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Predictive crowding as a concept to support the assessment of disruptive Ideas: a conceptual framework

Peisl, Thomas; Selen, Willem; Raeside, Robert; Albera, Tatiana


Thomas Peisl

Willem Selen

Tatiana Albera


Purpose - The purpose of this paper, is to develop a conceptual framework for a holistic view on how to use crowd intelligence to identify the logic of sequences to fully address the potential of crowds, and contest the common assumption that one crowd fits all challenges. Design/methodology/approach - This conceptual development is based on both deductive and inductive reasoning and is the result of interdisciplinary collaboration of partner universities and research institutions. Findings - A number of research postulations are presented, opening a future research stream to provide a new perspective on application possibilities of crowdsourcing in SMEs, and encourage further discussion on crowd definition and crowd selection for varying applications. Research limitations/implications - Subsequent empirical work is called for to test various research postulations. Practical Implications - The conceptual framework demonstrates the applicability of crowd intelligence for predictive assessment of disruptive ideas, and adds to the literature on how SMEs could use Predictive Crowding (Expert Crowds) to assess disruptive ideas

Journal Article Type Article
Publication Date 2014
Deposit Date May 6, 2015
Publicly Available Date May 3, 2017
Journal Journal of New Business Ideas & Trends
Print ISSN 1446-8719
Electronic ISSN 1447-9184
Peer Reviewed Peer Reviewed
Volume 12
Issue 2
Pages 1-13
Keywords Crowdsourcing; crowd-sourced innovation; disruptive innovation; innovation assessment; Delphi methodology, predictive crowding
Public URL
Publisher URL
Contract Date May 3, 2017


Predictive Crowding as a Concept to Support the Assessment of Disruptive Ideas: A Conceptual Framework (183 Kb)

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