations Management, 3(4), 293–
305.

Lovejoy, W. S. (1990). Myopic policies for some inventory models with uncertain demand distributions. Management Science, 36(6), 724–738.

Lu, X., Song, J.-S., & Regan, A. (2007). Rebate, returns and price protection policies in channel coordination. IIE Transactions, 39(2), 111–124.

Lu, X., Song, J.-S., & Zhu, K. (2008). Analysis of perishable-inventory systems with
censored demand data. Operations Research, 56(4), 1034–1038.

Monczka, R. M., Handfield, R. B., Giunipero, L. C., & Patterson, J. L. (1998). Purchasing and supply chain management. Cengage Learning.

Nahmias, S. (1994). Demand estimation in lost sales inventory systems. Naval Research Logistics, 41(6), 739–757.

Papanastasiou, Y. (2020). Newsvendor decisions with two-sided learning. Management Science, 66(11), 5408–5426.

Pasternack, B. A. (1985). Optimal pricing and return policies for perishable commodities. Marketing Science, 4(2), 166–176.

Qin, Y., Wang, R., Vakharia, A. J., Chen, Y., & Seref, M. M. (2011). The newsvendor
problem: Review and directions for future research. European Journal of OperationalResearch, 213(2), 361–374.

Scarf, H. (1959). Bayes solutions of the statistical inventory problem. The Annals of
Mathematical Statistics, 30(2), 490–508.

Spengler, J. J. (1950). Vertical integration and antitrust policy. Journal of Political Economy, 58(4), 347–352.

Weng, Z. K. (1997). Pricing and ordering strategies in manufacturing and distribution alliances. IIE Transactions, 29(8), 681–692.

Yu, Y., Chu, F., & Chen, H. (2009). A stackelberg game and its improvement in a vmi system with a manufacturing vendor. European Journal of Operational Research, 192(3),929–948.

Zhang, S., & Zhang, J. (2018). Contract preference with stochastic cost learning in a
two-period supply chain under asymmetric information. International Journal of Production Economics, 196, 226–247