2020 Faculty Courses School of Environment and Society Department of Technology and Innovation Management Graduate major in Technology and Innovation Management
Network Economics II
- Academic unit or major
- Graduate major in Technology and Innovation Management
- Instructor(s)
- Masahiro Hashimoto / Duk Hee Lee
- Class Format
- Lecture
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - Intensive
- Class
- -
- Course Code
- TIM.C415
- Number of credits
- 100
- Course offered
- 2020
- Offered quarter
- 3-4Q
- Syllabus updated
- Jul 10, 2025
- Language
- English
Syllabus
Course overview and goals
This course aims to help students to understand basic principles of network economics and encourage them to apply the principles to real economic and business issues. This course is interdisciplinary across different fields. We first address ‘Conventional Network Economics’ including network externalities, increasing returns principle, and then several practical issues related to information good, technology competition, standardization, spatial pattern, and so on. Secondly, students study a basic ‘Network Science’ and related issues such as network structure, network topology, strong tie and weak tie, homophily, and so on. Thirdly, students explore “Complexity’ in natural science and related issues that are handled in physics, biology, neural network. Finally, if time is allowed, we discuss some contemporary issues; Discrepancy and Instability, System Risk. Innovation System, Information Cascades, etc. Through this course students will be able to develop a basic research capability to address research questions, hypotheses, methodologies, and verification, interpretation in Network Economics.
Course description and aims
When students complete successfully this course they will be able to
∙ understand the principles(theories) of network economics
∙ understand how standard economics and network economics are
different
∙ know how to apply network economic theories to practical issues
∙ learn the concepts and methodologies of network topology: graph
theory, social network analysis
∙ know how to do interdisciplinary approaches, specially economics,
physics, network science, complexity science, and so on
∙ address how to develop research question, hypothesis, and model
∙ know how to test the hypothesis, interpret the results, and derive the
implication
Keywords
network economics, network externalities, power-law distribution, critical mass, increasing returns, path-dependence, positive feedback, multiple equilibria, network science, network topology, random network, scale-free network, small-world network, strong tie, weak tie, structural hole, homophily, complexity, phase transition, self-organization, synchronization, discrepancy, instability, system risk. innovation system, information cascades, herding behavior
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
This course will be held for 7 classes within first Q, in 200 min. each.
This course adopts interdisciplinary approach and basically discuss the analogy between social science and natural science through the course. So we conduct the following steps; Network Economics → Network Science → Complexity Science
In each sector we try to cross theory and practice and want students to build the capability to apply network economic theories to practical issues
Finally we will have chance to address how to develop research question, hypotheses, and verify them by individual or group presentation
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Part Ⅱ Network Science 4. Network Structure Graph Theory / Network Topology Analysis | Basic principle of network science |
| Class 2 | Network Structure Graph Theory / Network Topology Analysis | same as above |
| Class 3 | 5. Strong tie vs. Weak tie Strength of Tie / Strength of Weak Tie / Closure, Structural Hole, and Social Capital | Graph theory, Network topology |
| Class 4 | Strong tie vs. Weak tie Strength of Tie / Strength of Weak Tie / Closure, Structural Hole, and Social Capital | same as above |
| Class 5 | 6. Homophily Homophily: Selection vs. Social Influence / Selection vs. Social Influence / Affiliation Network / Empirical Data / Spatial Model of Segregation | same as above |
| Class 6 | Homophily Homophily: Selection vs. Social Influence / Selection vs. Social Influence / Affiliation Network / Empirical Data / Spatial Model of Segregation | same as above |
| Class 7 | Part Ⅲ Complexity Science 7. Complexity: Self-organization Phase Transition: Thermal Convection, etc. / Earthquake and Sandpile / Synchronization: Fireflies, Pacemaker Cell, Brain Wave | Basic understanding on the paradigm of classical science and modern science |
Study advice (preparation and review)
Textbook(s)
to be mentioned at tha class
cf.
Easley, D. and J. Kleinberg (2010), Network, Crowds, and Market: Reasoning about a Highly
Connected World, Cambridge University Press
Shapiro, C and H. R. Varian(1999). Information Rules , Harvard Business School Press.
Reference books, course materials, etc.
to be mentioned at the class
Evaluation methods and criteria
ateendance and cotribution to the classes(50%)
final assignment(50%)
Related courses
- TIM.C410 ： Innovation Policy I
- TIM.A401 ： Methodology of Corporate Management and Finance I
- TIM.C411 ： Innovation Policy II
- TIM.A402 ： Methodology of Corporate Management and Finance II
Prerequisites
Desirable to study the basics of economics, but not strictly