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Facilitating like Darwin : Supporting Cross-Fertilisation in Crowdsourcing

Title data

Gimpel, Henner ; Graf-Drasch, Valerie ; Laubacher, Robert J. ; Wöhl, Moritz:
Facilitating like Darwin : Supporting Cross-Fertilisation in Crowdsourcing.
In: Decision Support Systems. Vol. 132 (May 2020) .
ISSN 1873-5797
DOI: https://doi.org/10.1016/j.dss.2020.113282

Abstract in another language

Humankind faces many "wicked" decision-making problems, which must be solved. One promising approach refers to crowdsourcing systems that hold the potential to solve any kind of problem – notably wicked ones. Crowdsourced solutions work well because crowds exchange knowledge from different domains – a concept known as “cross-fertilisation.” Thereby, the “facilitator” of a crowdsourcing system is the primary decision maker when it comes to specifying and managing the crowd. The facilitator’s role includes actively managing cross-fertilisation. However, in the light of technological advancements and large-scale data, facilitation proves difficult – especially in one particular type of crowdsourcing – crowdsolving. Thus, academia recently called for relieving some burden of facilitators and started developing tools for supporting or automated facilitation. Yet, the focus of existing tools is not on fostering the innermost core of crowdsolving endeavours – cross-fertilisation. By taking a design science perspective, we propose design principles and design guidelines for a decision-support tool aiding facilitators to (a) set the boundary conditions for, (b) measure, and (c) facilitate cross-fertilisation. We evaluate feasibility and value added of the abstract design by applying it to different crowdsolving platforms including a prototypical implementation and qualitative evaluation by facilitators.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Cross-fertilisation; Crowdsolving; Facilitation; Collective Intelligence; Design Science
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering
Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Faculties
Faculties > Faculty of Law, Business and Economics
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 24 Mar 2020 08:56
Last Modified: 08 Jun 2020 06:11
URI: https://eref.uni-bayreuth.de/id/eprint/54665