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Steps towards an ecology of money infrastructures: materiality and cultures of Ripple

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  • Ludovico Rella

Abstract

Money’s materiality produces an ontological conundrum for social theory: should the analysis of money foreground the objects used as money, or the abstract relations that underpin it? Provoked by the emergence of cryptocurrencies, this paper develops a conceptualization of money as a technological and social infrastructure which directly addresses this theoretical impasse. Cryptocurrencies’ sole form of material existence coincides with their underpinning infrastructure of records, accounting and payments. In the past decade, cryptocurrencies have skyrocketed in number, and they have been applied to a host of use cases. This paper focuses on cross-border payments through the example of the fintech company Ripple, the cryptocurrency XRP, and the design of the XRP Ledger. Combining literatures from the social theory of money, science and technology studies and new materialisms, this article develops steps towards an ecological conceptualization of money infrastructures. Infrastructures, understood ecologically, include devices, active forms, and imaginaries in seamless webs of mutual relations of co-evolution. These ecologies are always potentially prone to slippage, dissolution, disassembling, reassembling and reappropriation, dependence, and competition.

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  • Ludovico Rella, 2020. "Steps towards an ecology of money infrastructures: materiality and cultures of Ripple," Journal of Cultural Economy, Taylor & Francis Journals, vol. 13(2), pages 236-249, March.
    • Handle: RePEc:taf:jculte:v:13:y:2020:i:2:p:236-249
    DOI: 10.1080/17530350.2020.1711532
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    Cited by:

    1. Koray Caliskan, 2022. "The Elephant in the Dark: A New Framework for Cryptocurrency Taxation and Exchange Platform Regulation in the US," JRFM, MDPI, vol. 15(3), pages 1-18, March.
    2. Salzer, Tim, 2024. "A short infrastructural history of currency digitalization in the People’s Republic of China, 2000s-2020s," SocArXiv 5yq4r, Center for Open Science.
    3. Danai Likitratcharoen & Pan Chudasring & Chakrin Pinmanee & Karawan Wiwattanalamphong, 2023. "The Efficiency of Value-at-Risk Models during Extreme Market Stress in Cryptocurrencies," Sustainability, MDPI, vol. 15(5), pages 1-21, March.
    4. Koki, Constandina & Leonardos, Stefanos & Piliouras, Georgios, 2022. "Exploring the predictability of cryptocurrencies via Bayesian hidden Markov models," Research in International Business and Finance, Elsevier, vol. 59(C).

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