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City-REDI Seminar Series: Recombinant Knowledge: Balancing Entropy and Relatedness in an Evolutionary Framework - Dr Dieter Kogler, University College Dublin

Location
University House - Room 204
Category
Lectures Talks and Workshops, Social Sciences
Dates
Tuesday 19th February 2019 (14:00-15:00)
Download the date to your calendar (.ics file)
Contact

For more details please contact Sarah Jeffery or Stuart Mitchell for more information.

City-REDI is delighted to invite you to our seminar series covering economics, economic geography, regional science, economic development, critical urbanism and urban policymaking. 

On the 19 February, Dr Dieter Kogler from University College Dublin will deliver a seminar titled "Recombinant Knowledge: Balancing Entropy and Relatedness in an Evolutionary Framework". 

Evolutionary Economic Geography offers a broad, though still evolving, framework that has at its core the production and destruction of novelty in space and the links between novelty and regional economic fortunes. A high degree of average relatedness among technological classes as indicated in regional knowledge spaces is expected to enhance innovative output as related technologies are more easily recombined into new knowledge. However, in the absence of diversity in the technological capabilities inherent to a region, possibilities to pursue recombination activities are limited. This logic follows an older debate of the benefits and restrictions exerted by patterns of regional economic specialization and diversity. Taking a more nuanced approach to the study of technological change in an evolutionary framework, the present study investigates the balance between entropy (diversity) and relatedness (specialization) in generating recombinant knowledge and subsequent regional branching opportunities.

This seminar will take place in Room 204, University House , University of Birmingham, on the 19 February 2019, 2 - 3pm.

You can find directions to the venue here.

Recombinant Knowledge: Balancing Entropy and Relatedness in an Evolutionary Framework

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