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課程名稱 |
行銷管理
Marketing Management |
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開課學期 |
108-2 |
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授課對象 |
學程 創意創業學程 |
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授課教師 |
黃明蕙 |
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課號 |
IM3011 |
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課程識別碼 |
705E33100 |
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班次 |
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學分 |
3.0 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期一7,8,9(14:20~17:20) |
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上課地點 |
管一403 |
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備註 |
本課程以英語授課。創意創業學程認列選修學分
限學士班三年級以上
總人數上限：30人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1082IM3011_ |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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課程大綱
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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. |
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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 |
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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. |
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預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
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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. |
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評量方式
(僅供參考) |
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週次 |
日期 |
單元主題 |
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Week 1 |
3/2 |
Orientation |
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Week 2 |
3/9 |
Overview |
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Week 3 |
3/16 |
Multiple AI intelligences |
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Week 4 |
3/23 |
Networked AI |
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Week 5 |
3/30 |
The theoretical foundation of collaborative AI in marketing |
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Week 6 |
4/6 |
Human, biological, and machine intelligences |
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Week 7 |
4/13 |
AI and machine learning |
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Week 8 |
4/20 |
Collaborative intelligence |
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Week 9 |
4/27 |
Collaborative AI for marketing |
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Week 10 |
5/4 |
AI-marketer collaboration I |
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Week 11 |
5/11 |
AI-marketer collaboration II |
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Week 12 |
5/18 |
AI-consumer collaboration I |
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Week 13 |
5/25 |
AI-consumer collaboration II |
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Week 14 |
6/1 |
Collaborative marketing |
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Week 15 |
6/8 |
Final AI-enabled marketing plan presentation |
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Week 16 |
6/15 |
Final AI-enabled marketing plan write-up |
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