Special Issue "Statistical Physics for the Digital Economy"
Deadline for manuscript submissions: closed (31 August 2020).
Interests: complex systems; econophysics; information filtering; mathematical finance; complex networks
Interests: random matrix theory; statistical mechanics; complex systems; legal complexity; quantitative social science
Interests: complex systems; random matrix theory; econophysics
The last decade has witnessed the emergence of an ecosystem of disruptive and intertwined technologies that are accelerating the digitisation of information and increasing connectivity in the economy. In this new “digital economy” era, a substantial portion of online decision making is delegated to interacting algorithms, standard financial intermediaries are replaced by peer-to-peer networks of agents, new purely digital assets and tokens are issued and transferred over decentralised platforms and a large amount of data is made available to business and consumers alike. Technologies driving the change include but are not limited to distributed ledgers, cloud computing and AI.
As the complexity and the size of the digital economies grow, with a large number of agents voluntarily interacting over a large decentralised network, theoretical and computational tools borrowed from statistical physics and complexity science are expected to acquire a paramount role.
This Special Issue welcomes contributions primarily in the following research areas, using standard statistical physics tools (network theory, stochastic processes, phase transitions, information theory and inference, etc.):
- Stability, functioning and vulnerability of peer-to-peer systems, including DLT, blockchains and decentralised marketplaces.
- Impact on the standard banking system of new players (BigTech firms, challenger banks).
- Unintended consequences of algorithmic interaction (e.g., flash crashes caused by automated high-frequency trading algorithms, spread of misinformation fuelled by bot ecosystems).
- Algorithmic bias and its implications (e.g., in online lending platforms)
- Trust and reputation on decentralised platforms.
- Pricing and valuation of nonstandard financial assets and digital tokens.
- Evolution and competition of new technologies and innovations.
- Collective phenomena and dynamics on crowdfunding and peer-to-peer lending platforms.
We welcome more speculative theoretical contributions on innovative and unexplored applications of Statistical physics to all areas of the digital economy.
Prof. Tiziana Di Matteo
Dr. Pierpaolo Vivo
Dr. Giacomo Livan
Dr. Silvia Bartolucci
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- network theory
- peer-to-peer systems
- sharing economy
- digital trust
- reputation systems
- algorithmic interaction
- algorithmic bias
- digital tokens