Abstract

Technologically enabled sharing-economy networks are changing the way humans trade and collaborate. Here, using a novel ‘Wi-Fi sharing’ game, we explored determinants of human sharing strategy. Subjects (N = 1,950) participated in a networked game in which they could choose how to allocate a limited, but personally not usable, resource (representing unused Wi-Fi bandwidth) to immediate network neighbors. We first embedded N = 600 subjects into 30 networks, experimentally manipulating the range over which subjects could connect. We find that denser networks decrease any wealth inequality, but that this effect saturates. Individuals’ benefit is shaped by their network position, with having many partners who in turn have few partners being especially beneficial. We propose a new, simplified “sharing centrality” metric for quantifying this. Further experiments (N = 1,200) confirm the robustness of the effect of network structure on sharing behavior. Our findings suggest the possibility of interventions to help more evenly distribute shared resources over networks.

Resource sharing over peer-to-peer technological networks is emerging as economically important, yet little is known about how people choose to share in this context. Here, the authors introduce a new game to model sharing, and test how players form sharing strategies depending on technological constraints.

Details

Title
Resource sharing in technologically defined social networks
Author
Shirado Hirokazu 1 ; Iosifidis, George 2 ; Tassiulas Leandros 3 ; Christakis, Nicholas A 4   VIAFID ORCID Logo 

 Yale University, Yale Institute for Network Science, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710); Yale University, Department of Sociology, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
 Trinity College Dublin, School of Computer Science and Statistics, Dublin, Ireland (GRID:grid.8217.c) (ISNI:0000 0004 1936 9705); SFI Research Centre CONNECT, Dublin, Ireland (GRID:grid.437854.9) (ISNI:0000 0004 0452 5752) 
 Yale University, Yale Institute for Network Science, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710); Yale University, Department of Electrical Engineering, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
 Yale University, Yale Institute for Network Science, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710); Yale University, Department of Sociology, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710); Yale University, Department of Biomedical Engineering, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
Publication year
2019
Publication date
Dec 2019
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2188581871
Copyright
This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.