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研究生:陳芳瑜
研究生(外文):Fang-Yu Chen
論文名稱:B2C需求品項數據分析_ 以個案物流公司為例
論文名稱(外文):B2C Demand Item Data Analysis_ A Case Study of the Logistics Company
指導教授:陳正杰陳正杰引用關係
指導教授(外文):Cheng-Chieh Chen
口試委員:褚志鵬康照宗
口試委員(外文):Chih-Peng ChuZhao-Zong Kang
口試日期:2020-07-17
學位類別:碩士
校院名稱:國立東華大學
系所名稱:運籌管理研究所
學門:商業及管理學門
學類:行銷與流通學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:101
中文關鍵詞:數據分析第三方物流區域分群儲位空間規劃
外文關鍵詞:data analysisthird-party logisticsregional groupingstorage space planning
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隨著網路的發達,引起消費習慣的改變,消費者習慣透過電商平台購物,而大多數的電商平台都會將商品交由第三方物流公司負責管理及配送服務,第三方物流公司每天都需要處裡來自電商平台大量的配送訂單,在過往的經營模式下,不論每日訂單量多寡,都採用每日配送的方式,需要耗費大量的時間及資源,若能有效的整合現有的訂單,針對不同時間的需求改善配送方式,甚至進一步評估各地區較常被訂購的商品,將需求品項提前配送至當地的物流倉庫,既能滿足消費者需求,亦能提升整體配送效率,為個案物流公司省下可觀的成本支出。
本研究透過數據分析,整合個案物流公司提供的歷史配送資料,將配送訂單根據進行區域分群,並針對不同地區的訂購特性提出更有效率的配送改善建議及商品庫存種類決策參考,提供個案物流公司作為處理現有訂單與存貨管理時的參考依據。
另外,本研究透過分析一定期間內的品項訂購頻率及數量,選取出熱門商品,並依照需求規則進行排列,提供個案公司儲位空間規劃建議。文中應用聚類分析將訂單資料進行區域分群,並分析訂單品項變化,了解消費者購物習慣,找出各地區需求品項,作為存貨管理依據。
With the development of the Internet, changes in consumption habits are caused. Nowadays consumers are used to shopping on e-commerce platforms. Most e-commerce platforms will deliver their goods to third-party logistics company for management and distribution services. Third-party logistics companies need to process a large number of distribution orders from e-commerce platforms every day. Under the previous business model, no matter how many of the daily order volume, the daily delivery method is used, which requires a lot of time and resources. If it can effectively integrate existing orders To improve the delivery method according to the needs at different times, and even further evaluate the more frequently ordered products in various regions, and deliver the required items to the local logistics warehouse in advance, which can not only meet the needs of consumers, but also improve the overall distribution efficiency. Logistics companies save considerable costs.
This study uses data analysis to integrate historical distribution data provided by case logistics companies, group delivery orders according to regions, and propose more efficient distribution improvement suggestions and merchandise inventory decision references for order characteristics in different regions to provide case logistics companies. As a reference basis for processing existing orders and inventory management.
In addition, this study selects popular commodities by analyzing the order frequency and quantity of items within a certain period, and arranges them according to the demand rules to provide storage space planning suggestions for case companies. In this paper, the cluster analysis method is used to regionally group order data, analyze the changes of order items, understand consumer shopping habits, find
out the demand items in various regions, and use them as the basis for inventory management.
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 4
1.3 研究對象與範圍 5
1.4 個案背景簡介 5
1.4.1 公司簡介 5
1.4.2 倉儲業務內容 6
1.4.3 電商專倉 6
1.5 研究限制 6
1.6 研究流程與架構 7
第二章 文獻探討 9
2.1 訂單數據分析 9
2.1.1 數據分析 9
2.1.2 視覺化數據分析 14
2.1.3 資料探勘 14
2.2 第三方物流倉儲 16
2.2.1 第三方物流定義 16
2.2.2 倉儲管理 18
2.2.3 儲位分配 19
2.3 資料分群 20
2.4 小結 25
第三章 研究方法 27
3.1 研究課題 27
3.2 研究流程 27
3.3 研究方法 29
3.3.1 資料匯入 29
3.3.2 資料處理 31
3.3.3 區域分群與資料再處理 34
3.3.4 資料分析與品項分析 37
第四章 資料分析結果 41
4.1 分群 41
4.2 每日各區及全台訂單量變化 46
4.3 各區每星期訂單量變化 48
4.4 不同選取規則熱門商品 52
4.5 各地區每周及全月熱門品項數與重複天數 55
4.5.1 北部群 56
4.5.2 中部群 59
4.5.3 南部群 62
4.5.4 小結 65
4.6 各地區全月熱門品項重複天數與平均數量 66
4.6.1 北部群 67
4.6.2 中部群 69
4.6.3 南部群 70
4.6.4 小結 72
4.7 不同擺放規則之儲位建議 73
第五章 結論與建議 93
5.1 結論 93
5.2 建議 93
參考文獻 95
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