2020 Methodology of Mathematical and Computational Analysis II

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Academic unit or major
Graduate major in Technology and Innovation Management
Nakamaru Mayuko  Kajikawa Yuya 
Class Format
Lecture / Exercise     
Media-enhanced courses
Day/Period(Room No.)
Course number
Academic year
Offered quarter
Syllabus updated
Lecture notes updated
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Course description and aims

This course teaches how modeling and simulation help understand innovation management. The aim of this course is to acquire analytical skills which are required to learn and to conduct research on technology management.
Modeling and simulations are good tools to grasp the essence of individuals and organizations. In this course, the students will learn and exercise the methodology of simulations and modeling.

Student learning outcomes

In this course, the students will learn:
1) how to grasp the cause-and-effect relationship in innovation management and make a model to describe it qualitatively and quantitatively.
2) how to analyze models.
3) how to interprete the results properly by comparison with practice.


game theory, evolutionary game theory, natural selection, application to innovation management

Competencies that will be developed

Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

Give a lecture in every class. Exercises are assigned to students, if necessary. In the final day, groups are assign to students and group members discuss together the application of what they have learned to innovation management.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Introduction to this class Introduction to game theory:Nash equilibrium and its application learn game theory and evolutionary game theory which can help understand our society, and consider the application of them to innovation management
Class 2 Introduction to game theory:Nash equilibrium and its application learn the application of game theory to reality
Class 3 Introduction to game theory: Matching theory learn the application of game theory to reality, taking matching theory as an example.
Class 4 Introduction to game theory: social choice theory learn the application of game theory to reality, taking social choice theory as an example.
Class 5 Introduction to evolutionary game theory learn the basic evolutionary game theory
Class 6 Cultural Evolution learn Cultural evolution and consider how cultural evolution can be adapted into technology's evolution and diffusion.
Class 7 Theory in Natural selection and Ecology can be adapted into business and management in human society learn how theory in natural selection and ecology can be adapted into business and management
Class 8 Group discussion based on what the students have learned, the students discuss the application to innovation management

Out-of-Class Study Time (Preparation and Review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.


Not assigned.

Reference books, course materials, etc.

Not assigned.

Assessment criteria and methods

Report (100%)

Related courses

  • TIM.A510 : Social Simulation I
  • TIM.A511 : Social Simulation II
  • TIM.C401 : Ecosystem Management I
  • TIM.C402 : Ecosystem Management II
  • TIM.D401 : Exercises in Research Literacy I
  • TIM.D401 : Exercises in Research Literacy I
  • TSE.C318 : Introduction to Engineering Design and Management of Technology

Prerequisites (i.e., required knowledge, skills, courses, etc.)

No prerequisite.

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