Abstract
Rather than constituting only a new method in the context of innovation that can help foster a business, crowdsourcing represents a new way of structuring and organizing work by relying on the principles of evolution, swarm intelligence and analog knowledge, self-selection, and task distribution and aggregation. More and more companies try to leverage the distributed intelligence of their customers, suppliers, employees, and internet users by setting up crowdsourcing platforms and broadcasting their problems and tasks to the internal and external crowd. Although crowdsourcing has become quite popular, it also faces some difficulties that must be overcome in order to provide value. The lack of a clear task description and problem explanation, of an appealing platform design, solid terms and constrains of participation, or of a fair price structure may create difficulties for companies applying crowdsourcing. But, once they have gained the relevant knowledge, companies can truly benefit from crowdsourcing and develop superior innovations.
No matter who you are, most of the smartest people work for someone else. (Bill Jo, co-founder of Sun Microsystems, 1990)
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Notes
- 1.
“The Mechanical Turk is a crowdsourcing Internet marketplace that enables computer programmers (known as requesters) to co-ordinate the use of human intelligence to perform tasks that computers are currently unable to do. The Requesters are able to post tasks known as HITs (Human Intelligence Tasks), such as choosing the best photo of a store front from among several photographs, writing product descriptions, or identifying performers on music CDs. Workers (called providers in Mechanical Turk’s Terms of Service, or, more colloquially, turkers) can then browse among existing tasks and complete them for a monetary payment set by the Requester.” http://en.wikipedia.org/wiki/Amazon_Mechanical_Turk
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Füller, J., Lemmer, S., Hutter, K. (2014). Crowdsourcing: How Social Media and the Wisdom of the Crowd Change Future Companies. In: Gassmann, O., Schweitzer, F. (eds) Management of the Fuzzy Front End of Innovation. Springer, Cham. https://doi.org/10.1007/978-3-319-01056-4_22
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