Abstract

From decentralized banking systems to digital community currencies, the way humans perceive and use money is changing1,2,3, thus creating novel opportunities for solving important economic and social problems. Here, we study Sardex, a fast-growing community currency in Sardinia (involving 1,477 businesses arrayed in a network with 48,170 transactions) using network analysis to shed light on its operation. Based on our experience with its day-to-day operations, we propose performance metrics tailored for Sardex but also to similar economic systems, introduce criteria for identifying prominent economic actors and investigate the interplay between network structure and economic robustness. Leveraging new methods for quantifying network ‘cyclic density’ and ‘k-cycle centrality,’ we show that geodesic transaction cycles, where money flows in a circle through the network, are prevalent and that certain nodes have a pivotal role in them. We analyse the transactions within cycles and find that the economic turnover of the involved firms is higher, and that excessive currency and debt accumulations are lower. We also measure a similar, but secondary, effect for nodes and edges that serve as intermediaries to many transactions. These metrics are strong indicators of the success of such mutual credit systems at individual and collective levels.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request, subject to approval by Sardex Spa and based on the confidentiality agreement of Sardex Spa with its clients.

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Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Acknowledgements

We thank D. G. Alvarez, F. Fu, J. Horton and A. Oswald for helpful comments. Support for this research was provided by a grant from the Robert Wood Johnson Foundation and the Star Family Foundation. Also, G.I. acknowledges that this publication has emanated from research supported in part by a research grant from Science Foundation Ireland under grant 16/IA/4610; and E.M.A. acknowledges the support by the National Science Foundation under grant IIS-1409177 and by the Office of Naval Research under grants YIP N00014-14-1-0485 and N00014-17-1-2131 to E.M.A. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Author notes

  1. These authors contributed equally: G. Iosifidis and Y. Charette.

Affiliations

  1. School of Computer Science and Statistics, Trinity College Dublin, Dublin, Ireland

    • George Iosifidis
  2. School of Social Work and Criminology, Laval University, Quebec City, Quebec, Canada

    • Yanick Charette
  3. Department of Statistical Science, Fox School of Business, Temple University, Philadelphia, PA, USA

    • Edoardo M. Airoldi
  4. Institute for Quantitative Social Sciences, Harvard University, Cambridge, MA, USA

    • Edoardo M. Airoldi
  5. Sardex Spa, Sardinia, Italy

    • Giuseppe Littera
  6. Yale Institute for Network Science, Yale University, New Haven, CT, USA

    • Leandros Tassiulas
    •  & Nicholas A. Christakis
  7. Department of Electrical Engineering, Yale University, New Haven, CT, USA

    • Leandros Tassiulas
  8. Department of Sociology, Yale University, New Haven, CT, USA

    • Nicholas A. Christakis
  9. Department of Biomedical Engineering, Yale University, New Haven, CT, USA

    • Nicholas A. Christakis
  10. School of Organization and Management, Yale University, New Haven, CT, USA

    • Nicholas A. Christakis

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Contributions

G.I., Y.C., L.T. and N.A.C. designed the project. G.I. and G.L. prepared the data. G.I. and Y.C. performed the statistical analyses. G.I., Y.C., E.M.A., L.T. and N.A.C. analysed the findings. G.I., Y.C., E.M.A., G.L., L.T. and N.A.C. wrote the manuscript.

Competing Interests

G.L. is one of the founders and currently an employee of Sardex Spa.

Corresponding author

Correspondence to George Iosifidis.

Supplementary information

  1. Supplementary Information

    Supplementary Notes 1–4, Supplementary Tables 1–23, Supplementary Figures 1–14, Supplementary References

  2. Reporting Summary

  3. Supplementary Software

    Supplementary Code 1–7

  4. Supplementary Video 1

    Edges creation in Sassari during 2013. The nodes represent businesses that are located in Sassari, and the edges depict their trading relationships (one or more transactions). The video presents the edges in a temporal sequence

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DOI

https://doi.org/10.1038/s41562-018-0450-0