Idea Generation, Creativity, and Incentives

By Olivier Toubia. 2006

286 citations recorded by the source corpus.

Subfields: Computer Science Applications, Safety Research, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/fb0ddedd6d99cf1cb55d9cf789edcce6d9c7cc09

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In Computer Science Applications

In Safety Research

In Sociology and Political Science

Citations in the corpus

Rewarding in open innovation communities – how to motivate members (2010, background): “In fact, classic research in social psychology suggests that incentives might actually even have a negative effect on ideation (Toubia, 2006).”
Modeling the Determinants and Effects of Creativity in Advertising (2007, background): “In addition, the divergence and relevance factors developed here could be extended to other marketing mix elements such as new product development (Im and Workman 2004), or the idea generation process itself (Toubia 2006).”
Reward System Design and Group Creativity: An Experimental Investigation (2012, methodology): “Group members have the opportunity to build on each others’ diverse ideas, which could enhance the creativity of individual inputs (Toubia 2006).”
Toolkits for Idea Competitions: A Novel Method to Integrate Users in New Product Development (2006, unknown): “context of NPD (Ernst and Gulati, 2003, Toubia, 2005 ).”
Leveraging Crowdsourcing: Activation-Supporting Components for IT-Based Ideas Competition (2009, background): “although ideas competitions sound like a familiar approach to access the knowledge of customers, there is only limited research that has studied these customer integration practices in detail [12, 37].”
Collaborating to create: The Internet as a platform for customer engagement in product innovation (2005, background): “Well-designed incentives have been found to remarkably improve collaborative idea generation (Toubia, 2004).”
Crowdsourcing New Product Ideas over Time: An Analysis of the Dell IdeaStorm Community (2013, methodology): “Future research might analyze secondary data involving actual crowdsourcing applications and/or construct experimental scenarios to determine the proper rewards and feedback to maintain (or increase) the crowd's output quantity and quality over time (e.g., Toubia 2006).”