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.
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.
differential equation, numerical analysis, game theory, evolutionary game theory, optimization theory, agent-based simulation
|✔ Specialist skills||Intercultural skills||Communication skills||Critical thinking skills||✔ Practical and/or problem-solving skills|
Give a lecture in every class. Exercises are assigned to students, if necessary.
|Course schedule||Required learning|
|Class 1||innovation management and simulations||learn that simulations and modeling can help understand innovation management|
|Class 2||Modeling and differential equation||learn how to make a model by means of differential equations|
|Class 3||Numerical analysis of differential equation||learn how to analyze differential equations numerically|
|Class 4||Introduction to game theory||learn the application of game theory to reality|
|Class 5||Introduction to evolutionary game theory||learn the basic evolutionary game theory|
|Class 6||Introduction to social simulation||learn what social simulation, especially agent-based simulation, is|
|Class 7||Introduction to optimization theory||learn the basic optimazation theory using simple examples|
|Class 8||Execises||exercise what the students have learned|