| 授業名 | Artificial Intelligence in Business Management |
|---|---|
| Course Title | Artificial Intelligence in Business Management |
| 担当教員 Instructor Name | Minjeong Ham |
| コード Couse Code | NUC452_N24B |
| 授業形態 Class Type | 講義 Regular course |
| 授業形式 Class Format | On Campus |
| 単位 Credits | 2 |
| 言語 Language | EN |
| 学位 Degree | BBA |
| 開講情報 Terms / Location | 2024 UG Nisshin Term4 |
授業の概要 Course Overview
Misson Statementとの関係性 / Connection to our Mission Statement
The course enables students to share best-case scenarios of businesses utilizing AI technologies. By focusing on strategic applications rather than technical details, students will develop the visionary approach needed to spearhead AI-driven innovation in business, embodying NUCB's commitment to cultivating frontier-minded professionals.
授業の目的（意義） / Importance of this course
Artificial Intelligence (AI) technology fundamentally differs from traditional information and communication technologies in both theoretical and practical aspects. This uniqueness has led to a rapid increase in business opportunities leveraging AI in recent times. To capitalize on these opportunities, it's crucial to understand both the theoretical and practical dimensions of AI technology. This course aims to provide that understanding, focusing on the principles and strategies for applying AI in business environments.
到達目標 / Achievement Goal
This course equips students with the knowledge and skills necessary to integrate AI into business environments effectively. Through real-world case studies, students will examine how businesses are harnessing AI technologies to gain competitive advantage and overcome strategic challenges. Students will cultivate the visionary approach necessary for spearheading AI-driven innovation in business, aligning with NUCB's mission to produce frontier-minded professionals.
本授業の該当ラーニングゴール Learning Goals
*本学の教育ミッションを具現化する形で設定されています。
LG1 Critical Thinking
LG2 Diversity Awareness
LG3 Ethical Decision Making
LG4 Effective Communication
LG6 Managerial Perspectives (BBA)
LG7 International Perspectives (BA)
LG2 Diversity Awareness
LG3 Ethical Decision Making
LG4 Effective Communication
LG6 Managerial Perspectives (BBA)
LG7 International Perspectives (BA)
受講後得られる具体的スキルや知識 Learning Outcomes
○ Identify and evaluate AI-driven business opportunities and challenges across industries
○ Understand stakeholder perspectives in AI adoption, examining how consumers, service providers, policymakers and developers interact with AI-driven systems
○ Develop a frontier-minded perspective for AI-driven business transformation
○ Address ethical and social considerations in applying AI to business, balancing innovation with responsible management
○ Understand stakeholder perspectives in AI adoption, examining how consumers, service providers, policymakers and developers interact with AI-driven systems
○ Develop a frontier-minded perspective for AI-driven business transformation
○ Address ethical and social considerations in applying AI to business, balancing innovation with responsible management
SDGsとの関連性 Relevance to Sustainable Development Goals
Goal 9 産業と技術革新の基盤をつくろう（Industry, Innovation and Infrastructure）
教育手法 Teaching Method
| 教育手法 Teaching Method | % of Course Time | |
|---|---|---|
| インプット型 Traditional | 5 % | |
| 参加者中心型 Participant-Centered Learning | ケースメソッド Case Method | 95 % |
| フィールドメソッド Field Method | 0 % | 合計 Total | 100 % |
事前学修と事後学修の内容、レポート、課題に対するフィードバック方法 Pre- and Post-Course Learning, Report, Feedback methods
In-class participation, Group Discussion, Group Presentation, Final Report
授業スケジュール Course Schedule
第1日（Day1）
Case 1●使用するケース
Growing: Using Artificial Intelligence to Screen Human Intelligence第2日（Day2）
Case 2●使用するケース
TikTok's AI Strategy: ByteDance's Global Ambitions第3日（Day3）
Case 3●使用するケース
SundaySky: Changing Customer Experiences Through Personalized Video第4日（Day4）
Case 4●使用するケース
Baidu INC.: Leveraging Artificial Intelligence for Intelligent Recruitment第5日（Day5）
Case 5●使用するケース
Evie.AI: The Rise of Artificial Intelligence, and the Future of Work第6日（Day6）
Case 6●使用するケース
PittaRosso: Artificial intelligence-driven pricing and Promotion第7日（Day7）
Case 7●使用するケース
Artificial Intelligence: Stitch Fix, A Blue Ocean Retailer in the AI World成績評価方法 Evaluation Criteria
*成績は下記該当項目を基に決定されます。
*クラス貢献度合計はコールドコールと授業内での挙手発言の合算値です。
○ Final Report: 20% of total grade
○ Final Grade Criteria:
90–100: S
80–89: A
70-79: B
60-69: C
40-59: F-Retry*
Below 40: F
*F-Retry: Students may apply for a make-up opportunity to revise their final report. The student will be assigned a C grade if the revised report scores 60 or above.
○ Academic Integrity Policy: There is zero tolerance for any form of academic dishonesty, including but not limited to Plagiarism, Sharing answers with others, Copying answers or papers, Submitting work done by someone else as one's own
*クラス貢献度合計はコールドコールと授業内での挙手発言の合算値です。
| 講師用内規準拠 Method of Assessment | Weights |
|---|---|
| コールドコール Cold Call | 0 % |
| 授業内での挙手発言 Class Contribution | 80 % |
| クラス貢献度合計 Class Contribution Total | 80 % |
| 予習レポート Preparation Report | 0 % |
| 小テスト Quizzes / Tests | 0 % |
| シミュレーション成績 Simulation | 0 % |
| ケース試験 Case Exam | 0 % |
| 最終レポート Final Report | 20 % |
| 期末試験 Final Exam | 0 % |
| 参加者による相互評価 Peer Assessment | 0 % |
| 合計 Total | 100 % |
評価の留意事項 Notes on Evaluation Criteria
○ Class Participation: 80% of total grade (20 for case discussion, 20 for stakeholder group discussion, 40 for stakeholder group presentation)○ Final Report: 20% of total grade
○ Final Grade Criteria:
90–100: S
80–89: A
70-79: B
60-69: C
40-59: F-Retry*
Below 40: F
*F-Retry: Students may apply for a make-up opportunity to revise their final report. The student will be assigned a C grade if the revised report scores 60 or above.
○ Academic Integrity Policy: There is zero tolerance for any form of academic dishonesty, including but not limited to Plagiarism, Sharing answers with others, Copying answers or papers, Submitting work done by someone else as one's own
教科書 Textbook
- Teoh, T. T., & Goh, Y. J.「Artificial Intelligence in Business Management.」 Springer（2023）978-981-99-4557-3
参考文献・資料 Additional Readings and Resource
Mandatory reading materials will be posted on Google Classroom before each class session.
授業調査に対するコメント Comment on Course Evaluation
担当教員のプロフィール About the Instructor
Minjeong Ham is an Assistant Professor at NUCB. She received her Ph.D. in Information Systems from Yonsei University, Seoul, South Korea. She was a postdoctoral fellow at Korea University before joining NUCB. Her research interests include Information Systems adoption and usage in digital business, especially in the creative industry. A significant aspect of her research centers on privacy concerns in personalized advertising, examining the delicate balance between user data protection and effective ad targeting.
Refereed Articles
- (2025) Personal data strategies in digital advertising: Can first-party data outshine third-party data?. International Journal of Information Management 80 0268-4012
- (2024) How does OTT social viewing relieve pandemic-related depressive symptoms? Investigating the moderated mediation model of social connectedness and network types. The Communication Review 10714421
- (2023) Personalization, Privacy and Algorithms in Online Advertising. Yonsei University
- (2021) The effects of internet proliferation on search engine and over-the-top service markets. Telecommunications Policy 45(8): 03085961
- (2021) Empirical study on video clip consumption: focusing on viewing habits and use motives. International Journal of Mobile Communications 19(2): 1741-5217