| 授業名 | Management Analytics |
|---|---|
| Course Title | Management Analytics |
| 担当教員 Instructor Name | KIM Tae-Seok |
| 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 | 2026 UG Nisshin Term4 |
| コード Couse Code | NUC455_N26B |
授業の概要 Course Overview
Mission Statementとの関係性 / Connection to our Mission Statement
Aligning with the NUCB's mission statement, this course aims to nurture innovative, ethical leaders who possess a ‘Frontier Spirit’ in conducting business research in response to the contemporary challenges faced by organizations in the New Asian and global context.
授業の目的（意義） / Importance of this course
This subject provides students with the fundamental knowledge and analytical skills required to support data-driven decision making in business. It equips students with key concepts, analytical frameworks, and methodological tools used in management analytics, while emphasizing ethical considerations in the use of data. Students will learn how to frame managerial problems as analytical questions, evaluate relevant data from multiple sources, apply appropriate analytical techniques, and translate findings into actionable insights. The course also develops students’ ability to plan, execute, and communicate structured analytical projects that inform business strategy and organizational decision-making.
学修到達目標 / Achievement Goal
By taking part in this course, students will deepen their understanding of the following methods in management analytics: research process, secondary data, interview method, survey method, experiment method, hypothesis testing and modeling, research ethics
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)
LG2 Diversity Awareness
LG3 Ethical Decision Making
LG4 Effective Communication
LG6 Managerial Perspectives (BBA)
受講後得られる具体的スキルや知識 Learning Outcomes
Upon completing this course, students are able to:
1. Describe and discuss the significance of management analytics in business and the key research processes.
2. Critically evaluate the strengths and weaknesses of various types of methodologies in management analytics.
3. Design suitable analytical methods in collecting, processing and analyzing data for quantitative and qualitative research with different purposes.
4. Critically evaluate key ethical issues and their potential impacts in research processes.
1. Describe and discuss the significance of management analytics in business and the key research processes.
2. Critically evaluate the strengths and weaknesses of various types of methodologies in management analytics.
3. Design suitable analytical methods in collecting, processing and analyzing data for quantitative and qualitative research with different purposes.
4. Critically evaluate key ethical issues and their potential impacts in research processes.
SDGsとの関連性 Relevance to Sustainable Development Goals
Goal 8 働きがいも経済成長も（Decent Work and Economic Growth）
教育手法 Teaching Method
| 教育手法 Teaching Method | % of Course Time | |
|---|---|---|
| インプット型 Traditional | 20 % | |
| 参加者中心型 Participant-Centered Learning | ケースメソッド Case Method | 80 % |
| 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
"Pre-class Preparation"
Students are expected to study each case and prepare their own answers to the questions in the assignment files. Participants should allow at least 3 hours of preparation time per case.
A laptop computer is required for electronic distribution of handouts on the day of the class.
"Class Discussion"
The class is based on open discussions and students are facilitated to exchange their opinions with their classmates. During the open discussions, students are expected to think flexibly and adjust their opinions. No specific comment may be given to each student's opinion, but students will know if their opinions are appreciated by listening to their classmates' feedback.
"Preparation report"
Assignment: Answer one of the assignment questions of the case.
Due date: A day before the class of the chosen case (due midnight).
Submission method: Please submit to Google Classroom.
Feedback method: Comments to the assignments will be discussed in the class.
"Final exam"
Theme: Management analytics design
Date: 7th week, in-class exam
Content: Students will answer questions related to one of the cases assigned between Week 1 and 6.
Submission method: Please submit to Google Classroom.
Feedback method: graded rubrics will be shared
Students are encouraged to use the Central Information Center (Library) for assessing relevant material about this course for self-study and final report writing.
Students are expected to study each case and prepare their own answers to the questions in the assignment files. Participants should allow at least 3 hours of preparation time per case.
A laptop computer is required for electronic distribution of handouts on the day of the class.
"Class Discussion"
The class is based on open discussions and students are facilitated to exchange their opinions with their classmates. During the open discussions, students are expected to think flexibly and adjust their opinions. No specific comment may be given to each student's opinion, but students will know if their opinions are appreciated by listening to their classmates' feedback.
"Preparation report"
Assignment: Answer one of the assignment questions of the case.
Due date: A day before the class of the chosen case (due midnight).
Submission method: Please submit to Google Classroom.
Feedback method: Comments to the assignments will be discussed in the class.
"Final exam"
Theme: Management analytics design
Date: 7th week, in-class exam
Content: Students will answer questions related to one of the cases assigned between Week 1 and 6.
Submission method: Please submit to Google Classroom.
Feedback method: graded rubrics will be shared
Students are encouraged to use the Central Information Center (Library) for assessing relevant material about this course for self-study and final report writing.
授業スケジュール Course Schedule
第1日（Day1）
Small group discussion and class discussionThemes: Introduction of Business Research
Main contents: Value of business research, different approaches of business research, data, research processes
●使用するケース
Windermere Manor: Sustainability and Change (9B13C044, Ivey Publishing (2013)) (related to SDG Goal#9 Industry, Innovation, and Infrastructure) * Case may be updated第2日（Day2）
Small group discussion and class discussionThemes: Secondary Data
Main contents: secondary data, data analytics, HR analytics
●使用するケース
Agoda: People Analytics and Business Culture (A) (W17429-PDF-ENG, Ivey Publishing) (related to SDG Goal#9 Industry, Innovation, and Infrastructure) * Case may be updated第3日（Day3）
Small group discussion and class discussionThemes: Interview Methods
Main contents: focus group discussion, in-depth Interview, interview question design, interview and facilitation skills, content analysis
●使用するケース
All Nutrition (A): Focus Group Research for Market Segmentation (CU276-PDF-ENG, Columbia Business School) (related to SDG Goal#9 Industry, Innovation and Infrastructure) * Case may be updated第4日（Day4）
Small group discussion and class discussionThemes: Survey Methods
Main contents: questionnaire design, measurement, sampling technique, quantitative data analysis
●使用するケース
All Nutrition (B): Quantitative Research for Market Segmentation (CU277-PDF-ENG, Columbia Business School) (related to SDG Goal#9 Industry, Innovation, and Infrastructure) * Case may be updated第5日（Day5）
Small group discussion and class discussionThemes: Experiment Method
Main contents: treatment and control, randomization, experiment design, pilot testing
●使用するケース
Expanding Health Insurance to Millions: Learning from the Oregon Health Insurance Experiment (Harvard Kennedy School, HKS799-PDF-ENG) (related to SDG Goal#9 Industry, Innovation, and Infrastructure) * Case may be updated第6日（Day6）
Small group discussion and class discussionThemes: Hypothesis Testing and Modelling
Main contents: hypotheses, research model, and statistical analysis
●使用するケース
Kenexa (907C04-PDF-ENG, Ivey Publishing) (related to SDG Goal#9 Industry, Innovation and Infrastructure) * Case may be updated第7日（Day7）
Small group discussion and class discussionThemes: Research Ethics
Main contents: research ethics, data privacy, data protection, data usage
●使用するケース
Amazon Shopper Panel: Paying Customers for Their Data (521058-PDF-ENG, Amity Research Centers) (related to SDG Goal#16 Peace, Justice, and Strong Institutions）* Case may be updated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。
*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 | 70 % |
| クラス貢献度合計 Class Contribution Total | 70 % |
| 予習レポート Preparation Report | 10 % |
| 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 | 0 % |
| 期末試験 Final Exam | 20 % |
| 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
Preparation before class and active participation in both small-group and open-class discussion is expected. The preparation report and final exam will be graded by the comprehensiveness and depth of the content.配布教材と教室における電子機器の利用マナーについて Guidelines for Classroom Technology and Proper Use of Course Materials
- ケースメソッド教育の中核は、積極的な参加と知識の共有です。この教育を支えるため参加者は授業中の電子機器（例：スマートフォン、ノートパソコン）の使用を制限するよう求められます。許可を得た場合でも、教室内では電子機器は、ケース討議に資する目的でのみ使用してください。授業中は、たとえケース討議に関連していても、検索エンジンや生成AIの使用は避けて下さい。
- 配布教材（ケースを含む）は指定された授業への参加以外の目的で利用しないで下さい。著者の権利、著作権、特定情報の機密性を保護するため、許可なく教材を個人や組織（生成AI を含む）に提供することはできません。このルールは、印刷物・電子教材のいずれにも適用されます。
- 詳細は「教室における電子機器の利用マナー・教材の適切な利用に関するガイドライン」を確認のうえ、教員の指示に従い、責任をもって遵守してください。
- Active participation and shared learning is at the core of the case method learning.Participants are asked to limit their use of electronic devices (e.g., laptops, smartphones) during classroom sessions in support of this model. Even with permission granted, devices should only be used in the classroom in service to the case discussion. Online searches and generative AI tools, even if related to the case discussion, are discouraged while class is in session.
- Students are prohibited from using the course materials (including cases) distributed by the university for any purpose other than participation in the designated class.Students must not input, process or test course materials with any artificial intelligence (AI) tools, bots, software, or platforms without the author’s permission. These actions violate the terms of use for the course materials and may also constitute copyright infringement.
- Please refer to the "Classroom Technology Guidelines / Guidelines for Properly Using Course Materials” for details, and follow the instructor’s directions. You are expected to comply with these guidelines responsibly.
教科書 Textbook
- NA「NA」NA（NA）
参考文献・資料 Additional Readings and Resource
There is no set textbook for this course, but students can refer to an open-source textbook by the following weblink:
Social Science Research: Principles, Methods, and Practices
https://open.umn.edu/opentextbooks/textbooks/social-science-research-principles-methods-and-practices
Introductory Statistics
https://open.umn.edu/opentextbooks/textbooks/introductory-statistics
Additional readings and videos will be distributed and shown in class.
Social Science Research: Principles, Methods, and Practices
https://open.umn.edu/opentextbooks/textbooks/social-science-research-principles-methods-and-practices
Introductory Statistics
https://open.umn.edu/opentextbooks/textbooks/introductory-statistics
Additional readings and videos will be distributed and shown in class.
授業調査に対するコメント Comment on Course Evaluation
The assessment structure has been revised in response to feedback and suggestions from previous participants. Adjustments have been made to better align assignments with the development of practical analytical and decision-making skills. In addition, feedback will be provided more frequently throughout the semester to support students’ continuous improvement and learning progress.
担当教員のプロフィール About the Instructor
Tae-Seok (Brian) Kim is an Associate Professor at NUCB Business School. He earned his PhD in Management from Emory University in the United States. His research focuses on strategic management and organization theory, utilizing diverse methodologies such as social network analysis and natural language processing. His research explores the factors influencing organizational actions and their outcomes, with a particular emphasis on internationalization, sustainability, and innovation.
（実務経験 Work experience）
Before joining NUCB, Tae-Seok (Brian) Kim served as an Assistant Professor at Waseda University School of Commerce.
Refereed Articles
- (2025) Recombination for Resilience: Corporate R&D Teams and Climate Innovations. R&D Management
- (2025) Beyond tokenism: a contingency model of board gender diversity and environmental innovation in Korean and Japanese firms. Asia Pacific Business Review
- (2024) Overcoming Uncertainty in Novel Technologies: The Role of Venture Capital Syndication Networks in Artificial Intelligence (AI) Startup Investments in Korea and Japan. Systems 2079-8954
- (2023) Mapping the Landscape of Blockchain Technology Knowledge A Patent Co-Citation and Semantic Similarity Approach. Systems 2079-8954
- (2023) A Structural Topic Modeling Approach to Exploring E-Commerce and Online Startups during COVID-19. E-Trade Review 21(1): 3022-8042
Refereed Proceedings
- (2024). Client Conflict as Barriers to Interfirm Mobilities in Professional Services Industry. Academy of Management Proceedings .The 84th Annual Meeting of the Academy of Management. 1. 2. Chicago, USA
- (2022). Foreign Firms' Outsiderness, Status, and Cross-Border Tie Formation Through Local Intermediaries. Academy of Management Proceedings .The 82nd Annual Meeting of the Academy of Management. 1. 2. Seattle, USA (Hybrid)
- (2021). Hazardous Connections: Conflictual Ties, Common Intermediary, and Tie Dissolution. Academy of Management Proceedings .The 81st Annual Meeting of the Academy of Management. 1. 2. Virtual