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題名 需求不確定及錯誤預期下的訂貨政策分析
Analysis of ordering policies under demand uncertainty and wrong beliefs作者 賴智祥
Lai, Chih-Hsiang貢獻者 張欣綠<br>莊皓鈞
Chang, Hsin-Lu<br>Chuang, Hao-Chun
賴智祥
Lai, Chih-Hsiang關鍵詞 報童問題
錯誤預期
電子零組件供應商
Newsvendor problem
Wrong belief
Critical fractile
Scarf’s rule
Electronic component distributor日期 2016 上傳時間 31-七月-2017 10:58:26 (UTC+8) 摘要 為了幫助首屈一指的電子零組件供應商解決其訂貨決策問題，本研究試圖去找出優於公司現有訂貨法則的訂貨政策。本研究將兩種學術上知名的訂貨政策比較於公司現有訂貨法則，以得到表現相對較佳的訂貨政策。兩種訂貨政策包含critical fractile solution以及Scarf’s rule。本研究首先比較在需求分配資訊已知下的訂貨政策表現，其次比較了在需求分配資訊發生錯誤預期時的訂貨政策表現。在本研究中，我們採納了貝塔二項分配去捕捉需求，並設計了兩個模擬實驗分別比較上述兩種情境中的訂貨政策表現，以了解在錯誤預期發生前後三種訂貨政策將如何被影響。本研究的目標在於找出在完整資訊下及錯誤預期下的最適訂貨政策，以幫助焦點公司改善其營運績效。
Motivated by the ordering decision problem at the largest high-tech electronic distribution company in the world, this research aims to find a better ordering policy for company managers. To ensure that the new ordering policies can lower the loss incurred by ordering decisions, we compare two well-known theoretical ordering policies, critical fractile and Scarf’s rule, to the simple rule used by managers in order to assess the performance of the three ordering policies. We also consider the performance of these three ordering policies when managers misjudge the risk of demand distribution. We use a beta-binomial distribution to capture the perceived demand and design a simulation experiment to observe how wrong beliefs affect the performance of different policies. We aim to identify ordering policies that are robust to wrong beliefs and can help the focal company to improve its operational performance, which has been compromised by excess inventory and demand uncertainty.參考文獻 [1]. Alfares, H. K., & Elmorra, H. H. (2005). The distribution-free newsboy problem: Extensions to the shortage penalty case. International Journal of Production Economics, 93, 465-477.[2]. Barnes, E., Dai, J., Deng, S., Down, D., Goh, M., Lau, H. C., & Sharafali, M. (2000). Electronics manufacturing service industry. The Logistics Institute–Asia Pacific, Georgia Tech and The National University of Singapore, Singapore.[3]. Bertsimas, D., & Thiele, A. (2005). A data-driven approach to newsvendor problems. Technical report, Massechusetts Institute of Technology, Cambridge, MA.[4]. Burnetas, A., & Gilbert, S. (2001). Future capacity procurements under unknown demand and increasing costs. Management Science, 47(7), 979-992.[5]. Chen, Y., Xu, M., & Zhang, Z. G. (2009). Technical note-a risk-averse newsvendor model under the cvar criterion. Operations Research, 57(4), 1040-1044.[6]. Gallego, G., & Moon, I. (1993). The distribution free newsboy problem: review and extensions. Journal of the Operational Research Society, 825-834.[7]. Lee, H., & Whang, S. (2002). The impact of the secondary market on the supply chain. Management Science, 48(6), 719-731.[8]. O`Neil, S., Zhao, X., Sun, D., & Wei, J. C. (2015). Newsvendor Problems with Demand Shocks and Unknown Demand Distributions. Decision Sciences.[9]. Porteus, E. L. (2002). Foundations of stochastic inventory theory. Stanford University Press.[10]. Scarf, H., Arrow, K. J., & Karlin, S. (1958). A min-max solution of an inventory problem. Studies in the mathematical theory of inventory and production, 10, 201-209.[11]. Sethi, S. P., Yan, H., & Zhang, H. (2004). Quantity Flexibility Contracts: Optimal Decisions with Information Updates*. Decision Sciences, 35(4), 691-712.[12]. Demand and prices, flexibility factor, p.696[13]. Shah, J., & Avittathur, B. (2007). The retailer multi-item inventory problem with demand cannibalization and substitution. International Journal of Production Economics, 106(1), 104-114.[14]. Silver, E., Pyke, D. F., & Peterson, R. (1998). Inventory management and production planning and scheduling.[15]. Vairaktarakis, G. L. (2000). Robust multi-item newsboy models with a budget constraint. International Journal of Production Economics, 66(3), 213-226. 描述 碩士
國立政治大學
資訊管理學系
103356004資料來源 http://thesis.lib.nccu.edu.tw/record/#G0103356004 資料類型 thesis dc.contributor.advisor 張欣綠<br>莊皓鈞 zh_TW dc.contributor.advisor Chang, Hsin-Lu<br>Chuang, Hao-Chun en_US dc.contributor.author (作者) 賴智祥 zh_TW dc.contributor.author (作者) Lai, Chih-Hsiang en_US dc.creator (作者) 賴智祥 zh_TW dc.creator (作者) Lai, Chih-Hsiang en_US dc.date (日期) 2016 en_US dc.date.accessioned 31-七月-2017 10:58:26 (UTC+8) - dc.date.available 31-七月-2017 10:58:26 (UTC+8) - dc.date.issued (上傳時間) 31-七月-2017 10:58:26 (UTC+8) - dc.identifier (其他 識別碼) G0103356004 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/111452 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊管理學系 zh_TW dc.description (描述) 103356004 zh_TW dc.description.abstract (摘要) 為了幫助首屈一指的電子零組件供應商解決其訂貨決策問題，本研究試圖去找出優於公司現有訂貨法則的訂貨政策。本研究將兩種學術上知名的訂貨政策比較於公司現有訂貨法則，以得到表現相對較佳的訂貨政策。兩種訂貨政策包含critical fractile solution以及Scarf’s rule。本研究首先比較在需求分配資訊已知下的訂貨政策表現，其次比較了在需求分配資訊發生錯誤預期時的訂貨政策表現。在本研究中，我們採納了貝塔二項分配去捕捉需求，並設計了兩個模擬實驗分別比較上述兩種情境中的訂貨政策表現，以了解在錯誤預期發生前後三種訂貨政策將如何被影響。本研究的目標在於找出在完整資訊下及錯誤預期下的最適訂貨政策，以幫助焦點公司改善其營運績效。 zh_TW dc.description.abstract (摘要) Motivated by the ordering decision problem at the largest high-tech electronic distribution company in the world, this research aims to find a better ordering policy for company managers. To ensure that the new ordering policies can lower the loss incurred by ordering decisions, we compare two well-known theoretical ordering policies, critical fractile and Scarf’s rule, to the simple rule used by managers in order to assess the performance of the three ordering policies. We also consider the performance of these three ordering policies when managers misjudge the risk of demand distribution. We use a beta-binomial distribution to capture the perceived demand and design a simulation experiment to observe how wrong beliefs affect the performance of different policies. We aim to identify ordering policies that are robust to wrong beliefs and can help the focal company to improve its operational performance, which has been compromised by excess inventory and demand uncertainty. en_US dc.description.tableofcontents TABLES AND FIGURES iiCHAPTER 1 INTRODUCTION 11.1 Background and Motivation 11.2 Research Questions 1CHAPTER 2 LITERATURE REVIEW 42.1 Newsvendor problems when there is complete information regarding demand distribution 52.2 Newsvendor problems with incomplete information regarding demand distribution 6CHAPTER 3 MODEL 93.1 Demand Distribution 103.2 Ordering Policies 133.3 Model Constraint 15CHAPTER 4 EXPERIMENT WITH ORDERING POLICIES UNDER DEMAND UNCERTAINTY WITHOUT CONSIDERING WRONG BELIEFS 174.1 Experiment Design 174.2 Parameters assumption 194.3 Experiment Results 214.4 Summary 28CHAPTER 5 EXPERIMENT WITH ORDERING POLICIES WHEN MANAGERS HAVE WRONG BELIEFS 305.1 Experiment results 315.2 Summary 39CHAPTER 6 CONCLUSION AND EXPECTED CONTRIBUTIONS 416.1 Conclusion 416.2 Expected Contributions 426.3 Limitations 44References 46 zh_TW dc.format.extent 2240503 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0103356004 en_US dc.subject (關鍵詞) 報童問題 zh_TW dc.subject (關鍵詞) 錯誤預期 zh_TW dc.subject (關鍵詞) 電子零組件供應商 zh_TW dc.subject (關鍵詞) Newsvendor problem en_US dc.subject (關鍵詞) Wrong belief en_US dc.subject (關鍵詞) Critical fractile en_US dc.subject (關鍵詞) Scarf’s rule en_US dc.subject (關鍵詞) Electronic component distributor en_US dc.title (題名) 需求不確定及錯誤預期下的訂貨政策分析 zh_TW dc.title (題名) Analysis of ordering policies under demand uncertainty and wrong beliefs en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) [1]. Alfares, H. K., & Elmorra, H. H. (2005). The distribution-free newsboy problem: Extensions to the shortage penalty case. International Journal of Production Economics, 93, 465-477.[2]. Barnes, E., Dai, J., Deng, S., Down, D., Goh, M., Lau, H. C., & Sharafali, M. (2000). Electronics manufacturing service industry. The Logistics Institute–Asia Pacific, Georgia Tech and The National University of Singapore, Singapore.[3]. Bertsimas, D., & Thiele, A. (2005). A data-driven approach to newsvendor problems. Technical report, Massechusetts Institute of Technology, Cambridge, MA.[4]. Burnetas, A., & Gilbert, S. (2001). Future capacity procurements under unknown demand and increasing costs. Management Science, 47(7), 979-992.[5]. Chen, Y., Xu, M., & Zhang, Z. G. (2009). Technical note-a risk-averse newsvendor model under the cvar criterion. Operations Research, 57(4), 1040-1044.[6]. Gallego, G., & Moon, I. (1993). The distribution free newsboy problem: review and extensions. Journal of the Operational Research Society, 825-834.[7]. Lee, H., & Whang, S. (2002). The impact of the secondary market on the supply chain. Management Science, 48(6), 719-731.[8]. O`Neil, S., Zhao, X., Sun, D., & Wei, J. C. (2015). Newsvendor Problems with Demand Shocks and Unknown Demand Distributions. Decision Sciences.[9]. Porteus, E. L. (2002). Foundations of stochastic inventory theory. Stanford University Press.[10]. Scarf, H., Arrow, K. J., & Karlin, S. (1958). A min-max solution of an inventory problem. Studies in the mathematical theory of inventory and production, 10, 201-209.[11]. Sethi, S. P., Yan, H., & Zhang, H. (2004). Quantity Flexibility Contracts: Optimal Decisions with Information Updates*. Decision Sciences, 35(4), 691-712.[12]. Demand and prices, flexibility factor, p.696[13]. Shah, J., & Avittathur, B. (2007). The retailer multi-item inventory problem with demand cannibalization and substitution. International Journal of Production Economics, 106(1), 104-114.[14]. Silver, E., Pyke, D. F., & Peterson, R. (1998). Inventory management and production planning and scheduling.[15]. Vairaktarakis, G. L. (2000). Robust multi-item newsboy models with a budget constraint. International Journal of Production Economics, 66(3), 213-226. zh_TW
