Statistical modeling of nanotechnology knowledge diffusion networks

Shan Jiang, Qiang Gao, Hsinchun Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Nanotechnology is crucial for industrial and scientific advancement, with millions of dollars being invested each year in nanotechnology-related research. Recent developments in information-technology enables modeling the knowledge diffusion process via online depositories of nanotechnology-related scientific publication records. Understanding the mechanism may help funding agencies use their funding effectively. This study uses Exponential Random Graph Models (ERGMs), a family of theorygrounded statistical models, to explore the knowledge diffusion patterns among nanotechnology researchers. We systematically evaluate how various attributes of researchers and public funding affect the knowledge diffusion processes. Results show that the impact of public funding on nanotechnology knowledge transfer has been increasing in recent years. Funding all kinds of researchers can stimulate knowledge transfer. Also, funding senior researchers help stimulate knowledge sharing. Our analysis framework of knowledge diffusion networks is effective in studying the knowledge diffusion patterns in nanotechnology, and can be easily applied to other fields.

Original languageEnglish (US)
Title of host publicationInternational Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design
Pages3552-3571
Number of pages20
Volume4
StatePublished - 2013
EventInternational Conference on Information Systems, ICIS 2013 - Milan, Italy
Duration: Dec 15 2013Dec 18 2013

Other

OtherInternational Conference on Information Systems, ICIS 2013
CountryItaly
CityMilan
Period12/15/1312/18/13

Fingerprint

Nanotechnology
Statistical Modeling
nanotechnology
funding
knowledge
Knowledge Transfer
knowledge transfer
Diffusion Process
Knowledge Sharing
Graph Model
Information Technology
Random Graphs
dollar
Statistical Model
Information technology
Knowledge
Knowledge diffusion
Modeling
information technology
Attribute

Keywords

  • Exponential Random Graph Models
  • Knowledge diffusion
  • Statistical network analysis

ASJC Scopus subject areas

  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Library and Information Sciences

Cite this

Jiang, S., Gao, Q., & Chen, H. (2013). Statistical modeling of nanotechnology knowledge diffusion networks. In International Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design (Vol. 4, pp. 3552-3571)

Statistical modeling of nanotechnology knowledge diffusion networks. / Jiang, Shan; Gao, Qiang; Chen, Hsinchun.

International Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design. Vol. 4 2013. p. 3552-3571.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Jiang, S, Gao, Q & Chen, H 2013, Statistical modeling of nanotechnology knowledge diffusion networks. in International Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design. vol. 4, pp. 3552-3571, International Conference on Information Systems, ICIS 2013, Milan, Italy, 12/15/13.
Jiang S, Gao Q, Chen H. Statistical modeling of nanotechnology knowledge diffusion networks. In International Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design. Vol. 4. 2013. p. 3552-3571
Jiang, Shan ; Gao, Qiang ; Chen, Hsinchun. / Statistical modeling of nanotechnology knowledge diffusion networks. International Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design. Vol. 4 2013. pp. 3552-3571
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