A game-based mechanism for managing 2-decomposable tasks in competitive crowdsourcing environments.

With the rapid development of social platforms and human activities, people are now interested to solve their problems with the help of the social crowd-powered system. So, crowdsourcing has become a promising way of solving problems in a distributed manner within a specific time. Crowd workers pick...

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Detalles Bibliográficos
Publicado en:Behaviour & Information Technology Vol. 42; no. 14; pp. 2366 - 2387
Autores principales: Mridha, Sankar Kumar, Bhattacharyya, Malay
Formato: algorithm equations & formulas pictorial research tables/charts Journal Article
Publicado: Taylor & Francis Ltd Nov2023
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:With the rapid development of social platforms and human activities, people are now interested to solve their problems with the help of the social crowd-powered system. So, crowdsourcing has become a promising way of solving problems in a distributed manner within a specific time. Crowd workers pick up a task (simple or complex) and solve it with competing interest or collaboratively and receive an incentive (as monetary or non-monetary). In paid crowdsourcing platforms, crowd workers solve complex tasks and get remunerations through prior bidding or prior announcement of fee decided by the requester (task provider). For decomposable tasks, a single winner may not provide a significant solution to the requester due to the insufficient knowledge. So, we induce collaboration in competitive crowdsourcing markets to better handle decomposable-type tasks. In this paper, we propose an envelope game-based mechanism that ensures if the tasks are decomposable then the workers will be encouraged to collaborate with their subtasks and share their remunerations. This mechanism also increases the chance of receiving more number of cost-effective solutions. Thus both the requester and crowd workers get benefits from the system. The effectiveness of the proposed mechanism is evaluated through empirical analysis on simulated environments.