An efficient and truthful pricing mechanism for team formation in crowdsourcing markets

Abstract

In a crowdsourcing market, a requester is looking to form a team of workers to perform a complex task that requires a variety of skills. Candidate workers advertise their certified skills and bid prices for their participation. We design four incentive mechanisms for selecting workers to form a valid team (that can complete the task) and determining each individual worker's payment. We examine profitability, individual rationality, computational efficiency, and truthfulness for each of the four mechanisms. Our analysis shows that TruTeam, one of the four mechanisms, is superior to the others, particularly due to its computational efficiency and truthfulness. Our extensive simulations confirm the analysis and demonstrate that TruTeam is an efficient and truthful pricing mechanism for team formation in crowdsourcing markets.IEEE ICC 2015 SAC -Internet of Things 978-1-4673-6432-4/15/$31.00 ©2015 IEEE

Emotional Crowdsourcing Tool Design for Product Development: A Case Study Using Local Crowds

“…To maximize tasks and minimize payments, the researchers came up with the platform Mechanical Perk(MPerk) on top of Amazon's Mechanical Turk(MTurk), which provides a good basis for designing pricing mechanisms for crowdsourcing markets that can be even further extended. Others [22] developed an efficient and truthful pricing mechanism (TruTeam) for team formation in crowdsourcing markets. Among four different incentive mechanisms: profitability, individual rationality, computational efficiency and truthfulness, simulations confirm that the superior mechanism is an efficient and truthful pricing mechanism for crowdsourcing markets.…”

Dynamic Programming based Allocation of Virtual Machine Instances in Clouds

“…Their work increased the efficiency of the auction but they ignore the price problem. Feng (11) presented four possible mechanisms: opt, greedy, VCG and TruTeamin to solve the allocation and pricing problems in set packing, and proved that VCG mechanism and TruTeam mechanism can efficiently allocate the resources with truthful and individual rational properties. The author proposed a strategy-proof incentive mechanism based on the VCG mechanism to deal with Mobile Crowdsourcing problem and achieved the desired design objectives.…”

Complex task allocation for crowdsourcing in social network context

“…Motivated by this example, it is natural to think using social networks to form a team and then undertake the complex task. In fact, there are now some related studies that are often implemented by team formation in which a team of workers that can perform outsourced tasks is found through social networks [41][42][43]. However, the requesters must undertake heavy computing loads for selecting appropriate team members [41,42].…”

“…Moreover, these related studies often assume that the team members are reliable, which may sometimes not conform to the actual situation [43].…”

“…Therefore, this thesis investigates distributed team formation for a batch of tasks in crowdsourcing. In general, the cost of team formation-based crowdsourcing in existing benchmark studies [43,[55][56][57] includes computational cost of forming teams, payments by requesters, and cost of communication among team members; thus, we set weights to make trade-off among them to calculate the total cost. Minimizing the total cost of team formation-based crowdsourcing for a batch of tasks in a social network is proven to be an NP-hard in the thesis.…”