Skip main navigation

Cookies Notification

We use cookies on this site to enhance your user experience. By continuing to browse the site, you consent to the use of our cookies. Learn More
×

System Upgrade on Tue, May 28th, 2024 at 2am (EDT)

Existing users will be able to log into the site and access content. However, E-commerce and registration of new users may not be available for up to 12 hours.
For online purchase, please visit us again. Contact us at customercare@wspc.com for any enquiries.

SEARCH GUIDE  Download Search Tip PDF File

  • articleNo Access

    Social Innovation: Drawing and Analysis with Using Research in Scientific Base

    The purpose of this study is to analyse the structure of social network co-occurrence and co-authorship of scientific documents of social innovation which are indexed in Scopus database. By using scientometric and network analysis techniques, the records were retrieved and integrated. It has been used a combination of software packages, including VOSviewer, Gephi, HistCite, Publish or Perish and NodeXL, for data analysis and mapping. Analysing all keywords shows that the most important keywords, based on frequency distribution, are innovation, sustainable growth and social entrepreneurship. Thematic mapping of the keywords using co-words analysis technique indicates that the topics innovation, social services and social change had top ranking in degree centrality, closeness centrality and betweenness indicators. The analysis of the co-authorship network of the field demonstrated that it is disconnected and sparse. Moreover, the total number of citations was 8,350. Mapping the knowledge structure of social innovation papers extracted from Scopus database could help to represent and visualise the thematic structure of research in the field of Social Science and Knowledge Studies and identify more specific research focuses within this field. It should be noted that in this study, the importance of concepts such as innovation, sustainable development and social entrepreneurship has been confirmed by reviewing the literature on these issues.

  • articleNo Access

    EMPLOYING STN ANAVIST TO FORECAST CONVERGING INDUSTRIES

    Converging industries are characterized by the blurring of boundaries between technologies, markets and industry sectors. As such they can enable firms to access new markets or threaten them with an array of new competitors and a lack of knowledge. This makes an early identification of convergence trends highly important. In the present paper we focus on the application of a frequency-based analysis and visualization software (STN AnaVist) for the forecasting of converging industries. Scrutinizing 3,836 patent and scientific publication references on phytosterols in the areas of nutraceuticals and cosmeceuticals, we employ research landscape, co-authorship and International Patent Classification (IPC) co-classification analyses. The results demonstrate partial convergence between the pharmaceutical, the chemical, the nutrition and the cosmetics industries and the suitability of the employed approach. According to this study, scientific as well as technology convergence have taken place in this segment, with a time-lag of roughly 25 years.

  • articleNo Access

    SOCIAL NETWORK ANALYSIS OF THE ISPIM INNOVATION MANAGEMENT COMMUNITY IN 2009–2011

    Scientific communities are bound together by common purpose and interests, and tangible evidence of the structure of such communities may be found by investigating co-authorship networks. We utilise social network analysis to examine the network structure of International Society for Professional Innovation Management (ISPIM), using co-authorship data from six ISPIM events during the years 2009–2011. We find interesting evidence of the network structure, illustrating vividly the central authors and sub-components of the network. Related to this, results reveal surprisingly tight clustering based on geographical and institutional boundaries. We also find evidence of high performing authors which span these boundaries via significantly different strategies. Overall, the results help to uncover the underlying structure of the scholarly network behind ISPIM, which helps to better understand the key contributors and their networks, and also the development points and promising research collaboration opportunities.