Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.8
3.3
Journals
Sustainability
Special Issues
AI for Sustainable Development: Applications and Impacts across Industries
sustainability-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Sustainability Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

AI for Sustainable Development: Applications and Impacts across Industries

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Products and Services".

Deadline for manuscript submissions: 30 April 2025 | Viewed by 1229

Special Issue Editors

Prof. Dr. Ahreum Hong

E-Mail Website
Guest Editor
Graduate School of Technology Management, Kyung Hee University, Seoul, Republic of Korea
Interests: artificial intelligence in sustainable technology management; digital transformation and innovation in emerging markets; data-driven decision making for environmental sustainability
Prof. Dr. Yannan Li

E-Mail Website
Guest Editor
Graduate School of Technology Management, Kyung Hee University, Seoul, Republic of Korea
Interests: AI and sustainable development; environmental policy and AI integration; human resource management and AI technologies

Special Issue Information

Dear Colleagues,

The Special Issue on “AI for Sustainable Development: Applications and Impacts across Industries” aims to explore how Artificial Intelligence (AI) is revolutionizing various sectors to support the achievement of sustainable development goals (SDGs). This issue invites research that examines the application of AI in promoting sustainability across diverse domains such as energy, agriculture, urban planning, and resource management. This Special Issue seeks to contribute to a deeper understanding of how AI can be harnessed to address global environmental and societal challenges by bridging the gap between AI innovation and sustainable practices. We encourage submissions that provide empirical evidence, methodological advancements, and theoretical perspectives on integrating AI technologies to foster sustainable development. The goal is to advance interdisciplinary research highlighting AI’s potential to drive progress toward a more sustainable future.

Prof. Dr. Ahreum Hong
Prof. Dr. Yannan Li
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. Sustainability 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 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

  • artificial intelligence
  • AI applications
  • economics in AI
  • ethics in AI
  • educational AI
  • transportation AI
  • machine learning
  • domain-specific AI
  • interdisciplinary research

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • 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 polices can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

24 pages, 1930 KiB  
Article
The Impact of Rainfall on Water, Energy, Industry and Economic Growth—Based on Empirical Data from 29 Provinces in China
by Yuan Gao, Qiqi Xiao and Zhong Fang
Sustainability 2025, 17(1), 40; https://doi.org/10.3390/su17010040 - 25 Dec 2024
Abstract
Sustainable urban development requires good interaction between water, energy, infrastructure and socio-economic areas. In the context of more frequent heavy rainfall and flooding events, managing the subsystems within the city in an integrated manner and realizing sustainable development have become popular research topics. [...] Read more.
Sustainable urban development requires good interaction between water, energy, infrastructure and socio-economic areas. In the context of more frequent heavy rainfall and flooding events, managing the subsystems within the city in an integrated manner and realizing sustainable development have become popular research topics. Based on the above analysis, this paper constructs a water, energy, industry and economic growth system. It also introduces rainfall as an exogenous variable into the model in order to simulate the process of interactions between subsystems within a city and achieve sustainable development. By measuring the dynamic changes and spatial distribution characteristics of the efficiency values of the total water–energy–industry and economic growth system and each subsystem in 29 provinces in China, the following conclusions are drawn: (1) Most of the provinces are in the situation of “high-efficiency–negative growth” or “low-efficiency–positive growth”, and the constraints for them to reach the state of “high efficiency–positive growth” are due to the water subsystem. (2) The low-efficiency provinces are mainly concentrated in the central region, and the spillover effect of the low-efficiency provinces on the neighboring regions is more notable than that of the high-efficiency provinces. (3) The addition of rainfall improves the total efficiency in most provinces, with the most obvious improvement in the efficiency of the water subsystem. (4) The efficiency value of the industry and economic growth subsystem is relatively less affected by the amount of rainfall, but excessive rainfall will also have a negative impact. Finally, relevant policy recommendations are made to inform the relevant government departments in formulating policies related to addressing climate change and achieving sustainable urban development. Full article
(This article belongs to the Special Issue AI for Sustainable Development: Applications and Impacts across Industries)
►▼ Show Figures

Figure 1

24 pages, 6150 KiB  
Article
Forecasting Maritime and Financial Market Trends: Leveraging CNN-LSTM Models for Sustainable Shipping and China’s Financial Market Integration
by Zihui Han, Xiangcheng Zhu and Zhenqing Su
Sustainability 2024, 16(22), 9853; https://doi.org/10.3390/su16229853 - 12 Nov 2024
Cited by 1 | Viewed by 837
Abstract
With the acceleration of economic globalization, China’s financial market has emerged as a vital force in the global financial system. The Baltic Dry Index (BDI) and China Container Freight Index (CCFI) serve as key indicators of the shipping sector’s health, reflecting their sensitivity [...] Read more.
With the acceleration of economic globalization, China’s financial market has emerged as a vital force in the global financial system. The Baltic Dry Index (BDI) and China Container Freight Index (CCFI) serve as key indicators of the shipping sector’s health, reflecting their sensitivity to shifts in China’s financial landscape. This study utilizes an innovative CNN-LSTM deep learning model to forecast the BDI and CCFI, using 25,974 daily data points from the Chinese financial market between 5 May 2015 and 30 November 2022. The model achieves high predictive accuracy across diverse samples, frequencies, and structural variations, with an R2 of 97.2%, showcasing its robustness. Beyond its predictive strength, this research underscores the critical role of China’s financial market in advancing sustainable practices within the global shipping industry. By merging advanced analytics with sustainable shipping strategies, the findings offer stakeholders valuable tools for optimizing operations and investments, reducing emissions, and promoting long-term environmental sustainability in both sectors. Additionally, this study enhances the resilience and stability of financial and shipping ecosystems, laying the groundwork for an eco-friendly, efficient, and sustainable global logistics network in the digital era. Full article
(This article belongs to the Special Issue AI for Sustainable Development: Applications and Impacts across Industries)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop