Dear Colleagues,

The advancement of new technologies such as big data, artificial intelligence, blockchain and the Internet of Things have opened new business opportunities. Meanwhile, complex, dynamic and uncertain environments pose new challenges. The balance between economic growth and environmental, social, and economic sustainability continues to be a major concern for society.

Information systems, intelligent systems and operations management are often the catalysts in addressing the challenges of sustainability. For example, intelligent routing and transportation have a direct impact on reducing carbon emissions. Closed-loop supply chains use reverse logistics to reuse end-of-life products and eliminate waste. Intelligent information systems combine big data and artificial intelligence techniques to rapidly adapt business operations to changing environments. Smart and connected communities continuously increase levels of prosperity, safety, security, accessibility and inclusivity, and overall quality of life.

This Special Issue on Intelligent Information Systems and Operations Management studies the inter-related roles of people, computing, information, and operations on sustainability.  The subject areas include, but are not limited to, sustainable computing, smart homes and communities, sustainable supply chain management, green and sustained innovation, data science and artificial intelligence for sustainable development. The purpose of this Special Issue is to highlight the advancements and impact of information systems, intelligent systems, and operations management in face of changing environments.

We welcome submissions from any business and technology disciplines. We encourage researchers and practitioners to submit original research articles, case studies, reviews, critical perspectives, and viewpoint articles on topics including but not limited to:

• Sustainable computing;
• Use of intelligent information systems in enterprises;
• Smart and connected homes and communities;
• Intelligent transportation and routing;
• Closed-loop supply chain management;
• Resilience and security of information systems and supply chains;
• Green innovation and green manufacturing;
• Corporate social responsibility and sustainability;
• Life-cycle analysis of technologies and operations.

Prof. Dr. Harris Wu
Prof. Dr. Nengmin Wang
Dr. Qidong He
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 2200 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.

• sustainable computing
• intelligent information systems
• sustainable operations management
• sustainable supply chain
• closed-loop supply chain
• green innovation
• green manufacturing
• corporate social responsibility
• big data
• artificial intelligence
• life cycle analysis