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Advances in Statistical Analysis for Health, Finance, Industry and Digital...
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Advances in Statistical Analysis for Health, Finance, Industry and Digital Economy

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D1: Probability and Statistics".

Deadline for manuscript submissions: 1 July 2025 | Viewed by 7965

Special Issue Editor

Prof. Dr. Lei Qin

E-Mail Website
Guest Editor
School of Statistics, University of International Business and Economics, Beijing, China
Interests: data mining; health data analysis; digital economy

Special Issue Information

Dear Colleagues,

Emerging sectors such as health, finance, industry and digital economy increasingly rely on complex data to address challenges and drive innovation. As the volume and variety of data continue to grow exponentially, the need for sophisticated statistical methods and analytical tools becomes imperative. However, advanced analytics applications often lag behind theoretical developments, especially in interdisciplinary research and practical applications.

This Special Issue aims to bridge this gap by soliciting contributions demonstrating the integration of cutting-edge statistical methods and novel applications. We welcome submissions from researchers, practitioners and academics at the forefront of data analysis in these fields. This Special Issue will provide a platform for exchanging ideas and disseminating knowledge, leading to meaningful advances in health, finance, industry and digital economy.

Prof. Dr. Lei Qin
Guest Editor

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. Mathematics is an international peer-reviewed open access semimonthly 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

  • application of data mining
  • machine learning and optimization
  • generative AI
  • artificial intelligence in healthcare
  • health economics
  • bioinformatics
  • digital driven diagnostics and prognostics
  • option pricing
  • market microstructure
  • cryptocurrency
  • blockchain
  • digital economy
  • data assets

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

36 pages, 732 KiB  
Article
The Impact of Digital Transformation on High-Quality Development of Manufacturing Enterprises: An Integrated Perspective on Efficiency and Social Responsibility
by Xing Liu, Shaobo Hong, Zhi Su and Yuanren Zhou
Mathematics 2025, 13(5), 815; https://doi.org/10.3390/math13050815 - 28 Feb 2025
Viewed by 767
Abstract
With the rise of a new wave of technological revolution and industrial transformation, digital technology has become a key force driving global economic and social development. Digital technology holds significant advantages in promoting industrial transformation and upgrading, as well as facilitating the high-quality [...] Read more.
With the rise of a new wave of technological revolution and industrial transformation, digital technology has become a key force driving global economic and social development. Digital technology holds significant advantages in promoting industrial transformation and upgrading, as well as facilitating the high-quality development of manufacturing enterprises. This study selects 482 manufacturing enterprises in the Shanghai and Shenzhen A-share markets from 2010 to 2022 as samples and comprehensively measures the high-quality development level of enterprises from the two dimensions of production efficiency and social responsibility. Based on this, a two-way fixed effect model is used to test the impact of digital technology on the high-quality development of manufacturing enterprises. The results show that the digital transformation of manufacturing enterprises enhances their level of high-quality development by improving production efficiency and strengthening social responsibility. This conclusion remains robust after a series of robustness checks. The mechanism analysis reveals that digitalization influences the high-quality development of manufacturing enterprises by altering financing costs, innovation output, and human capital. The heterogeneity analysis indicates that this impact varies significantly across ownership types, industries, and regions. Therefore, further efforts should be made to promote the digital transformation of manufacturing enterprises, strengthen technological innovation, enhance talent cultivation, and promote industrial integration, thereby leveraging digital technology to significantly improve high-quality development levels. Full article
(This article belongs to the Special Issue Advances in Statistical Analysis for Health, Finance, Industry and Digital Economy)
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27 pages, 529 KiB  
Article
The Impact of Digital Economy Development on Regional Income Gaps: A Perspective on Multidimensional Inequality Decomposition and Threshold Effects
by Jing Ruan, Lu Zou, Ruiqi Liu and Hongyun Pan
Mathematics 2024, 12(24), 4024; https://doi.org/10.3390/math12244024 - 22 Dec 2024
Viewed by 1367
Abstract
This paper investigates the impact of digital economy development on regional income gaps within provinces in China, focusing on the underlying mechanisms and multidimensional threshold effects. Using provincial panel data from 2011 to 2021, this study finds that the relationship between digital economy [...] Read more.
This paper investigates the impact of digital economy development on regional income gaps within provinces in China, focusing on the underlying mechanisms and multidimensional threshold effects. Using provincial panel data from 2011 to 2021, this study finds that the relationship between digital economy development and income gaps follows a U-shape, initially reducing the gap and later widening it. This analysis identifies internet penetration and digital transaction growth as key contributors to multidimensional inequality in digital economy development. Moreover, moderate levels of multidimensional inequality in digital economy development enhance its positive effect on narrowing regional income gaps, while excessive multidimensional inequality may diminish or even reverse this effect. These findings highlight the importance of managing multidimensional inequality to maximize digital economies’ potential for fostering more balanced regional development. Full article
(This article belongs to the Special Issue Advances in Statistical Analysis for Health, Finance, Industry and Digital Economy)
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17 pages, 2553 KiB  
Article
Technology Empowers Finance: Boundaries and Risks
by Zheng Ji, Xiaoqi Zhang, Han Liang and Yang Lyu
Mathematics 2024, 12(21), 3394; https://doi.org/10.3390/math12213394 - 30 Oct 2024
Viewed by 1073
Abstract
BigTech credit has enhanced financial inclusion, but it also poses concerns with its boundaries. This article uses theoretical frameworks and numerical simulations to examine the risks and inclusiveness of technology-empowered credit services for “long-tail” clients. This research discovered that the discrepancy between the [...] Read more.
BigTech credit has enhanced financial inclusion, but it also poses concerns with its boundaries. This article uses theoretical frameworks and numerical simulations to examine the risks and inclusiveness of technology-empowered credit services for “long-tail” clients. This research discovered that the discrepancy between the commercial boundaries of BigTech credit and the technical limitations of risk management poses a risk in BigTech credit. The expanding boundaries of BigTech’s credit business may mitigate the representativeness of the data, resulting in a systematic deviation of unclear characteristics from the training sample data, which reduces the risk-control model’s ability to identify long-tail customers and raises the risk of credit defaults. Further computer simulations validate these results and demonstrate that competition among various companies would expedite the market’s transition over the boundary in case of a capital shortage. Finally, this article proposes setting up a joint-stock social unified credit technology company with data assets as an investment to facilitate the healthy and orderly development of financial technology institutions. Full article
(This article belongs to the Special Issue Advances in Statistical Analysis for Health, Finance, Industry and Digital Economy)
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30 pages, 2330 KiB  
Article
A New Framework, Measurement, and Determinants of the Digital Divide in China
by Yuanren Zhou, Menggen Chen, Xiaojie Liu and Yun Chen
Mathematics 2024, 12(14), 2171; https://doi.org/10.3390/math12142171 - 11 Jul 2024
Cited by 2 | Viewed by 2494
Abstract
The digital divide (DD) reflects the inequality of the digital economy, while existing research lacks a comprehensive framework for investigating the measurement of DD and its determinants. This study constructs a new framework with a five-dimensional comprehensive index system. City-level data are used [...] Read more.
The digital divide (DD) reflects the inequality of the digital economy, while existing research lacks a comprehensive framework for investigating the measurement of DD and its determinants. This study constructs a new framework with a five-dimensional comprehensive index system. City-level data are used to measure China’s DD index from 2010 to 2020 at the national, regional, and provincial levels. Furthermore, this study investigates the decomposition of DD at both regional and provincial levels and the determinants of DD from the perspectives of physical, human, and social capital. The key results are: (1) China’s DD has generally exhibited a fluctuating downward trend. While it remains high in the eastern and western regions, it has shown a decline year by year. However, the DD within most provinces is on the rise. (2) The intra-regional and inter-provincial are the primary drivers of changes in national DD, with both intra-regional and intra-provincial contribution rates on the rise. (3) Economic growth, infrastructure, foreign trade, education, and online interaction significantly impact DD, and these determinants may change at different periods. This study intends to provide empirical support for bridging the DD, fostering the balanced development of the digital economy, and reducing social inequality. Full article
(This article belongs to the Special Issue Advances in Statistical Analysis for Health, Finance, Industry and Digital Economy)
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