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Entropy
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Explaining Economic and Social Science Phenomena Through Physical Models, Second...
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Explaining Economic and Social Science Phenomena Through Physical Models, Second Edition

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Multidisciplinary Applications".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 998

Special Issue Editors

Dr. Marcin Makowski

E-Mail Website
Guest Editor
Faculty of Physics, University of Bialystok, ul. Ciołkowskiego 1L, 15-245 Białystok, Poland
Interests: quantum information processing; quantum game theory; econophysics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jan Sładkowski

E-Mail Website
Guest Editor
Institute of Physics, University of Silesia, 75 Pułku Piechoty 1, Pl 41-005 Chorzów, Poland
Interests: quantum field theory; quantum computing; mathematical physics; game theory
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The idea that physics might play an important role in understanding and explaining various aspects of life has long been promoted by physicists in their publications. Examples of such publications include Light and Life (N. Bohr) and What Is Life? (E. Schrödinger). Recently, we have observed growing interest in modeling economic and social phenomena with physical methods. This is because traditional models used, for example, in economics have failed, especially in the face of recent crises. Attempts to find better, more accurate models have led to the emergence of entirely new fields, such as quantum information science related to quantum game theory or, more broadly, econophysics. Searching for new, more precise risk measures seems to be particularly important. Can entropy present advantages as a measure of uncertainty or risk? Do quantum games and quantum information provide us with better tools for modeling social and economic phenomena? The present Special Issue is open to novel contributions on these topics, as well as to others related to them, taking into account the wideness of physics and its applications.

Dr. Marcin Makowski
Prof. Dr. Jan Sładkowski
Guest Editors

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 submissions that pass pre-check are 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 2600 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.

Keywords

  • entropy and fisher information
  • quantum games
  • econophysics
  • decision making/analysis
  • quantum market game
  • quantum-like models
  • social science
  • quantum finances

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Related Special Issue

Published Papers (2 papers)

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Research

22 pages, 779 KiB  
Article
Instability of Financial Time Series Revealed by Irreversibility Analysis
by Youping Fan, Yutong Yang, Zhen Wang and Meng Gao
Entropy 2025, 27(4), 402; https://doi.org/10.3390/e27040402 - 9 Apr 2025
Viewed by 261
Abstract
Since the 2008 global economic crisis, the detection of financial instabilities has garnered extensive research attention, particularly through the application of time-series analysis. In this study, a novel time-series analysis method, integrating the Kullback–Leibler Divergence (KLD) metric with a sliding window technique, is [...] Read more.
Since the 2008 global economic crisis, the detection of financial instabilities has garnered extensive research attention, particularly through the application of time-series analysis. In this study, a novel time-series analysis method, integrating the Kullback–Leibler Divergence (KLD) metric with a sliding window technique, is proposed to detect instabilities in time-series data, especially in financial markets. Global financial time series from 2004 to 2022 were analyzed. The raw time series were preprocessed into return rate series and transformed into complex networks using the directed horizontal visibility graph (DHVG) algorithm, effectively preserving temporal variabilities in network topologies. The KLD method was evaluated through both retrospective analysis and real-time monitoring. It successfully identified idiosyncratic incidents in the financial market, correlating them with specific economic events. Compared to traditional metrics (e.g., moments) and econometric methods, KLD demonstrated superior performance in capturing sequence information and detecting anomalies without requiring linear regression models. Although initially designed for financial data, the KLD method is versatile and can be applied to other types of time series as well. Full article
(This article belongs to the Special Issue Explaining Economic and Social Science Phenomena Through Physical Models, Second Edition)
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20 pages, 15599 KiB  
Article
Quantitative Analysis of Trade Position Shifts of China and the United States in the Indian Ocean Rim Trade Networks Using a Weighted Centrality Approach
by Lihua Yuan, Changqing Song, Xiaoqiang Chen, Manjun Zhang and Menghan Yang
Entropy 2025, 27(3), 262; https://doi.org/10.3390/e27030262 - 1 Mar 2025
Viewed by 651
Abstract
The Indian Ocean Rim (IOR) is a crucial hub for global commerce, possessing key maritime corridors and competitive markets for China and the United States. Assessing the evolving positions of China and the United States in regional trade provides critical insights into their [...] Read more.
The Indian Ocean Rim (IOR) is a crucial hub for global commerce, possessing key maritime corridors and competitive markets for China and the United States. Assessing the evolving positions of China and the United States in regional trade provides critical insights into their economic competition. This study quantitatively investigated their changing positions in the IOR trade networks from 1992 to 2020 through an interdisciplinary approach combining the Fisher optimal segmentation, chord-diagram visualization, and five weighted centrality indicators, including two advanced metrics derived from physical current flow theory. The results reveal a significant shift in their trade positions in the IOR trade networks across four phases (1992–2002, 2003–2008, 2009–2014, and 2015–2020); in particular, the United States occupied a dominant position in the IOR trade networks until 2008, after which China rose to the central trading position, as reflected in its top ranking across four weighted indicators (excluding weighted authority centrality). In machinery and transport equipment (SITC7), China also surpassed the United States in 2008 and further consolidated its supremacy, driven by its strong manufacturing capabilities and the growing demand from the IOR countries. Meanwhile, the United States experienced a noticeable decline but maintained substantial influence as a key importer. This research develops a quantitative framework that integrates the temporal segmentation with weighted centrality indicators to provide insights into the dynamics and structural changes of trade networks across sectors and regions. Full article
(This article belongs to the Special Issue Explaining Economic and Social Science Phenomena Through Physical Models, Second Edition)
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