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