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On technology emergence and pattern detection in aggregate innovative activity

Korzinov, Vladimir V.

Abstract:

Theories of General Purpose Technologies (GPT) introduced heterogeneity in the world of technological change in order to explain fluctuations in economic growth, productivity paradoxes, or technological clusters. The first part of this thesis addresses in detail a GPT's emergence, presenting a new theoretical model that focuses on pervasiveness character of a GPT emphasizing knowledge network characteristics. Each new product in the economy is a result of a combination of technologies forming a complex network structure of technological inter-dependencies, where a general knowledge emerges as a result of knowledge spillovers, coordination of innovative efforts among economic agents, dynamics of expected profits, and the structure of knowledge base. The model demonstrates similar network characteristics when compared to empirical networks of products and technologies as well as explains clustering of innovations in time, change of technological paradigms and mechanism leading to a technological lock-in.
It is argued that robotics and especially new developments in service robotics can be considered as a potential GPT. Employing a machine learning technique, namely Support Vector Machine, the second part of this thesis introduces a methodology for identification of service robotics patents within databases. ... mehr


Volltext §
DOI: 10.5445/IR/1000084152
Veröffentlicht am 06.07.2018
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Volkswirtschaftslehre (ECON)
Publikationstyp Hochschulschrift
Publikationsjahr 2018
Sprache Englisch
Identifikator urn:nbn:de:swb:90-841525
KITopen-ID: 1000084152
Verlag Karlsruher Institut für Technologie (KIT)
Umfang XII, 176 S.
Art der Arbeit Dissertation
Fakultät Fakultät für Wirtschaftswissenschaften (WIWI)
Institut Institut für Volkswirtschaftslehre (ECON)
Prüfungsdatum 15.01.2018
Schlagwörter General Purpose Technologies; Patent Analysis; Spatial Organization, Markov Chains
Referent/Betreuer Ott, I.
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