Crowdsourcing in real time. Number of workers and Expected Waiting Time: the trade-off in the Retainer Model.

Abstract

Crowdsourcing, as a “participative online activity in which an individual, an institution, a non-profit organization, or company proposes to a group of individuals of varying knowledge, heterogeneity, and number, via a flexible open call, the voluntary undertaking of a task” (Estellés-Arolas and González-Ladrón-de-Guevara, 2012), is becoming more and more popular. The application of crowdsourcing in real time is something that the crowdsourcing world is studying and trying to solve, knowing its potentialities concerning the future of marketing, security and some phone applications that would simplify everyday life.

If crowdsourcing is the encounter between different intelligences, realtime crowdsourcing represents the desire that this meeting produces a response in the shortest possible time.

This thesis wants to study the characteristics of the Retainer Model, a model that mathematically analyzes crowdsourcing in real time, analyzing and studying the function of total cost of hiring some workers and the Expected Waiting Time for a new incoming task. It wants to identify the reasons of the existence of a minimum stationary point that represents the minimum number of workers optimizing the Retainer Model’s trade-off, as much as an algorithm to automatically find this optimal number.