pBOL: An Idea Filtering Method Based on Negative Multi-Voting and Pareto Aggregation

30 Pages Posted: 21 May 2018

See all articles by Ana Cristina Garcia

Ana Cristina Garcia

UFF - Universidade Federal Fluminense; Massachusetts Institute of Technology (MIT) - Sloan School of Management

Mark Klein

Massachusetts Institute of Technology

Date Written: August 11, 2017

Abstract

Open Innovation has pioneered as a troubleshooting method based on massively magnifying the source of solvers who bring new and unusual perspectives to solutions. Successful crowdsourcing brings a new challenge: the selection of ideas that deserve attention. This paper describes a new method for filtering ideas based on crowd evaluation: pBOL. The novelty lies on three aspects: the task is predicting a specialized committee’s choices rather than providing preferences, the task is eliminating bad ideas rather than selecting the best ones and the final solution comes from Pareto aggregation of subgroup solutions. Experimental results show the potential benefit of using pBOL as a high speed filtering method to enable successful open innovation.

Keywords: open innovation, idea filtering, negative multi-voting

JEL Classification: Y

Suggested Citation

Garcia, Ana Cristina and Klein, Mark, pBOL: An Idea Filtering Method Based on Negative Multi-Voting and Pareto Aggregation (August 11, 2017). Available at SSRN: https://ssrn.com/abstract=3175329 or http://dx.doi.org/10.2139/ssrn.3175329

Ana Cristina Garcia

UFF - Universidade Federal Fluminense ( email )

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Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

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Cambridge, MA 02142
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Mark Klein (Contact Author)

Massachusetts Institute of Technology ( email )

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MIT E94-1505
Cambridge, MA 02139
United States
617-253-6796 (Phone)

HOME PAGE: http://cci.mit.edu/klein/

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