An agent-based model for crowdsourcing systems

Zou, Guangyu; Gil, A.E.; Tharayil, Marina

doi:10.1109/wsc.2014.7019907

Cited by 11 publications

(8 citation statements)

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“…Zou et al [35] built an agent-based model of crowdsourcing composed of the requester, task and workers. Workers search for a task and decide whether to accept it or not.…”

Section: Agent-based Models Of Crowdsourcing and Social Innovationmentioning

confidence: 99%

Agent-Based Modelling: Parallel and Distributed Simulation of Product Development Team

2022

Teh. vjesn.

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The successful collaboration of team members plays a crucial role in product development. Research of different teamwork factors may help understand the process, and computer simulation can be a suitable method of achieving this goal. This work aims to give an overview of agent-based modelling of product development teams and survey existing models that tackle this problem. Some tools and frameworks for agent-based modelling will be described with an emphasis on parallel and distributed architectures which are used to improve performance and enable very big and complex simulations.

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“…Zou et al [35] built an agent-based model of crowdsourcing composed of the requester, task and workers. Workers search for a task and decide whether to accept it or not.…”

Section: Agent-based Models Of Crowdsourcing and Social Innovationmentioning

confidence: 99%

Agent-Based Modelling: Parallel and Distributed Simulation of Product Development Team

2022

Teh. vjesn.

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“…To evaluate an agent-based model and increase confidence in its simulation, two activities are generally conducted; Verification and Validation (V&V). Verification refers to the process of determining whether the simulation code corresponds to the conceptual model (Zou et al, 2014) i.e. the program does what it is supposed to do (David, 2006).…”

Section: Validate and Verify The Modelmentioning

confidence: 99%

Untitled

2020

J. Islam. bus. manag.

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In this paper, we try reducing the moral hazard of profit misreporting in Profit and Loss Sharing Contract (PLS). In this kind of contracts , the corporate manager has a temptation to misreport profits which can lead to either project failing or to financiers receiving an unfair allocation of profits. To help in solving this problem we propose a new model that includes a real option that gives the corporate manager (agent) the right, but not the obligation, to gradually buy shares in the corporation from the financier/bank. We compare our results with the standard case of PLS without real options. We show, using a multi-agent simulation (Netlogo) that embedding real options in the PLS contract can reduce the profit misreporting case. The fact that PLS contracts are riskier compared to other forms of financing such as debt, provides an incentive for the creation of models that reduce their risk to capital providers. Given the results obtained from our real options model, the latter could prove to be of practical use to financial institutions willing to engage in PLS financing.

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“…Scekic et al (2013) used an agent-based model (ABM) to simulate the traffic reporting behavior of the crowd under three different incentive/penalty schemes. For other quantitative studies on crowdsourcing participant management, see Buecheler et al (2011), Zou et al (2014), and Yu et al (2016).…”

Section: Introductionmentioning

confidence: 99%

Reward‐Based Participant Management for Crowdsourcing Rainfall Monitoring: An Agent‐Based Model Simulation

Yang

Cai

2019

Water Resources Research

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Crowdsourcing incorporates common citizens as rich sources of data and is promising for environmental monitoring. In this paper, we propose and test the idea of incorporating incentives to crowdsourcing management for rainfall monitoring. Specifically, we model the allocation of incentives (quantitatively measurable and limited rewards) among crowdsourcing participants for a theoretical rainfall monitoring case. For this purpose, we develop an integrated model comprising a reward allocation component to represent the decision‐making process of a central manager, an agent‐based model to simulate the interactions between the manager and participants, and a rainfall simulation model to evaluate the effectiveness of various reward allocation policies. We simulate six reward allocation policies of varying levels of administrative cost, and consideration of participant and rainfall spatial heterogeneities. The results suggest the performance of each policy to improve with the reward budget and their spatial uniformity. Among the six policies tested, we find that the participant density weighted maximum participation policy yields the most accurate estimation of rainfall intensity due to its more explicit consideration of the spatial distribution of participants; however, this policy associates with a high administrative cost. This highlights the trade‐off between performance and cost in designing effective reward allocation policies. This paper provides a physical and behavior simulation modeling tool to study the feasibility and complexity of reward‐based participant management for crowdsourcing rainfall monitoring. The proposed crowdsourcing method is beneficial for a wide range of applications that require rainfall data with fine resolution, such as storm water management and water availability and biomass assessment for food and energy crops.

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An agent-based model for crowdsourcing systems

Cited by 11 publications

References 10 publications

Agent-Based Modelling: Parallel and Distributed Simulation of Product Development Team

Agent-Based Modelling: Parallel and Distributed Simulation of Product Development Team

Untitled

Reward‐Based Participant Management for Crowdsourcing Rainfall Monitoring: An Agent‐Based Model Simulation

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