Decision Making and Management Innovation in the Era of Big Data towards Sustainability

Dear Colleagues,

In the post-COVID-19 era, escalating challenges, including supply chain instability, resource scarcity, environmental pollution and social inequality, threaten the sustainable development of societies and organizations. Meanwhile, with the rapid development of information technology in recent years, the emergence of big data has profoundly changed various fields of society and exerted a discernible influence on the decision-making and management process. The combination of big data technologies, such as machine learning and artificial intelligence, and the principle of sustainable development provides both opportunities and challenges for decision makers and managers to improve decision-making methods and innovate management models. Therefore, this Special Issue aims to discuss the design of decision-making methods and the innovation of management practices based on big data technologies which can promote the sustainable development of organizations and society. To meet this purpose, this Special Issue invites the submission of original and meaningful works which involve real world practice in sustainable decision-making and management innovation. Research from an interdisciplinary perspective is also welcome.

Research areas may include (but are not limited to) the following:

• Data-driven sustainable decision-making method design;
• The evaluation and innovation of sustainable management models based on machine learning;
• Supply chain traceability evaluation based on big data technology;
• Data-driven carbon abatement strategy evaluation in supply chains;
• Data-driven supply chain risk management model design;
• Data-driven resource allocation method design;
• Application of machine learning technology in city resource management;
• Resource management model innovation based on machine learning;
• Data-driven pollution control strategy decision;
• Environmental policy making with group opinions on social media;
• Intelligent medical decision making for the elderly;
• Elderly care services sustainability evaluation based on big data technology.

We look forward to receiving your contributions.

Prof. Dr. Decui Liang
Dr. Mingwei Wang
Dr. Kobina Agbodah
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.

• sustainability
• intelligent decision making
• management innovation
• data-driven
• multi-attribute decision making
• group decision making
• machine learning