The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Blockchain and Smart Contracts for Insurance: Is the Technology Mature Enough?
Open accessAbstract
Blockchain is receiving increasing attention from academy and industry, since it is considered a breakthrough technology that could bring huge benefits to many different sectors. In 2017, Gartner positioned blockchain close to the peak of inflated expectations, acknowledging the enthusiasm for this technology that is now largely discussed by media. In this scenario, the risk to adopt it in the wake of enthusiasm, without objectively judging its actual added value is rather high. Insurance is one the sectors that, among others, started to carefully investigate the possibilities of blockchain. For this specific sector, however, the hype cycle shows that the technology is still in the innovation trigger phase, meaning that the spectrum of possible applications has not been fully explored yet. Insurers, as with many other companies not necessarily active only in the financial sector, are currently requested to make a hard decision, that is, whether to adopt blockchain or not, and they will only know if they were right in 3–5 years. The objective of this paper is to support actors involved in this decision process by illustrating what a blockchain is, analyzing its advantages and disadvantages, as well as discussing several use cases taken from the insurance sector, which could easily be extended to other domains.
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Cites
Blockchains and smart contracts for the internet of things
Christidis, K., & Devetsikiotis, M. (2016) · IEEE Access · doi:10.1109/access.2016.2566339 · Cited by 4,552
A Survey of Attacks on Ethereum Smart Contracts (SoK)
Atzei, N., Bartoletti, M., & Cimoli, T. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-662-54455-6_8 · Cited by 1,553
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Monrat, A. A., Schelen, O., & Andersson, K. (2019) · IEEE Access · doi:10.1109/access.2019.2936094 · Cited by 1,077
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A Trustworthy Privacy Preserving Framework for Machine Learning in Industrial IoT Systems
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Astarita, V., Giofrè, V. P., Mirabelli, G., & Solina, V. (2019) · Information · doi:10.3390/info11010021 · Cited by 180
Eling, M., Nuessle, D., & Staubli, J. (2022) · The Geneva Papers on Risk and Insurance Issues and Practice · doi:10.1057/s41288-020-00201-7 · Cited by 156
Ziolkowski, R., Miscione, G., & Schwabe, G. (2020) · Journal of Management Information Systems · doi:10.1080/07421222.2020.1759974 · Cited by 151
Security Aspects of Blockchain Technology Intended for Industrial Applications
Idrees, S. M., Nowostawski, M., Jameel, R., & Mourya, A. K. (2021) · Electronics · doi:10.3390/electronics10080951 · Cited by 127
Yang, J., Onik, M. M. H., Lee, N.-Y., Ahmed, M., & Kim, C.-S. (2019) · Applied Sciences · doi:10.3390/app9071370 · Cited by 91
Alcarria, R., Bordel, B., Robles, T., Martín, D., & Manso-Callejo, M.-Á. (2018) · Sensors · doi:10.3390/s18103561 · Cited by 81
Metadata
- Authors
- Gatteschi, V., Lamberti, F., Demartini, C., Pranteda, C., & Santamaría, V.
- Venue
- Future Internet
- Publisher
- MDPI AG
- Published
- 2018-02-20
- Volume
- 10
- Issue
- 2
- Pages
- 20
- ISSN
- 1999-5903 (ISSN-L)
- OpenAlex
- W2793333522
- Cited by
- 516
- References
- 2
- FWCI
- 96.41
- Type
- journal article
- Language
- en
- Open access
- gold
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