國立高雄大學圖資館 |

登入

回首頁

From Creation to Diffusion to Application: The Evolution of AI Innovations From a Dynamic Network Perspective /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	From Creation to Diffusion to Application: The Evolution of AI Innovations From a Dynamic Network Perspective /Kaige Gao.
作者:	Gao, Kaige,
面頁冊數:	1 electronic resource (198 pages)
附註:	Source: Dissertations Abstracts International, Volume: 87-03, Section: B.
附註:	Advisors: Yoo, Youngjin Committee members: Son, Yoonseock; Schecter, Aaron; Lyytinen, Kalle.
Contained By:	Dissertations Abstracts International87-03B.
標題:	Information technology.
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=32276878
ISBN:	9798291598122

From Creation to Diffusion to Application: The Evolution of AI Innovations From a Dynamic Network Perspective /
Gao, Kaige,

From Creation to Diffusion to Application: The Evolution of AI Innovations From a Dynamic Network Perspective /Kaige Gao. - 1 electronic resource (198 pages)

Source: Dissertations Abstracts International, Volume: 87-03, Section: B.

Artificial Intelligence (AI) is reshaping global economies, yet we lack a holistic understanding of how AI innovations evolve across interconnected communities. This dissertation examines how interactions among heterogeneous actors and artifacts across open-source communities, academic fields, and commercial industries influence AI innovation's creation, diffusion, and application. Unlike previous research focusing on isolated breakthroughs, this study provides a comprehensive view of AI's evolutionary trajectory through a dynamic network perspective. The first introduces "network variability" as a novel construct to analyze how open-source collaboration networks adapt to changing environments, revealing that meaningful structural reconfigurations significantly enhance project development outcomes under increasing complexity. The second study examines how open-source AI models function as boundary objects bridging developer and academic communities, demonstrating that model network positioning influences scholarly impact through complex temporal patterns. The third study investigates cross-boundary knowledge transfer to industry contexts, analyzing how AI knowledge integration strategies affect patent generation and firm valuation in autonomous vehicles, revealing that exploration-oriented approaches yield greater market value than exploitation strategies. These findings establish AI innovation as a networked phenomenon with distinctive evolutionary dynamics that differ from traditional technologies, characterized by complex feedback loops across multiple interacting communities rather than a linear progression.

English

ISBN: 9798291598122Subjects--Topical Terms:

184390
Information technology.
Subjects--Index Terms:

Evolution of innovations

From Creation to Diffusion to Application: The Evolution of AI Innovations From a Dynamic Network Perspective /
LDR:03193nmm a22004333i 4500 001 693776
005 20260511063023.5
006 m o d
007 cr|nu||||||||
008 260819s2025 miu||||||m |||||||eng d
020 $a 9798291598122
035 $a (MiAaPQD)AAI32276878
035 $a AAI32276878
040 $a MiAaPQD $b eng $c MiAaPQD $e rda
100 1 $a Gao, Kaige, $e author. $3 1010449
245 1 0 $a From Creation to Diffusion to Application: The Evolution of AI Innovations From a Dynamic Network Perspective / $c Kaige Gao.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2025
300 $a 1 electronic resource (198 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 87-03, Section: B.
500 $a Advisors: Yoo, Youngjin Committee members: Son, Yoonseock; Schecter, Aaron; Lyytinen, Kalle.
502 $b Ph.D. $c Case Western Reserve University $d 2025.
520 $a Artificial Intelligence (AI) is reshaping global economies, yet we lack a holistic understanding of how AI innovations evolve across interconnected communities. This dissertation examines how interactions among heterogeneous actors and artifacts across open-source communities, academic fields, and commercial industries influence AI innovation's creation, diffusion, and application. Unlike previous research focusing on isolated breakthroughs, this study provides a comprehensive view of AI's evolutionary trajectory through a dynamic network perspective. The first introduces "network variability" as a novel construct to analyze how open-source collaboration networks adapt to changing environments, revealing that meaningful structural reconfigurations significantly enhance project development outcomes under increasing complexity. The second study examines how open-source AI models function as boundary objects bridging developer and academic communities, demonstrating that model network positioning influences scholarly impact through complex temporal patterns. The third study investigates cross-boundary knowledge transfer to industry contexts, analyzing how AI knowledge integration strategies affect patent generation and firm valuation in autonomous vehicles, revealing that exploration-oriented approaches yield greater market value than exploitation strategies. These findings establish AI innovation as a networked phenomenon with distinctive evolutionary dynamics that differ from traditional technologies, characterized by complex feedback loops across multiple interacting communities rather than a linear progression.
546 $a English
590 $a School code: 0042
650 4 $a Information technology. $3 184390
650 4 $a Computer science. $3 199325
653 $a Evolution of innovations
653 $a Dynamic network perspective
653 $a Open-source community
653 $a Innovation diffusion
653 $a Requisite variety theory
690 $a 0489
690 $a 0800
690 $a 0984
710 2 $a Case Western Reserve University. $b Management. $3 886641
720 1 $a Yoo, Youngjin $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 87-03B.
790 $a 0042
791 $a Ph.D.
792 $a 2025
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=32276878