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

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

Abstract

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

Citation

Peisl, T., Selen, W., Raeside, R., & Albera, T. (2014). Predictive crowding as a concept to support the assessment of disruptive Ideas: a conceptual framework. The journal of new business ideas & trends, 12(2), 1-13

• 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
• 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: http://researchrepository.napier.ac.uk/id/eprint/7979
• Publisher URL: http://www.jnbit.org/upload/JNBIT_Peisl_Selen_Raeside_Alber_12(2)_2014.pdf
• Contract Date: May 3, 2017