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| Title: | 應用模擬工具改善電子零組件通路商產品經理之訂單決策
A Simulation Tool to Enhance Product Managers Order Decision-Making in the Electronic Component Industry |
| Authors: | 蔡耀賢
Tsai, Yao Hsien |
| Contributors: | 張欣綠
莊皓鈞
Chang, Hsin Lu
Chuang, Hao Chun
蔡耀賢
Tsai, Yao Hsien |
| Keywords: | 決策輔助系統
電子零組件產業
訂單管理
模擬工具
decision support system
electronic component industry
order management
simulation tool |
| Date: | 2016 |
| Issue Date: | 2016-07-20 17:14:59 (UTC+8) |
| Abstract: | W企業在台灣是一個大型的電子零組件通路商，在供應鏈上扮演著舉足輕重角色，負責整體供應鏈產品的調節和緩衝。然而，在變動相當快速、產品生命週期短的高科技產業往往面對許多的不確定性而導致訂單經常有變動發生。以W企業來說，產品經理是面對不確定性並處理訂單情況的第一線人員，但他們目前都僅仰賴自己的直覺和經驗去做訂單決策，沒有一個明確的決策準則。因此為了解決這樣的問題，W企業與政大合作設計一套模擬工具(ODSS)來輔助產品經理並改善其訂單決策能力。本研究使用模擬工具和產品經理直觀的決策在4個特定情境下探討是否能夠改善產品經理的決策能力。我們在本研究發現了3個結論：
1.模擬工具ODSS在預測「單期訂購決策、一次性訂購及一次性遞交的訂單」的情境下是準確的。然而，產品經理通常在初次處理訂單時會趨向保守且訂購較少的數量，而且會嘗試和客戶溝通把訂單拆成數期分批遞送以降低風險。
2.理論上，當產品經理認知的服務水準越高，訂購數量將會越趨近於顧客的下單量。但我們觀察發現認知的服務水準高低並沒有實際反應在訂購數量上，本研究發現是被產品經理和顧客的關係以及產品屬性所影響。
3.在觀察產品經理輸入參數到模擬工具ODSS時，發現產品經理主觀認知的信心水準會被「產品屬性」、「產品的供應商支持度」和「此顧客的歷史交易紀錄」所影響。另外，產品經理主觀認知的服務水準並沒有實際反應出W企業原先依照客戶規模大小而設定的服務水準。
As one of the biggest electronic component distributors in Taiwan, W company plays a buffer role between upstream and downstream companies in the electronic component industry. While an electronic component distributor may face many uncertain situations, product managers of W company face tremendous challenges when making ordering decisions. Currently, product managers in W company rely solely on their experience and intuition to make decisions, as the company lacks clear rules or methods for supporting its product managers. To solve this problem, we collaborated with W company to design a simulation tool (ODSS) for their product managers and for decision making. Drawing on this research, we reached three conclusions:
1. For a single-period problem with one ordering decision, ODSS’s prediction is closer to fulfilment. However, the manager trends to order fewer items because he/she (a) tends to be more conservative in initial ordering decisions and (b) considers the possibility of placing extra orders later or delaying some of the shipment.
2. Logically, when the desired service level is high, we expect managers’ ordering quantities to increase accordingly. However, we observed that this may not hold in actual decisions, which primarily depend on customer and component types.
3. For input parameters of ODSS, we observed (a) the confidence level is affected by vendor support level, component type, and transaction history; and (b) the service level does not necessarily reflect the customer type. |
| Reference: | [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] Anderson, E. G., & Morrice, D. J. (2000), “A simulation game for teaching service-oriented supply chain management: Does information sharing help managers with service capacity decisions?”, Production and Operations Management, 9(1), 40-55.
[3] Anderson, D., Sweeney, D., Williams, T., Camm, J., & Cochran, J. (2015), “An introduction to management science: quantitative approaches to decision making. Cengage Learning”, 475-488.
[4] Dada, M., Petruzzi, N. C., & Schwarz, L. B. (2007), “A newsvendor`s procurement problem when suppliers are unreliable”, Manufacturing & Service Operations Management, 9(1), 9-32.
[5] Enspire Learning (2004), “Global Supply Chain Management Simulation”, Harvard Business Publishing.
[6] Gopher, D., Well, M., & Bareket, T. (1994), “Transfer of skill from a computer game trainer to flight”, Human Factors: The Journal of the Human Factors and Ergonomics Society, 36(3), 387-405.
[7] Hammond, J. H. (1994), “The beer game: Board version”, Harvard Business School Pub..
[8] Harvard Business Publishing (2015), “CASE METHOD TECHING”, Retrieved September 28, 2015, from https://cb.hbsp.harvard.edu/cbmp/pages/content/
casemethodteaching.
[9] Holweg, M., & Bicheno, J. (2002), “Supply chain simulation–a tool for education, enhancement and endeavor”, International journal of production economics, 78(2), 163-175.
[10] Jacobs, F. R. (2000), “Playing the beer distribution game over the internet”, Production and Operations Management, 9(1), 31-39.
[11] Janda, M. S., Mattheos, N., Nattestad, A., Wagner, A., Nebel, D., Färbom, C., Lê D.H. & Attström, R. (2004), “Simulation of patient encounters using a virtual patient in periodontology instruction of dental students: design, usability, and learning effect in history‐taking skills”, European Journal of Dental Education, 8(3), 111-119.
[12] Khouja, M. (1999), “The single-period (news-vendor) problem: literature review and suggestions for future research”, Omega, 27(5), 537-553.
[13] Kindley, R. (2002), “The power of simulation-based e-learning (SIMBEL)”, The eLearning Developers’ Journal, 17.
[14] Kleijnen, J. P. (2005), “Supply chain simulation tools and techniques: a survey”, International Journal of Simulation and Process Modelling, 1(1-2), 82-89.
[15] Lindley, D. V., & Barnett, B. N. (1965), “Sequential sampling: two decision problems with linear losses for binomial and normal random variables”, Biometrika, 507-532.
[16] O`HARA, J. M. (1990), “The retention of skills acquired through simulator-based training”, Ergonomics, 33(9), 1143-1153.
[17] Olivares, M., Terwiesch, C., & Cassorla, L. (2004), “Structural estimation of the newsvendor model: Theory and applications”, Working paper, University of Pennsylvania, Philadelphia, PA.
[18] O`Neil, S., Zhao, X., Sun, D., & Wei, J. C. (2015), “Newsvendor Problems with Demand Shocks and Unknown Demand Distributions,” Decision Sciences, doi: 10.1111/deci.12187.
[19] Ponce, F. J., Pallarés, F. M., Juan-Llácer, L., & Cardona, N. (2001), “Educational software tool based on a geographical information system (GIS) for radio wave propagation analysis. Education”, IEEE Transactions on, 44(4), 355-364.
[20] Ravid, G., & Rafaeli, S. (2000), “Multi Player, Internet and Java-Based Simulation Games: Learning and Research in Implementing a Computerized Version of the "Beer-Distribution Supply Chain Game"”,.Simulation Series, 32(2), 15-22.
[21] Shi, J., Zhang, G., & Sha, J. (2011), “Jointly pricing and ordering for a multi-product multi-constraint newsvendor problem with supplier quantity discounts”, Applied Mathematical Modelling, 35(6), 3001-3011.
[22] Siddiqui, A., Khan, M., & Akhtar, S. (2008), “Supply chain simulator: A scenario-based educational tool to enhance student learning”, Computers & Education, 51(1), 252-261.
[23] Silver, E., Pyke, D. F., & Peterson, R. (1998), “Inventory management and production planning and scheduling”.
[24] Sparling, D. (2002), “Simulations and supply chains: strategies for teaching supply chain management”, Supply Chain Management: An International Journal, 7(5), 334-342.
[25] Sterman, J. D. (1989), “Modeling managerial behavior: Misperceptions of feedback in a dynamic decision making experiment”, Management science, 35(3), 321-339.
[26] Walters, B. A., Coalter, T. M., & Rasheed, A. M. (1997), “Simulation games in business policy courses: Is there value for students?”, Journal of Education for Business, 72(3), 170-174.
[27] Yang, S., Yang, J., & Abdel-Malek, L. (2007), “Sourcing with random yields and stochastic demand: A newsvendor approach”, Computers & Operations Research, 34(12), 3682-3690
[28] Zhang, G. (2010), “The multi-product newsboy problem with supplier quantity discounts and a budget constraint”, European Journal of Operational Research, 206(2), 350-360. |
| Description: | 碩士
國立政治大學
資訊管理學系
103356008 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0103356008 |
| Data Type: | thesis |
| Appears in Collections: | [資訊管理學系] 學位論文
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