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 (5)
Financial Profiles of Companies
Online Gig Economy
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 (3)
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
Community evolution in patent networks: technological change and network dynamicsApplied 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.
Consistency and Trends of Technological Innovations: A Network Approach to the International Patent Classification DataInternational 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.