| 摘要: | 摘要
電商滯銷庫存成因探討及存貨控制改善的研究
－以A公司為研究對象
頁數：75頁
校所組別：國立中央大學工業管理研究所
畢業時間及提要別：113學年度第2學期碩士論文提要
研究生：姚羿琳
指導教授：何應欽 博士
論文摘要：
本研究以A公司為個案，探討B2C（Business to Consumer, 簡稱B2C）電子商務環境中滯銷庫存的生成機制與現行存貨控制策略的制度性缺陷，並提出具體改善方案。隨著電商平台商品策略日趨少量多樣，商品結構日益複雜，導致庫存分類失真、安全庫存設計失衡與滯銷品處理遲滯等問題，嚴重影響倉儲效能與資金周轉。為此，本研究從商品價值與需求穩定性出發，導入ABC分類（ABC Classification）與變異係數（Coefficient of Variation, 簡稱CV），建構九宮格交叉分類架構，協助釐清制度盲點，並設計更具策略適配性的控管原則。進一步結合實務資料進行分類模擬與滯銷品處理機制優化，評估制度調整對庫存結構與周轉效率的影響。結果顯示，結合 ABC 與 CV 分類法有助於提升商品分類準確度，縮短滯銷反應時間，並降低庫存積壓風險，強化補貨與退清決策的執行效率。研究亦指出，制度落實效果高度仰賴資訊透明與組織協作，故提出強化分類制度運作與部門分工的管理建議。整體而言，本研究驗證交叉分類制度於電商庫存管理上具明確效益，實證成果可為同類型企業提供具體改善參考與制度優化依據。
關鍵字：B2C電子商務、商品分類、滯銷庫存、ABC分類、需求變異係數。;Abstract
Exploring the Causes of Dead Stock and Improving Inventory Control Strategies in E-commerce - A Case Study of Company A
Total number of pages：75
Program and university：Graduate Institute of Industrial Management,
National Central University.
Graduation semester and year：2025 spring semester
Student：Yi-Lin Yao
Thesis advisor：Dr. Ying-Chin Ho
Abstract：
This study explores the causes of slow-moving inventory in a B2C (Business to Consumer) e-commerce environment, using Company A as a case study. It examines the systemic flaws in current inventory control strategies and proposes practical improvements. With the increasing trend toward low-volume, high-variety product strategies on e-commerce platforms, issues such as inventory misclassification, imbalanced safety stock design, and delayed processing of unsellable items have become prominent, severely impacting warehouse efficiency and cash flow. To address these challenges, this research incorporates ABC Classification and the Coefficient of Variation (CV) based on product value and demand stability. A cross-classification framework in a 3×3 matrix structure is developed to identify institutional blind spots and design more strategically aligned control principles. Further simulations using actual business data were conducted to optimize the processing mechanisms for slow-moving items and assess the impact of system adjustments on inventory structure and turnover efficiency. The results indicate that the integrated use of ABC and CV classification enhances classification accuracy, shortens response time to unsellable items, and reduces inventory accumulation risk, thereby improving the effectiveness of replenishment and clearance decisions. The study also highlights that the effectiveness of the system depends heavily on information transparency and cross-functional collaboration. Accordingly, it offers managerial suggestions for strengthening system implementation and departmental coordination. Overall, the study confirms that cross-classification systems bring measurable benefits to inventory management in e-commerce settings, and its findings may serve as practical references for similar enterprises seeking to optimize their inventory control systems.
Keywords: B2C e-commerce, product classification, slow-moving inventory, ABC classification, demand variability coefficient. |
