Department of Economics and Business Economics

How good are ideas identified by an automatic idea detection system?

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

DOI

  • Kasper Christensen, Nofima A/S, Norwegian University of Life Sciences, Norway
  • Joachim Scholderer
  • Stine Alm Hersleth, Nofima A/S
  • ,
  • Tormod Næs, Nofima A/S, University of Copenhagen, Norway
  • Knut Kvaal, Norwegian University of Life Sciences
  • ,
  • Torulf Mollestad, Acando
  • ,
  • Nina Veflen, Nofima A/S, BI Norwegian Business School
  • ,
  • Einar Risvik, Nofima A/S

Online communities can be an attractive source of ideas for product and process innovations. However, innovative user-contributed ideas may be few. From a perspective of harnessing “big data” for inbound open innovation, the detection of good ideas in online communities is a problem of detecting rare events. Recent advances in text analytics and machine learning have made it possible to screen vast amounts of online information and automatically detect user-contributed ideas. However, it is still uncertain whether the ideas identified by such systems will also be regarded as sufficiently novel, feasible and valuable by firms who might decide to develop them further. A validation study is reported in which 200 posts from an online home brewing community were extracted by an automatic idea detection system. Two professionals from a brewing company evaluated the posts in terms of idea content, idea novelty, idea feasibility and idea value. The results suggest that the automatic idea detection system is sufficiently valid to be deployed for the harvesting and initial screening of ideas, and that the profile of the identified ideas (in terms of novelty, feasibility and value) follows the same pattern identified in studies of user ideation in general.

Original languageEnglish
JournalCreativity and Innovation Management
Volume27
Issue1
Pages (from-to)23-31
Number of pages9
ISSN0963-1690
DOIs
Publication statusPublished - 2018

    Research areas

  • AGREEMENT, ANALYTICS, BIG DATA, CREATIVE IDEAS, INNOVATION, MANAGEMENT, ONLINE COMMUNITIES, PRODUCT IDEAS, SOCIAL MEDIA, USER COMMUNITIES

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