AI-Powered Commerce: Enhancing Sustainability Through Smart Applications

Dear Colleagues,

In the current era in which digital transformation and sustainable development are becoming increasingly intertwined, emerging technologies play a pivotal role in business operations and social governance. In particular, the rapid advancement of artificial intelligence (AI) and big data analytics not only revolutionizes electronic commerce and green supply chain management but also provides novel tools and analytical approaches for supporting environmental, social, and governance (ESG) initiatives. This Special Issue focuses on how AI and big data are applied in e-commerce, operations, supply chain management, and ESG practices, enabling organizations to enhance efficiency while achieving sustainability.

The scope of this Special Issue encompasses innovative applications and academic exploration of emerging technologies (e.g., AI, big data, IoT, blockchain) in various contexts, including e-commerce, production, logistics, supply chains, sustainable finance, energy management, and consumer behavior. We especially welcome interdisciplinary studies that integrate AI and big data analytical frameworks to support sustainability performance management, carbon monitoring, green logistics, and intelligent decision-making. Researchers from diverse disciplines, such as management, information systems, environmental science, and industrial engineering, are encouraged to contribute their latest findings and practical insights.

The purpose of this Special Issue is to create a platform for the exchange of academic and industrial research, with the goal of advancing our understanding of how AI and big data can be practically applied in the transformation of e-commerce and sustainable supply chains. It aims to bridge the gap between ESG policies and technical solutions by examining how emerging technologies enable ESG practices to become actionable strategies. This issue not only highlights mechanisms through which AI and big data enhance digital resilience and sustainability in enterprises but also emphasizes the tangible contributions of these technologies to carbon reduction, energy saving, and social responsibility.

Although the existing literature has accumulated considerable knowledge on the use of AI and big data in operations management and e-commerce, studies focusing on their integration with ESG, support for green supply chain transformation, and empirical modeling within the context of sustainability remain limited. Therefore, this Special Issue will crucially supplement and extend current scholarship by providing in-depth analyses and empirical evidence on how AI and big data can drive green innovation and sustainable strategies in business.

The contributions of this Special Issue to sustainable development are articulated through three dimensions: (1) Environmental: Using AI predictions and big data monitoring to improve resource allocation efficiency and reduce carbon emissions and energy consumption. (2) Social: Enhancing information transparency and supporting socially responsible practices such as automated sustainability reporting and ESG disclosures. (3) Governance: Facilitating the adoption of technology-driven ESG governance frameworks and risk monitoring systems. Overall, this Special Issue is committed to revealing the potential of emerging technologies in supporting the United Nations Sustainable Development Goals (SDGs) and addressing global challenges in sustainability.

Topics covered in this Special Issue will include (but will not be limited to) the following:

• Sustainable applications of AI and big data on e-commerce platforms.
• Decision support systems using AI and big data in green supply chain management.
• ESG data analytics and intelligent report generation tools.
• Carbon footprint tracking and environmental performance monitoring using AI and big data.
• Smart logistics and energy-efficient scheduling technologies.
• Roles and challenges of AI in sustainable business models.
• AI’s applications in predicting and influencing sustainable consumer behavior.
• Empirical research on AI and big data in sustainable finance and green investment.
• AI-based risk assessment and innovations in ESG governance.
• Sustainable operations strategies and technical practices in cross-border e-commerce.

Prof. Dr. Shih-Chih Chen
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. 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.

• artificial intelligence (AI)
• big data analytics
• electronic commerce
• green supply chain management
• ESG (environmental, social, and governance)
• emerging technologies for sustainable development
• smart logistics
• sustainable business models