課程大綱

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_
課程簡介影片
核心能力關聯	核心能力與課程規劃關聯圖
課程大綱
為確保您我的權利,請尊重智慧財產權及不得非法影印
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