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Yuan Gao

Senior Research Associate

Norwich, UNITED KINGDOM

She uses data to examine the financial profiles of companies, to study their patents, & to examine their research and development processes.

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Biography

Yuan Gao is Senior Research Associate in the Department of Economics, UEA. She explores the broad issue of what makes innovation happen. She uses data to examine the financial profiles of companies, to study their patents, and to examine their research and development processes. She looks at the concept of “recombination” – how companies draw on what have been totally separate (usually technical) inventions to inform the creation of a new single new idea or (technology) product through the union of these individual concepts.

In addition, Yuan has been researching the online gig economy – where workers undertake their role entirely remotely via the internet, computers, telephone or other technologies (examples are: online transcription services, graphic designers and computer programmers). Part of this is examining the potential to achieve higher pay against conventional gig workers and the resilience of online gig work in the lockdown climate.

Areas of Expertise

RecombinationRemote WorkEconomicsFinancial Profiles of CompaniesOnline Gig Economy

Education

IMT School for Advanced Studies

Ph.D., Economics and Management Science

2018

Purdue University

M.S., Industrial Engineering

2014

Fudan University

B.S., Electronics Engineering

2004

Event Appearances

A Deeper Understanding of Technology Evolution Using Cluster Destructiveness Index

8th Annual CIRANO-Sam M. Walton College of Business Workshop on Networks in Trade and Finance - 2019  Montreal, Canada

Innovative Destructiveness based on Patent Networks: A Case Study in Artificial Intelligence

The Second Tohoku-UEA Research Symposium - 2019  Norwich, U.K.

Consistency and Trends of Technological Innovations: A Network Approach to the International Patent Classification Data

6th Annual CIRANO-Sam M. Walton College of Business Workshop on Networks in Trade and Finance - 2016  Montreal, Canada

Articles

Community evolution in patent networks: technological change and network dynamics | Applied Network Science

2018

When studying patent data as a way to understand innovation and technological change, the conventional indicators might fall short, and categorizing technologies based on the existing classification systems used by patent authorities could cause inaccuracy and misclassification, as shown in literature.

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Consistency and Trends of Technological Innovations: A Network Approach to the International Patent Classification Data | International Conference on Complex Networks and their Applications

2017

Classifying patents by the technology areas they pertain is important to enable information search and facilitate policy analysis and socio-economic studies. Based on the OECD Triadic Patent Family database, this study constructs a cohort network based on the grouping of IPC subclasses in the same patent families, and a citation network based on citations between subclasses of patent families citing each other.

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