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【Course Description】
This course is designed for doctoral students to develop advanced skills in formulating research questions, building models, and performing model analysis. It also cultivates the ability to conduct quantitative and empirical research using simulation-based approaches.
In addition, the course covers essential aspects of academic writing and scholarly publication, including paper structure and the peer-review process. All course materials are provided in English.
【Supplementary Course Description】
(1) The course is conducted entirely in English.
(2) Face-to-face (in-person) attendance is required. Online or remote participation is not permitted.
(3) The course uses simulation as the primary analytical tool and is specifically designed to equip PhD students with the practical knowledge and skills needed to advance their own research projects.
(4) This course does not cover the fundamentals of simulation techniques or the operational details of simulation software.
(5) Lectures assume that participants already have academic writing experience at least at the level of a master’s thesis (prior publication is not required).
(6) Although formally listed as a lecture course, the class is highly interactive and seminar-style. Students are expected to actively participate through presentations, discussions, and oral reports.
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1. Class Introduction and Simulation Basic
2. How to Write a Good Paper （Releasing Homework 1）
3. How to Critically Read Papers （Releasing Homework 2）
4. How to Critically Read Papers （Releasing Homework 3）
5. Paper Discussions 1 (Releasing Homework 4)
6. Reviewing Academic Papers (Releasing Homework 5)
7. Critical Evaluation of Presentation Materials 1
8. Critical Evaluation of Presentation Materials 2
9. Paper Discussions 2 (Releasing Homework 6)
10. Paper Discussions 3 (Releasing Homework 7)
11. Paper Discussions 4
12. Mult-Agent Simulation (MAS) (Releasing a Final Report)
13. Business Game
14. Research Ideas about Simulation Application 1
15. Research Ideas about Simulation Application 2
(16. Final Report Submission during the exam week）
Note: Schedule is subject to change.
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Students must read all assigned materials before each class. Materials are available for download via the YNU Learning Management System (LMS). After each class, students should review the content carefully and work on assignments, including paper reviews, presentations, and the development of their own research ideas using simulation methods.
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・To master the knowledge of the methods used to skillfully conduct a quantitative and simulation study, including the setting of a suitable research theme, the formulation of a model, and the analysis of the model.
・To fully understand mathematical and quantitative research approaches using simulation
・To develop the ability to adequately understand the contents of the academic studies of other researchers and to conduct proper evaluation of the quality of the extant research.
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・To understand the basic research processes, such as research question formulation, model building, model analysis, and discussion of results.
・To understand the fundamental knowledge of mathematical and empirical modeling techniques using simulation.
・To understand the essential contents of academic research papers and evaluate their quality.
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Final report 20%, Reading and presentation assignments 30%, Research plan development 30%, and Discussions and class participation 20%.
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【成績評価の基準表】
| 秀(S) | 優(A) | 良(B) | 可(C) | 不可(F) |
| 履修目標を越えたレベルを達成している | 履修目標を達成している | 履修目標と到達目標の間にあるレベルを達成している | 到達目標を達成している | 到達目標を達成できていない |
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履修目標：授業で扱う内容（授業のねらい）を示す目標
到達目標：授業において最低限学生が身につける内容を示す目標
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【授業別ルーブリック】
| 評価項目 | 評価基準 |
| 期待している以上である | 十分に満足できる(履修目標) | やや努力を要する | 努力を要する(到達目標) | 相当の努力を要する |
| Understanding of simulation methods | To substantially master the knowledge of the methods used to skillfully conduct a quantitative and simulation study, including the setting of a suitable research theme, the formulation of a model, and the analysis of the model. | To master the knowledge of the methods used to skillfully conduct a quantitative and simulation study, including the setting of a suitable research theme, the formulation of a model, and the analysis of the model. | To deeply understand the basic research processes, such as research question formulation, model building, model analysis, and discussion of results. | To understand the basic research processes, such as research question formulation, model building, model analysis, and discussion of results. | Less than the expected minimum level. |
| Ability of evaluating simulation research | To substantially understand mathematical and quantitative research approaches using simulation | To fully understand mathematical and quantitative research approaches using simulation | To fully understand the fundamental knowledge of mathematical and empirical modeling techniques using simulation. | To understand the fundamental knowledge of mathematical and empirical modeling techniques using simulation. | Less than the expected minimum level. |
| Development of simulation research | Outstanding ability of development of simulation research planning and operations | Excellent ability of development of simulation research planning and operations | Sufficient ability of development of simulation research planning and operations | Minimum level of ability of development of simulation research planning and operations | Less than the expected minimum level. |
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The course combines lectures, discussions, exercises, and student presentations to help participants master simulation-based research. Students are expected to participate actively in all activities.
The language of instruction is English, and face-to-face attendance is mandatory.
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The list of the references will be distributed during the class. The academic papers for reading can be downloadable from the data base system of the university library.
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・Having the credits for the introductory courses on management, mathematics, and statistics.
・Having the knowledge and experience of basic level computer programming (e.g., solution of simultaneous equations, generation of random numbers) using Java and/or Python.
・Having an interest in quantitative management research.
・This course is closely related to other graduate courses covering quantitative methods.
・Lectures are planned on the assumption that all participants already have experience in academic writing at the level of at least a master’s thesis (a published paper is not required).
・Minimum level of English language ability is necessary （Teacing language is English）.
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シミュレーション（Simulation）、オペレーションズ・マネジメント（Operations Management)、研究テーマの構築（Research theme development)、論文作成（Academic paper writing)
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This course focuses on the development of research skills, in particular the skills of writing an academic paper that will be accepted by an academic journal. In 2021, this course will be offered by real-time online teaching using Zoom. The schedule is subject to change. I expect students to actively participate in all the course work by assuming you are a junior researcher.
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