A Crowdsourcing Data-Driven Approach for Innovation

Forbes, Hannah, Han, Ji ORCID: 0000-0003-3240-4942 and Schaefer, Dirk ORCID: 0000-0002-5695-9312 (2020) A Crowdsourcing Data-Driven Approach for Innovation. The International Journal of Systematic Innovation, 6(2) (2020). 9 - 19.

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Abstract

Creativity is an essential element of innovation, but producing creative ideas is often challenging in design. Many computational tools have been developed recently to support designers in producing creative ideas that are new to individuals. As a common feature, most of the tools rely on the databases employed, such as Con-ceptNet and the US Patent Database. However, the limitations of these databases have constrained the capa-bilities of the tools. Thereby, new computational databases for supporting the generation of ideas that are new to a crowd or even history are needed. Crowdsourcing outsources tasks conventionally performed in-house to a crowd and uses external knowledge to solve problems and democratize innovation. Social media is often employed in crowdsourcing for a crowd to create and share knowledge. A novel approach employing social media to crowdsource knowledge from a crowd for constructing crowd knowledge databases is proposed in this paper. The crowd knowledge database is expected to be used by the current computational tools to sup-port designer producing highly creative ideas, which are new to the crowd, in new product design, and ulti-mately leading to innovation. Challenges of employing this approach are discussed to provide insights and potential directions for future research.

Item Type:	Article
Depositing User:	Symplectic Admin
Date Deposited:	17 Aug 2020 07:48
Last Modified:	18 Jan 2023 23:37
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3097790