需求鏈管理協同預測模式之系統動態模擬─以主機板產業為例

A System Dynamics Model for Collaborative Forecasting of Demand Chain Management - Taking Mainboard Industry as Example

王建信(Chien-Hsin Wang)

指導教授 ： 陳銘崑

國立臺北科技大學/管理學院/商業自動化與管理研究所/碩士(2007年)

https://doi.org/10.6841/NTUT.2007.00203

摘要

隨著資訊科技的發展，企業的經營模式面臨重大的轉型。過去由供應端所驅動，以製造商為核心將產品推入市場的模式，使得多數企業在進行預測、銷售、生產與採購規劃時，多半以自身進行思考，鮮少與供應鏈夥伴協同合作。在需求端資訊不透通的情況下，上游「長鞭效應」的現象。本研究以我國主機板產業為研究對象，以需求鏈管理為主要概念，結合協同預測中分享預測與決定預測機制的特性，參照過去文獻以及產業實務，建立一個需求協同預測的系統動態模型進行探討。模型主要針對供應鏈中自有品牌製造商、通路商與零售商在不同協同需求預測機制情境下，協同雙方所設定的不同水準例外門檻值及自有品牌製造商存貨政策，對供應鏈整體總存貨波動變化所產生的影響。研究結果指出訂單預測由買方主導的情境所產生績效最佳，採連續盤存制度的存貨政策對協同預測的適用性較高，而協同預測門檻值的高低在不同情境組合中的影響不一，模擬研究結果可提供企業作為實務上決策擬定之參考。

關鍵字

需求鏈管理 ； 協同預測 ； 系統動態學

並列摘要

With the development of information technology, the model of business administration faces heavy challenges. The former model driven by supply side and took manufacturer as the center pushed products into market, and made most firms consider just themselves when they planned on forecasting, selling, and purchasing, but only a few collaborates with their supply-chain partners. Under the situation of information opaque, it leads the phenomenon that inventory fluctuates severely when it goes upstream, known as “bullwhip effect”.
Theory from demand chain management (DCM), collaborative forecasting, system dynamics (SD) and inventory policy are applied to this study. It establishes a demand collaborative forecasting model combines the characteristics of sharing forecasts and forecasting decision mechanism, and takes former literatures and industrial practices as references. In this study, we take the mainboard industry as the subject to investigate how the OBM manufacturer’s inventory policy affects total supply-chain inventory’s fluctuation in different forecasting decision mechanism under different collaborative forecasting scenarios and different level of exception threshold made from each collaboration sides.
Simulation results shows some conclusions: the scenario of sales forecast dominated by buyer will lead best performance; continuous review inventory policy is more adaptable to collaborative forecasting; high or low level of exception threshold has different affections in different scenarios. The result of simulation can offer references to enterprise when making practical decisions.

並列關鍵字

Demand Chain Management ； Collaborative Forecasting ； System Dynamics

參考文獻

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