How Good are Ideas Identified by an Automatic Idea Detection System?

9 Pages Posted: 20 Feb 2018

See all articles by Kasper Christensen

Kasper Christensen

Norwegian University of Science and Technology (NTNU)

Joachim Scholderer

Arhus University; University of Zurich

Stine Alm Hersleth

Nofima

Tormod Næs

Nofima

Knut Kvaal

Norwegian University of Life Sciences (NMBU)

Torulf Mollestad

Independent

Nina Veflen Olsen

Independent

Einar Risvik

Nofima

Date Written: March 2018

Abstract

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 ,idea ,idea and idea. 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.

Suggested Citation

Christensen, Kasper and Scholderer, Joachim and Hersleth, Stine Alm and Næs, Tormod and Kvaal, Knut and Mollestad, Torulf and Olsen, Nina Veflen and Risvik, Einar, How Good are Ideas Identified by an Automatic Idea Detection System? (March 2018). Creativity and Innovation Management, Vol. 27, Issue 1, pp. 23-31, 2018. Available at SSRN: https://ssrn.com/abstract=3126559 or http://dx.doi.org/10.1111/caim.12260

Kasper Christensen (Contact Author)

Norwegian University of Science and Technology (NTNU) ( email )

Trondheim NO-7491
Norway

Joachim Scholderer

Arhus University ( email )

Department of Economics and Business Economics
Fuglesangs Allé 4
Århus V, 8210
Denmark
+45 871 65019 (Phone)

HOME PAGE: http://person.au.dk/js@econ.au.dk

University of Zurich ( email )

CCRS
Zähringerstrasse 24
Zurich, 8001
Switzerland
+41 44 634 40 61 (Phone)

HOME PAGE: http://www.ccrs.uzh.ch

Stine Alm Hersleth

Nofima ( email )

Tromsø, NO-9291
Norway

Tormod Næs

Nofima ( email )

Tromsø, NO-9291
Norway

Knut Kvaal

Norwegian University of Life Sciences (NMBU)

Torulf Mollestad

Independent

No Address Available

Nina Veflen Olsen

Independent ( email )

No Address Available

Einar Risvik

Nofima ( email )

Tromsø, NO-9291
Norway

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