Framing the structure of global open innovation research

Hsin-Ning Su, Pei Chun Lee*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

This study proposes a way of mapping open innovation research structure by quantitatively analyzing open innovation research papers retrieved from Web of Science database. A total of 130 papers are retrieved in this study and 62 papers which contain keywords are chosen for research structure visualization. Open innovation research networks are quantitatively investigated by combining network theory and keyword co-occurrence. Contour maps of open innovation are also created on the basis of networks for visualization. The networks and contour maps can be expressed differently by choosing different information as the main actors, such as the paper author, the institute, the country or the author-keywords, to reflect open innovation research structures in micro, meso, and macro-levels, respectively.The quantitative ways of exploring open innovation research structure are investigated to unveil important or emerging open innovation components as well as to demonstrate visualization of the structure of global open innovation research. The quantitative method provided in this project shows a possible way of visualizing and evaluating research community structure and thus a computerized calculation is possible for potential quantitative applications on open innovation research management, e.g. R&D resource allocation, research performance evaluation, and science map.

Original languageEnglish
Pages (from-to)202-216
Number of pages15
JournalJournal of Informetrics
Volume6
Issue number2
DOIs
StatePublished - 1 Apr 2012

Keywords

  • Knowledge map
  • Network theory
  • Open innovation
  • Quantitative analysis
  • Structure

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