課程資訊
課程名稱
電子商務
Electronic Commerce 
開課學期
107-1 
授課對象
管理學院  資訊管理學研究所  
授課教師
黃明蕙 
課號
IM7082 
課程識別碼
725EU3320 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期一7,8,9(14:20~17:20) 
上課地點
管一403 
備註
本課程以英語授課。
限碩士班以上
總人數上限:30人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1071IM7082_ 
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課程概述

“The rise of artificial intelligence has inspired both fascination and fear of the world to come.” (Ginny Rometty, IBM CEO, December 2016)

E-commerce is the strategic management of the creation and delivery of product in which information and communication technology play a substantial role. It is interdisciplinary, encompassing information systems, marketing management, service science, and strategic management, among others.

Notably, e-commerce can be e-business, where companies have included e-commerce as part of their value creation and appropriation; can be e-marketing, where marketing activities are carried out electronically to add value to the goods and services to customers; and can be e-service, where the creation and delivery of service is digitalized. 

課程目標
This semester this course has a special focus on the strategic role and impact of artificial intelligence (AI) in e-commerce. AI, manifested by machines that exhibit aspects of human intelligence, is increasingly utilized in e-commerce, and today is a major source of e-commerce innovation and revolution. For example, service robots have automated many parts of e-commerce. We have robots for healthcare and hotels, driverless cars, and automated serving at restaurants. AI has been used extensively in many e-commerce scenarios. For example, virtual bots turn customer service into self-service, big data AI applications are used to recommend portfolios to customers, and social robots such as Pepper are used for frontline customer interactions. This AI revolution is well underway in e-commerce, with AI being expected to have a “greater impact on marketing and communications than social media ever had” (Conick 2016).

The course materials are organized in terms of Huang and Rust’s (2017) four artificial intelligence (AI) levels framework.

I. MECHANICAL AI: does not learn or adapt
II. ANALYTICAL AI: learn and adapt systematically based on data
III. INTUITIVE AI: learn and adapt intuitively based on understanding
IV. EMPATHETIC AI: learn ad adapt emphatically based on experience 
課程要求
The coursework includes presentations and summaries of readings, discussions, participations, and a final case or business plan, including a write-up and presentation on a self-selected e-commerce related topic.  
預期每週課後學習時數
 
Office Hours
另約時間 備註: Office hour: by appointment 
指定閱讀
The major readings of this course are built up through a combination of assigned readings. All the required readings are available for purchase at Harvard Business School Publishing or from the National Taiwan University Library databases. Illegal copies and illegal sharing of course materials are strictly prohibited. 
參考書目
1. Huang, Ming-Hui and Roland T. Rust (2017), “Artificial Intelligence in Service.”

2. Huang, Ming-Hui and Roland T. Rust (2017), “Technology-Driven Service Strategy,” JOURNAL OF THE ACADEMY OF MARKETING SCIENCE, forthcoming.

3. Rust, Roland T. and Ming-Hui Huang (2014), “The Service Revolution and the Transformation of Marketing Science,” MARKETING SCIENCE, 33(2), 206-221.  
評量方式
(僅供參考)
   
課程進度
週次
日期
單元主題
第1週
  No class 
第2週
  Overview 
第3週
  Mechanical AI: Service robots 
第4週
  Mechanical AI: Smart service 
第5週
  National holiday 
第6週
  Analytical AI: Big data analytics 
第7週
  Analytical AI: Cognitive technologies 
第8週
  Intuitive AI: Artificial intuition 
第9週
  Mid-term exam week 
第10週
  Mid-term proposal presentation 
第11週
  Guest talk 
第12週
  Intuitive AI: Deep learning 
第13週
  Empathetic AI: Emotional AI 
第14週
  Empathetic AI: Human-machine integration 
第15週
  Final presentation 
第16週
  Final presentation 
第17週
  National holiday