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| Title: | 半導體關鍵零組件預測錯誤之實證分析
An Empirical Analysis of Semiconductor Key Component Forecast Errors |
| Authors: | 洛昀
Lo, Yun |
| Contributors: | 莊皓鈞
Chuang, Hao-Chun
洛昀
Lo, Yun |
| Keywords: | 企業決策
需求預測
迴歸分析
半導體產業
Semiconductor industry
Business decision-making
Demand forecasting
Regression analysis |
| Date: | 2024 |
| Issue Date: | 2024-08-05 12:10:57 (UTC+8) |
| Abstract: | 由於半導體庫存資訊不對稱的關係，需求預測對於半導體各大廠商來說都是非常重要的決策依據。需求預測的錯誤往往會伴隨庫存管理不良、產能過剩等後果。為了有效降低需求預測的錯誤，本研究旨在分析導致需求預測錯誤的相關因素，期望能夠找到預測錯誤產生的慣性，提供企業經理人在制定需求預測時的一些不同見解。
本研究透過分析Intel公司於2019年提供的187週、五個不同銷售地區（ALPHA、BETA、GAMMA、DELTA 和 EPSILON，以下簡稱配送中心A、B、G、D 和 E）的微處理器銷售和需求預測數據，並且在原有數據資料的基礎下，創造了表示產品銷售成長幅度(累積銷售總量)、產品近期銷售狀況(產品近四周的銷售總量)、產品生命週期(產品已上市週數) 、下一代產品的世代交替(距離下一代產品上市週數)、替代品與現有產品的共存與銷售策略(下一代的產品的同期銷售量)的相關變項，並以預測錯誤作為目標變數，運用回歸分析挖掘預測錯誤產生的潛在因素。
研究指出，市場趨勢評估、多世代產品策略及企業內部資訊整合程度均對需求預測的準確性有重要影響。經理人在進行需求預測時，不僅需要依賴產品相關的歷史數據，還需考慮市場的新興趨勢、產品生命週期、競爭者動態以及企業內部資訊的有效整合等潛在因素。期望透過本研究能為企業經理人提供在面對需求預測優化時的全面思考方式，減少決策錯誤的發生，進一步打造更完善的需求預測報表。
Due to the asymmetry of information in the semiconductor industry, demand forecasting is a crucial decision-making tool for major semiconductor manufacturers. In order to effectively reduce forecast errors, this study aims to analyze the factors contributing to inaccuracies in demand forecasting. By identifying the inherent biases in forecasting, the research seeks to provide business managers with new perspectives when formulating demand forecasts. This study analyzes the microprocessor sales and demand forecasting data provided by Intel in 2019 with over 187 weeks of data across five different sales regions (ALPHA, BETA, GAMMA, DELTA, and EPSILON, referred to as distribution centers A, B, G, D and E). Based on the original data, we created variables representing product sales growth (cumulative sales), recent sales performance (sales over the past four weeks), product life cycle (weeks since product launch), next-generation product transition (weeks until the next-generation product launch), and the coexistence sales strategy of substitutes and existing products (concurrent sales of next-generation products). Using forecasting errors as the target variable, regression analysis was employed to uncover potential factors leading to forecasting errors.
This study points out that market trend assessment, multi-generation product strategies, and the degree of internal information integration within the company all significantly affect the accuracy of demand forecasts. Managers should not only rely on historical data when making forecasts but also consider emerging market trends, product life cycles, competitor dynamics, and the effective integration of internal information. It is hoped that this study can provide managers with a comprehensive approach to optimizing demand forecasts, reducing decision errors, achieving knowledge externalization, and further creating more accurate demand forecast reports. |
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| Description: | 碩士
國立政治大學
企業管理研究所(MBA學位學程)
111363031 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0111363031 |
| Data Type: | thesis |
| Appears in Collections: | [MBA Program] Theses
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