Call: Satellite on Complex Networks in Economics and Innovation

Satellite Organizers:
Morgan R. Frank, University of Pittsburgh
Lingfei Wu, University of Pittsburgh
Michele Coscia, IT University of Copenhagen
Call for Participation:
We are looking for abstracts for the “Complex Networks in Economics and Innovation” satellite event of the Networks 2021 conference (Link).

Submission Deadline: May 5, 2021
Notification to Authors: May 21, 2021
Submission of recorded talk (if that’s your chosen option): June 14, 2021
You should submit an abstract of one-page abstract including one optional descriptive figure and caption. If you’re presenting at Networks 2021 or another of its satellites, there should not be too much overlap with your other contributed talks. Your abstract should be submitted to https://easychair.org/my/conference?conf=cnei21.

Confirmed Speakers:
Daniel Rock, The Wharton School, University of Pennsylvania
Hyejin Youn, Kellogg School of Management, Northwestern University
Esteban Moro, Media Lab, MIT
Yong-Yeol “YY” Ahn, Center for Complex Networks and Systems Research, Indiana University Bloomington
Marta Gonzalez, Civil and Environmental Engineering, UC Berkeley
Jiang Zhang, School of Systems Science, Beijing Normal University
R. Maria del Rio-Chanona, Mathematical Institute, University of Oxford
Lü Linyuan, University of Electronic Science and Technology of China

Satellite Description:
Economic convergence occurs when developing economies increase their productivity faster than developed economies. Society has a moral imperative to promote economic convergence because it is the most reliable path to lift people out of poverty and achieve decent standards of living. However, today’s global and regional economies are characterized by a high degree of complexity. Thus, economic convergence is best supported by improved understanding of the ecosystem of complementary actors, knowhow, and capital comprising various economic activities. Thus, productivity may be conceptualized as an emerging property of a complex system made by simpler interacting parts. Complex systems are notoriously difficult to control but quantifying these interactions can identify the bottlenecks to growth and inform policy to bolster economic convergence. Using tools from economics, complex systems, and network science, we seek crucial insights that enable economic convergence.

This satellite will collect contributions using complex network analysis to model economic systems and to gain insights into economic development. Recent results on economic complexity, the principle of relatedness, and on the automation of workplace activities have shown how network analysis can uncover the pathways for innovation and economic development while highlighting potential issues. For example, the Product Space analysis showed how a bipartite country-product network reveals economic complexity that is strongly correlated with diversified export portfolios and future GDP growth. More generally, the principle of relatedness unveils hidden relationships between different industrial activities that can be leveraged to diversify an economy. Failure to exploit these opportunities impedes economic convergence through economic friction. There is much to add to this research, ranging from enhancing its spatial granularity (from global/regional economics to the intra-firm level), to exploring the complex dynamics of knowledge exchange (which is at the basis of the development of new skills and, therefore, of new economic activities), to applying similar techniques in new areas of economic research.

Building on the above, the aim of this satellite is to explore the potential applications of complex network analysis to foster our understanding of complex economic systems. Examples include:

Mapping the relationship of complex economic activities at the global, regional, and local level;
Tracking flows of knowhow in all its forms;
Creating networks of related tasks and skills to estimate knockoff effects and productivity gains of automation;
Investigating the dynamics of research and innovation via analysis of patents, inventions, and science;
Uncovering scaling laws and other growth trends able to describe the systemic increase in complexity of activities due to agglomeration;
In general, any application of network analysis that can be used to further our understanding of economics.

Agenda:
Tenative Schedule (Date TBD. All times are EST):

8:30AM Invited I: Lü Linyuan
9:10AM Invited II: Maria del Rio Chanona
9:50AM Contributed I
10:10AM Contributed II
10:30AM Break
10:50AM Invited III: Yong-Yeol Ahn
11:30AM Contributed III
11:50AM Contributed IV
12:10PM Invited IV: Hyejin Youn
12:50PM Lunch Break
1:30PM Invited V: Esteban Moro
2:10PM Invited VI: Marta C. Gonzalez
2:50PM Contributed V
3:10PM Contributed VI
3:30PM Break
3:50PM Invited VII: Daniel Rock
4:30PM Contributed VII
4:50PM Contributed VIII
5:10PM Invited VIII: Jiang Zhang