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Systems
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Data Analytics for Social, Economic and Environmental Issues
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Data Analytics for Social, Economic and Environmental Issues

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 1893

Special Issue Editors

Dr. Martins Adelaide

E-Mail Website
Guest Editor
CEF.UP, Faculty of Economics, University of Porto, Rua Dr Roberto Frias s/n, 4200-464 Porto, Portugal
Interests: accountability and impression management; sustainability and non-financial reporting; accounting and the state; accounting education; accounting in the era of big data
Dr. Susana Silva

E-Mail Website
Guest Editor
CEF.UP, Faculty of Economics, University of Porto, Rua Dr Roberto Frias s/n, 4200-464 Porto, Portugal
Interests: data analytics regarding economic, social, and environmental issues; policy making; sustainability
Special Issues, Collections and Topics in MDPI journals
Dr. Bruno Veloso

E-Mail Website
Guest Editor
LIAAD—INESC TEC, Faculty of Economics, University of Porto, Rua Dr Roberto Frias s/n, 4200-464 Porto, Portugal
Interests: data science; machine learning; data streams; AUTOML

Special Issue Information

Dear Colleagues,

Data are being generated at a much faster rate, and the volume of data being collected in business, engineering, science, and other fields is much greater than ever before. This has huge implications for data-related issues. Data analytics (DA) is becoming increasingly important in all aspects of business management and a major area of study for both practitioners and researchers. The application of DA techniques and tools to analyze large and complex data for various applications can help organizations harness vast amounts of data to gain actionable insights and uncover useful information for making informed decisions across business processes while adjusting to consumer preferences. Through DA, organizations and policy makers can gain valuable insights by analyzing trends, patterns, and citizen/consumer behaviors with implications for social, economic, and environmental performance.

This Special Issue will contribute to a better and more comprehensive understanding of DA in the social, economic, and environmental dimensions of the business landscape.

  • Data governance in a DA-driven world;
  • DA capabilities as a reporting enabler;
  • DA and the supply chain;
  • DA to predict and achieve social, economic, and environmental goals;
  • DA and environmental changes;
  • DA predicting consumer behavior and adapting marketing strategies;
  • DA in second-hand markets as a driver of sustainability;
  • DA and the circular economy.

Dr. Martins Adelaide
Dr. Susana Silva
Dr. Bruno Veloso
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. Systems 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 2400 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

  • data analytics
  • big data
  • data governance
  • information systems
  • social, economic, and environmental dimensions
  • behavioral trends
  • reporting
  • economic analysis and forecast

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

Published Papers (2 papers)

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Research

28 pages, 16929 KiB  
Article
Spatial–Temporal Coupling and Interactive Effects of Reclaimed Water Usage Efficiency and High-Quality Development of the Financial Sector
by Ying Zhou, Fengping Wu, Gen Li and Chen Feng
Systems 2025, 13(2), 137; https://doi.org/10.3390/systems13020137 - 19 Feb 2025
Viewed by 476
Abstract
In China, the current policy of the financial sector on water conservation and management is being vigorously pursued; therefore, efficient synergy between the two systems is of great significance. In this study, the coupling and coordination degree (CCD) between reclaimed water usage efficiency [...] Read more.
In China, the current policy of the financial sector on water conservation and management is being vigorously pursued; therefore, efficient synergy between the two systems is of great significance. In this study, the coupling and coordination degree (CCD) between reclaimed water usage efficiency (RWUE) and high-quality development of the financial sector (HQDFS) was assessed using a coupling coordination model with panel data from 27 provinces in China during 2010–2021, and a more in-depth coupling and coordination relationship (CCR) was carried out using a spatiotemporal evolution methodology and PVAR model. The results of this study show the following: (1) CCD exhibits a continuous upward trajectory. At the end of the study period, the eastern, central, western, and northeastern regions moved to the primary coordination level. (2) The eastern and northeastern regions show an increasing trend in absolute differences and polarization. Meanwhile, the central region experiences a gradual rise in polarization. (3) The elliptical plot of the CCD’s standard deviation tends toward a circular shape with a positive aspect ratio. An expanding trend of absolute differences and polarization is observed in the eastern and northeastern regions. (4) The PVAR results show that the two systems can promote each other in the early stages and have a negative impact in the later stages. This study provides policy recommendations for a balanced development of the two systems and the formulation of regional development strategies based on the state of coupling and coordination between the two. Full article
(This article belongs to the Special Issue Data Analytics for Social, Economic and Environmental Issues)
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29 pages, 5916 KiB  
Article
The Coordinated Development and Identification of Obstacles in the Manufacturing Industry Based on Economy–Society–Resource–Environment Goals
by Jiaojiao Yang, Ting Wang, Min Zhang, Yujie Hu and Xinran Liu
Systems 2025, 13(2), 78; https://doi.org/10.3390/systems13020078 - 26 Jan 2025
Viewed by 776
Abstract
Given the deficiencies in the definition of connotation, the construction of index systems, and the coordination of targets within the research on sustainable development in the manufacturing industry, an evaluation index system for sustainable development has been established. This system includes economic benefits, [...] Read more.
Given the deficiencies in the definition of connotation, the construction of index systems, and the coordination of targets within the research on sustainable development in the manufacturing industry, an evaluation index system for sustainable development has been established. This system includes economic benefits, social benefits, resource management, and environmental goals and is built upon a clear definition of the concept’s connotation. The CRITIC–entropy–TOPSIS–CCDM approach is employed for the computation of the coordinated development level of the manufacturing industry. To identify the main factors influencing the coupling coordination degree (CCD) from a mechanistic and compositional point of view, a logarithmic mean divisia index (LMDI) is used. Furthermore, the obstacle degree model analyzes the factors that restrict subsystem development. The results show the following. (1) The coordinated development level of the Chinese manufacturing industry has been maintained at 0.6–0.7, while the CCD of Hainan, Qinghai, and Xinjiang remains to be enhanced. (2) The key factor affecting the CCD is the coupling degree. The evaluation value of the economy and employment system determines the trend of coordinated development in the regional manufacturing industry. (3) The economic and employment scenarios in most provinces (cities) led to a significant decrease in the CCD compared to the baseline scenario, with average growth rates of −10.55% and −12.69%. This suggests that policymakers’ priorities significantly influence the CCD. The research presents a theoretical framework for assessing the sustainability of the manufacturing industry, offering valuable insights to guide the industry towards more sustainable practices. Full article
(This article belongs to the Special Issue Data Analytics for Social, Economic and Environmental Issues)
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