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Entropy, Econophysics, and Complexity

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

Deadline for manuscript submissions: 30 May 2025 | Viewed by 2742

Special Issue Editors


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Guest Editor
Research Institute on Artificial Intelligence, Universidad Veracruzana, Xalapa Veracruz 91000, Mexico
Interests: statistical physics; complex systems; econophysics and finance; stochastic processes and computational physics

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Guest Editor
Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Cuernavaca 62210, Mexico
Interests: physics; random matrix theory; decoherence; quantitative finance; multivariate analysis

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Guest Editor
Department of Economics and Business, University of Almería, 04120 Almería, Spain
Interests: long memory; portfolio theory; fractal dimension; financial markets; econophysics
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Cuernavaca 62210, Mexico
Interests: many-body physics; quantum chaos; random matrix theory; quantum information science; multivariate analysis

Special Issue Information

Dear Colleagues,

We present this Special Issue on Entropy, aimed to explore the new and potential applications and connections that Entropy, Econophysics, and Complexity have on understanding the dynamics of Economic and Social Complex systems.

Econophysics offers a new approach for considering financial markets and the economy by applying Statistical Physics, Computer Science, Based Agents Simulations, Data Analysis, and other methodologies. This contributes to the understanding of Economic and Social Complex systems by examining their patterns, dynamics, and large-scale behaviors. Additionally, Entropy, a concept in thermodynamics and information theory, has found significant applications in the economy, providing insights into the unpredictability of markets and information processing in Economic Complex Systems.

This Special Issue collects articles that apply Entropy, Econophysics Methodologies, and Complexity Theory for Economic phenomena analysis. Contributions may range from theoretical studies, like those proposing new methods for assessing  Economic Complex Systems, to empirical studies that show novel analyses and new properties of financial markets and Social and  Economic Complex Systems.

We also intend to construct an interdisciplinary forum for these fields by connecting Economics, Physics, and Complex Systems Theory practitioners interested in these topics.

Dr. Alejandro Raúl Hernández-Montoya
Prof. Dr. Thomas  Seligman
Prof. Dr. J.E. Trinidad-Segovia
Dr. Manan Vyas
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

  • stylized facts
  • econophysics
  • sociophysics
  • entropy
  • financial markets
  • wealth distribution
  • inequality
  • financial crisis

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Published Papers (4 papers)

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Research

25 pages, 4731 KiB  
Article
Analysis of Core–Periphery Structure Based on Clustering Aggregation in the NFT Transfer Network
by Zijuan Chen, Jianyong Yu, Yulong Wang and Jinfang Xie
Entropy 2025, 27(4), 342; https://doi.org/10.3390/e27040342 - 26 Mar 2025
Viewed by 50
Abstract
With the rise of blockchain technology and the Ethereum platform, non-fungible tokens (NFTs) have emerged as a new class of digital assets. The NFT transfer network exhibits core–periphery structures derived from different partitioning methods, leading to local discrepancies and global diversity. We propose [...] Read more.
With the rise of blockchain technology and the Ethereum platform, non-fungible tokens (NFTs) have emerged as a new class of digital assets. The NFT transfer network exhibits core–periphery structures derived from different partitioning methods, leading to local discrepancies and global diversity. We propose a core–periphery structure characterization method based on Bayesian and stochastic block models (SBMs). This method incorporates prior knowledge to improve the fit of core–periphery structures obtained from various partitioning methods. Additionally, we introduce a locally weighted core–periphery structure aggregation (LWCSA) scheme, which determines local aggregation weights using the minimum description length (MDL) principle. This approach results in a more accurate and representative core–periphery structure. The experimental results indicate that core nodes in the NFT transfer network constitute approximately 2.3–5% of all nodes. Compared to baseline methods, our approach improves the normalized mutual information (NMI) index by 6–10%, demonstrating enhanced structural representation. This study provides a theoretical foundation for further analysis of the NFT market. Full article
(This article belongs to the Special Issue Entropy, Econophysics, and Complexity)
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23 pages, 11439 KiB  
Article
Enterprise Digital Transformation Strategy: The Impact of Digital Platforms
by Qiong Huang and Yifan Tang
Entropy 2025, 27(3), 295; https://doi.org/10.3390/e27030295 - 12 Mar 2025
Viewed by 368
Abstract
The development of the digital economy is a strategic choice for seizing new opportunities in the latest wave of technological revolution and industrial transformation. As a critical tool for driving the digital transformation of enterprises, digital platforms play a pivotal role in this [...] Read more.
The development of the digital economy is a strategic choice for seizing new opportunities in the latest wave of technological revolution and industrial transformation. As a critical tool for driving the digital transformation of enterprises, digital platforms play a pivotal role in this process. This study employs the evolutionary game theory of complex networks to develop a game model for the digital transformation of enterprises and utilizes the Fermi rule from sociophysics to characterize the evolution of enterprise strategies. Throughout this process, the interactive behaviors and strategic choices of enterprises embody the features of information flow and dynamic adjustment within the network. These features are crucial for elucidating the complexity and uncertainty inherent in strategic decision-making. The research findings indicate that digital platforms, through the provision of high-quality services and the implementation of effective pricing strategies, can significantly reduce the costs associated with digital transformation, thereby enhancing operational efficiency and innovation capacity. Moreover, the model reveals the competitive relationships between enterprises and their impact on transformation strategies, offering theoretical insights for policymakers. Based on these findings, the paper proposes policy recommendations such as strengthening infrastructure, implementing differentiated service strategies, and enhancing decision-making capability training, with the aim of supporting the digital transformation of enterprises across various industries and promoting sustainable development. Full article
(This article belongs to the Special Issue Entropy, Econophysics, and Complexity)
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24 pages, 595 KiB  
Article
A Network Analysis of the Impact of the Coronavirus Pandemic on the US Economy: A Comparison of the Return and the Momentum Picture
by Janusz Miśkiewicz
Entropy 2025, 27(2), 148; https://doi.org/10.3390/e27020148 - 1 Feb 2025
Viewed by 500
Abstract
This study examines a cross-correlation analysis of companies included in the S&P 500 Index at three different intervals: before, during, and after the pandemic’s onset. The aim is to evaluate how the pandemic and related governmental actions have affected market structures and economic [...] Read more.
This study examines a cross-correlation analysis of companies included in the S&P 500 Index at three different intervals: before, during, and after the pandemic’s onset. The aim is to evaluate how the pandemic and related governmental actions have affected market structures and economic conditions. This paper introduces the notion of momentum time series, integrating return and volume data. We show that these momentum time series provide unique insights that differ from return time series, suggesting their potential utility in economic analysis. Our analysis employs the Manhattan and Mantegna distances to construct a threshold-based network, which we subsequently scrutinize. Lastly, we evaluate how the pandemic has influenced these outcomes. Full article
(This article belongs to the Special Issue Entropy, Econophysics, and Complexity)
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27 pages, 1556 KiB  
Article
Environmental Performance, Financial Constraints, and Tax Avoidance Practices: Insights from FTSE All-Share Companies
by Probowo Erawan Sastroredjo, Marcel Ausloos and Polina Khrennikova
Entropy 2025, 27(1), 89; https://doi.org/10.3390/e27010089 - 18 Jan 2025
Viewed by 1215
Abstract
Through its initiative known as the Climate Change Act (2008), the Government of the United Kingdom encourages corporations to enhance their environmental performance with the significant aim of reducing targeted greenhouse gas emissions by the year 2050. Previous research has predominantly assessed this [...] Read more.
Through its initiative known as the Climate Change Act (2008), the Government of the United Kingdom encourages corporations to enhance their environmental performance with the significant aim of reducing targeted greenhouse gas emissions by the year 2050. Previous research has predominantly assessed this encouragement favourably, suggesting that improved environmental performance bolsters governmental efforts to protect the environment and fosters commendable corporate governance practices among companies. Studies indicate that organisations exhibiting strong corporate social responsibility (CSR), environmental, social, and governance (ESG) criteria, or high levels of environmental performance often engage in lower occurrences of tax avoidance. However, our findings suggest that an increase in environmental performance may paradoxically lead to a rise in tax avoidance activities. Using a sample of 567 firms listed on the FTSE All Share from 2014 to 2022, our study finds that firms associated with higher environmental performance are more likely to avoid taxation. The study further documents that the effect is more pronounced for firms facing financial constraints. Entropy balancing, propensity score matching analysis, the instrumental variable method, and the Heckman test are employed in our study to address potential endogeneity concerns. Collectively, the findings of our study suggest that better environmental performance helps explain the variation in firms’ tax avoidance practices. Full article
(This article belongs to the Special Issue Entropy, Econophysics, and Complexity)
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