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The University of Southampton
Centre for Risk Research

How can organisations make money out of crowdsourcing?

Published: 1 October 2013

Dr Frank McGroarty and Dr Gerhard Kling from the Centre for Risk Research are leading a European Union-funded research project into the financial viability of crowdsourcing in IT projects. His colleague Dr Thanassis Tiropanis from Electronics and Computer Science at Southampton is also involved.


The three year €3,347,000 grant from the EU's FP7 programme has been awarded to eight institutions for research into the feasibility of adding crowdsourcing to an existing substantial EU funded multi-country network infrastructure project. Research related to developing a business around this is led by the University of Southampton.

Crowdsourcing encourages people to engage with large complex tasks. Wikipedia is probably the most well-known product of crowdsourcing, but it has been used for other tasks. One such project, Foldit, helped scientists working in drug discovery by creating a puzzle-solving online game around protein folding to create new molecules. Hundreds of thousands of people now play the game. Another crowdsourcing project is Galaxy Zoo, where members of the public are engaged in visual inspection and categorisation of millions of images of galaxies. The new research project aims at engaging users of smart mobile devices such as smart phones and tablet computers, to carry out tasks that computers cannot do well.

"While these developments are exciting in terms of technology and break new ground in research, our role is to examine the commercial potential of crowdsourcing," explains Frank. "We will model how academic researchers can use these techniques and how they could be rolled out commercially as apps."

Southampton researchers will provide financial management expertise to develop the most efficient crowdsourcing applications and explore different incentive systems for people taking part. They will also use crowdsourcing to run online finance experiments, inviting people to make choices and decisions on financial information.

Related Staff Member

We will model how academic researchers can use these techniques and how they could be rolled out commercially as apps.

Frank McGroarty - Professor of Computational Finance
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