Executive Education
Faculty

Florenta Teodoridis

Assistant Professor of Management and Organization

Florenta Teodoridis’ main areas of interest are the economics of innovation, creativity, and the impact of technology on society. Her research agenda consists of two research streams: factors influencing the process of knowledge production at the individual researcher level, and the relationship between knowledge advancement and markets. Through her first research stream, she examines various factors influencing the rate and direction of technological advancements. These advancements include research tools, breadth and depth of expertise, collaboration, and ideology. As part of her second stream, she explores the impact of technological advancement on business strategy, productivity, and labor markets.

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Programs for Organizations:

Custom Designed Curriculum in Economics of Innovation, Creativity and the Impact of Technology

Articles & Research:

Goldfarb, A., Taska, B., & Teodoridis, F. (2021). Could machine learning be a general purpose technology? A comparison of emerging technologies using data from online job postings. A comparison of emerging technologies using data from online job postings (May 8, 2021).

Jeff Furman, Florenta Teodoridis (2020) “Automation, Research Technology and Researchers’ Trajectories: Evidence from Computer Science and Electrical Engineering,”  Organization Science  31(2): 330-354.

Jeffrey Furman, Florenta Teodoridis (2020) “Machine Learning Could Improve Innovation Policy,” Nature Machine Intelligence.

Articles & Research:

Goldfarb, A., Taska, B., & Teodoridis, F. (2021). Could machine learning be a general purpose technology? A comparison of emerging technologies using data from online job postings. A comparison of emerging technologies using data from online job postings (May 8, 2021).

Articles & Research:

Jeff Furman, Florenta Teodoridis (2020) “Automation, Research Technology and Researchers’ Trajectories: Evidence from Computer Science and Electrical Engineering,”  Organization Science  31(2): 330-354.

Articles & Research:

Jeffrey Furman, Florenta Teodoridis (2020) “Machine Learning Could Improve Innovation Policy,” Nature Machine Intelligence.