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Blockchain Technology and Its Potential to Benefit Public Services Provision: A Short Survey

Author

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  • Giorgio Piccardo

    (Department of Business and Management, LUISS University, Viale Romania 32, 00197 Rome, Italy)

  • Lorenzo Conti

    (Department of Business and Management, LUISS University, Viale Romania 32, 00197 Rome, Italy)

  • Alessio Martino

    (Department of Business and Management, LUISS University, Viale Romania 32, 00197 Rome, Italy)

Abstract

In the last few years, blockchain has emerged as a cutting-edge technology whose main advantages are transparency, traceability, immutability, enhanced efficiency, and trust, thanks to its decentralized nature. Although many people still identify blockchain with cryptocurrencies and the financial sector, it has many prospective applications beyond digital currency that can serve as use cases for which traditional infrastructures have become obsolete. Governments have started exploring its potential application to public services provision, as confirmed by the increasing number of adoption initiatives, projects, and tests. As the current public administration is often perceived as slow, bureaucratic, lacking transparency, and failing to involve citizens in decision-making processes, blockchain can establish itself as a tool that enables a process of disintermediation, which can revolutionize the way in which public services are managed and provided. In this paper, we will provide a survey of the main application areas which are likely to benefit from blockchain implementation, together with examples of practical implementations carried out by both state and local governments. Later, we will discuss the main challenges that may prevent its widespread adoption, such as government expenditure, technological maturity, and lack of public awareness. Finally, we will wrap up by providing indications on future areas of research for blockchain-based technologies.

Suggested Citation

  • Giorgio Piccardo & Lorenzo Conti & Alessio Martino, 2024. "Blockchain Technology and Its Potential to Benefit Public Services Provision: A Short Survey," Future Internet, MDPI, vol. 16(8), pages 1-22, August.
    • Handle: RePEc:gam:jftint:v:16:y:2024:i:8:p:290-:d:1453570
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    References listed on IDEAS

    as
    1. Jarrahi, Mohammad Hossein, 2018. "Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making," Business Horizons, Elsevier, vol. 61(4), pages 577-586.
    2. Carmen ROTUNA & Alexandru GHEORGHITA & Alin ZAMFIROIU & Dragos-Marian SMADA, 2019. "Smart City Ecosystem Using Blockchain Technology," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 23(4), pages 41-50.
    3. Thomas K. Dasaklis & Theodore G. Voutsinas & Giannis T. Tsoulfas & Fran Casino, 2022. "A Systematic Literature Review of Blockchain-Enabled Supply Chain Traceability Implementations," Sustainability, MDPI, vol. 14(4), pages 1-30, February.
    4. Igor Radanović & Robert Likić, 2018. "Opportunities for Use of Blockchain Technology in Medicine," Applied Health Economics and Health Policy, Springer, vol. 16(5), pages 583-590, October.
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