Location

Grand Wailea, Hawaii

Event Website

https://hicss.hawaii.edu/

Start Date

8-1-2019 12:00 AM

End Date

11-1-2019 12:00 AM

Description

The widespread availability of digital ecosystems and networking tools have supported the emergence of the sharing economy, and in particular, social support networks that enable collaborative consumption. This paper proposes an agent-based simulation to shed light on how information sharing dynamics can affect the decision-making process and outcomes of asset sharing online communities. The model considers the online community as a complex system of cognitive and tangible networks, and provides a platform to evaluate architectural choices in the design process of digital platforms. It is grounded on a cognitive model of dependence networks and provides a means for modeling the dynamics of collaborative consumption in digital social support networks. The results of four simulation runs are analyzed and discussed, providing insights regarding the potentiality of this approach and the effect of behavioral rules on agents’ outcomes and decision-making patterns.

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Jan 8th, 12:00 AM Jan 11th, 12:00 AM

Networks dynamics and information sharing: an agent-based simulation approach for the sharing economy

Grand Wailea, Hawaii

The widespread availability of digital ecosystems and networking tools have supported the emergence of the sharing economy, and in particular, social support networks that enable collaborative consumption. This paper proposes an agent-based simulation to shed light on how information sharing dynamics can affect the decision-making process and outcomes of asset sharing online communities. The model considers the online community as a complex system of cognitive and tangible networks, and provides a platform to evaluate architectural choices in the design process of digital platforms. It is grounded on a cognitive model of dependence networks and provides a means for modeling the dynamics of collaborative consumption in digital social support networks. The results of four simulation runs are analyzed and discussed, providing insights regarding the potentiality of this approach and the effect of behavioral rules on agents’ outcomes and decision-making patterns.

https://aisel.aisnet.org/hicss-52/cl/distributed_group_decision-making/4