TY - GEN
T1 - Empowered by Innovation: Unravelling Determinants of Idea Implementation in Open Innovation Platforms
AU - Situmeang, Frederik
AU - Loke, Rob
AU - de Boer, Nelleke
AU - de Boer, Danielle
N1 - ISSN: 2184-285X connected to the paper.
PY - 2019
Y1 - 2019
N2 - Companies use crowdsourcing to solve specific problems or to search for innovation. By using open innovation platforms, where community members propose ideas, companies can better serve customer needs. So far, it remains unclear which factors influence idea implementation in crowd sourcing context. With the research idea that we present here, we aim to get a better understanding of the success and failure of ideas by examining relationships between characteristics of ideators, characteristics of ideas and the likelihood of implementation. In order to test the methodological approach that we propose in this paper in which we investigate for business relevant innovativeness as well as sentiment based on text analytics, data including unstructured text was mined from Dell IdeaStorm using webcrawling and scraping techniques. Some relevant hypotheses that we define in this paper were confirmed on the Dell IdeaStorm dataset but in order to generalize our findings we want to apply to the Leg o dataset in our current work in progress. Possible implications of our novel research idea can be used to fill theoretical gaps in marketing literature, help companies to better structure their search for innovation and for ideators to better understand factors contributing to successful idea generation.
AB - Companies use crowdsourcing to solve specific problems or to search for innovation. By using open innovation platforms, where community members propose ideas, companies can better serve customer needs. So far, it remains unclear which factors influence idea implementation in crowd sourcing context. With the research idea that we present here, we aim to get a better understanding of the success and failure of ideas by examining relationships between characteristics of ideators, characteristics of ideas and the likelihood of implementation. In order to test the methodological approach that we propose in this paper in which we investigate for business relevant innovativeness as well as sentiment based on text analytics, data including unstructured text was mined from Dell IdeaStorm using webcrawling and scraping techniques. Some relevant hypotheses that we define in this paper were confirmed on the Dell IdeaStorm dataset but in order to generalize our findings we want to apply to the Leg o dataset in our current work in progress. Possible implications of our novel research idea can be used to fill theoretical gaps in marketing literature, help companies to better structure their search for innovation and for ideators to better understand factors contributing to successful idea generation.
KW - Crowdsourcing
KW - Innovation
KW - Unstructured Text
UR - http://www.scopus.com/inward/record.url?scp=85072986692&partnerID=8YFLogxK
UR - http://www.dataconference.org/?y=2019
UR - https://www.scitepress.org/ProceedingsDetails.aspx?ID=ntgme06zBBY=&t=1
U2 - 10.5220/0007948602890295
DO - 10.5220/0007948602890295
M3 - Conference contribution
AN - SCOPUS:85072986692
VL - 1
T3 - DATA 2019 - Proceedings of the 8th International Conference on Data Science, Technology and Applications
SP - 289
EP - 295
BT - DATA 2019 - Proceedings of the 8th International Conference on Data Science, Technology and Applications
A2 - Hammoudi, Slimane
A2 - Quix, Christoph
A2 - Bernardino, Jorge
PB - SCITEPRESS Digital Library
CY - Setúbal (Portugal)
T2 - 8th International Conference on Data Science, Technology and Applications, DATA 2019
Y2 - 26 July 2019 through 28 July 2019
ER -