Type of Credit: Elective
Credit(s)
Number of Students
大數據可以為供應商網絡 (Supplier Networks) 提供更好的數據準確性 (Accuracy)、清晰度 (Clarity) 和洞察力 (Insights),從而在共享的供應網絡中實現更多的情境智能 (Contextual Intelligence)。如今的製造商都立足於在準確性(Accuracy)、速度 (Speed) 和質量 (Quality) 方面展開市場競爭,這一定位迫使企業的供應商網絡必須具備一定程度的情景智能的能力。然而當今大多數企業還沒有將大數據技術引入其供應鏈管理當中,本課程將介紹如何將大數據應用於供應鏈管理之中。
能力項目說明
本課程目的在針對大數據分析法在供應鏈各個環節中的作用做講述,指出向智能供應鏈轉型的阻礙。從中,學員可習得如何分割和分析顧客,確定每部分競爭優先權,調整功能背後的策略,感知需求,做出更好決策,確定適當的指標來支持以上的行為。透過這些技巧,學員可利用大數據,解決供應鏈中的問題。
本課程預計以每週三小時,共計十二週,進行授課。授課方式以課堂講授及個案討論為主,並輔以企業參訪、業界人士演講,以及學生心得回饋報告。
教學週次Course Week | 彈性補充教學週次Flexible Supplemental Instruction Week | 彈性補充教學類別Flexible Supplemental Instruction Type |
---|---|---|
週次 Week |
課程主題 Topic |
課程內容與指定閱讀 Content and Reading Assignment |
教學活動與作業 Teaching Activities and Homework |
學習投入時間 Student workload expectation |
|
課堂講授 In-class Hours |
課程前後 Outside-of-class Hours |
||||
1 |
09.13 |
智能供應鏈介紹 |
|
3 |
3 |
2 |
09.20 |
供應鏈策略與取捨 |
|
3 |
3 |
3 |
09.27 |
大數據與產品/服務設計 |
(HBS) IKEA |
3 |
3 |
4 |
10.04 |
Beer Game |
|
3 |
3 |
5 |
10.11 |
大數據與採購 |
|
3 |
3 |
6 |
10.18 |
大數據與製造 (工業4.0) |
Game Theory |
3 |
3 |
7 |
10.25 |
(MBA 停課週) |
|
|
|
8 |
11.01 |
大數據與物流 |
(HBS) Easy Flower |
3 |
3 |
9 |
11.08 |
Plant Visiting / Guest Speaker |
|
3 |
3 |
10 |
11.15 |
大數據與銷售 (新零售) |
Case: 真心服飾 |
3 |
3 |
11 |
11.22 |
(期末報告準備週) |
|
3 |
3 |
12 |
11.29 |
團體專案報告 |
|
3 |
3 |
Assessment Task |
Due Date |
Value |
Class Participation |
Participation, Assignments, Quiz, Discussion, and Interaction with the Lecturer in Classes |
30 % |
Case Discussion |
|
35 % |
Group Project Analysis |
Week 12 |
35 % |
|
|
Total 100 % |
This class, unless otherwise specifically stated, is to be individual effort. Any student engaged in, or supporting other students engaged in, activities which seek to undermine the integrity of the subject assessment process will receive the penalty according to the school policy at National Chengchi University. These activities include cheating, plagiarism, and collusion.
TBD
TBD