A Dynamic Network Analysis approach for evaluating knowledge dissemination in a multi-disciplinary collaboration network in obesity research

Hyojung Kang, David Munoz

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

Abstract

Effective knowledge dissemination is important to promote the adoption of new concepts and tools. This study aims to provide a framework that assesses strategies for successful knowledge dissemination in a research collaboration network. We propose a Markov-chain Monte Carlo (MCMC) approach along with Dynamic Network Analysis (DNA) to model a social network and understand how different knowledge dissemination strategies can be used in a research collaboration network. The proposed method was demonstrated through a case study that uses a multi-disciplinary collaboration network in obesity research at an academic medical center. To assess the impact of initial disseminators on knowledge dissemination, four different strategies were considered. The simulation results indicated that the best strategy to disseminate knowledge within this obesity research network may be to use central agents in clusters when considering the coverage and speed of knowledge dissemination.

Original languageEnglish (US)
Title of host publication2015 Winter Simulation Conference, WSC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1319-1330
Number of pages12
ISBN (Electronic)9781467397438
DOIs
StatePublished - Feb 16 2016
Externally publishedYes
EventWinter Simulation Conference, WSC 2015 - Huntington Beach, United States
Duration: Dec 6 2015Dec 9 2015

Publication series

NameProceedings - Winter Simulation Conference
Volume2016-February
ISSN (Print)0891-7736

Conference

ConferenceWinter Simulation Conference, WSC 2015
CountryUnited States
CityHuntington Beach
Period12/6/1512/9/15

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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