Oscar.howell/LOW and Long Tail
Large interconnected groups of people can perform tiny tasks that produce a meaningful whole in collaboration, forgoing monetary motivations. The “work” performed is not evenly distributed among all the members of the community. It follows a Power Law distribution.
There is a small population of collaborators that perform a large number of tasks (usually the people that make many contributions, that organize the work performed or take the task of assembly). And there is the “Long Tail”, a large number of collaborators that perform a very small number of tasks, many of them only one single task ever. The bulk of the “production” is usually done by the Long Tail.
The first group may have monetary motivations, apart from just making contributions to the social network. They tend to have a leading role in the community (like in Lead User Innovation, Hippel, MIT). The people in the second group have little or no monetary motivation. They perform the tasks out of social or psychological motivations and forgo any kind of payment (the Wikipedia collaborator).
- The people performing many tasks (the head) may have a monetary motivation and expect to be paid or other wise rewarded.
- The people in the Long Tail will mainly be motivated by the contribution to the group, but given the chance to have a monetary compensation, will in some cases take it.
- We expect that at some point collaborative networks will move in the direction of offering some kind of monetary rewards to its members, given that there already are some examples of businesses that are experimentiing with it.
- The issue will be how to mantain the motivation of a largely collaborative workforce, and be able to harness the performance it can accomplish, by introducing some sort of monetary reward.
Notes
- "Answerer earnings include a few extreme outliers, including one answerer who has netted some $17,000 from Google Answers for providing more than 900 answers" (Ben Edelman, Earnings and Ratings at Google Answers)
- I find a statistically significantly positive coefficient on the indicator variable for ultimately answering more than ten questions – meaning that the high type answerers already receive higher ratings in their initial answers" (Ben Edelman, Earnings and Ratings at Google Answers)