Advances in Artificial Intelligence in Sustainable Business Management
A special issue of Sustainability (ISSN 2071-1050).
Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 3166
Special Issue Editors
Interests: machine learning; data analytics; health informatics; environmental informatics
Special Issues, Collections and Topics in MDPI journals
Interests: green technologies; artificial inteligence; recommender systems; tourism management; sustainable development
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial Intelligence (AI) deploys several algorithms and statistical models to produce computer systems and applications that can make predictions and draw inferences from the input data. Deep Learning (DL) and Machine Learning (ML) are popular subsets of AI that are used to analyze data, learn from it, and reach intelligent decisions. AI approaches have been improved in terms of the deployed methods and applied tools and are utilized in almost all areas of humans' lives. AI applications have assisted the development of many emerging innovations in several business management branches, including the management of marketing, finances, sales, strategy, risk, quality, design, facility, innovation, change, research, and the supply chain. With the availability of big data in the market, AI techniques can reformulate customers’ and business managers’ behaviors in almost all areas of business, such as healthcare, agriculture, industry, tourism, transportation, and so on. Therefore, several research disciplines have applied AI techniques for various business-focused tasks, such as classification, prediction, analysis, evaluation, reporting, and segmentation.
Following the announcement of the Sustainable Development Goals (SDGs), more attention has been allocated to sustainability issues in business management. Sustainability encourages businesses to carefully consider the factors that impact their long-run performance. Recognizing these factors helps them locate the real value of the business through incorporating those factors in business management strategy, performance evaluation, marketing analysis, and reporting. Sustainable business management guides business operations through the concept of “valuable and limited resources”, adding value to the business and encouraging resource conservation. AI techniques may surpass previous approaches in their capability to implicitly recognize complex structures in large data sets and their applicability in addressing research and practical problems in sustainable business management. The recent increase in research on ML and DL methods in this field can be explained by the availability of large volumes of data from several sources in the market, particularly social media data. The main goal of this Special Issue is to present the research community and decision makers with emerging academic research developments and industrial advancements in AI for sustainable business management applications. Research topics include, but are not limited to:
- Data analytics and ML approaches for sustainable business management.
- Incremental learning for risk management in sustainable business.
- Emerging AI approaches for addressing sustainability issues in the market.
- AI approaches for sustainability initiatives in business.
- Sustainable business performance evaluation using AI approaches.
- Analyzing business models using AI techniques focusing on sustainable value.
- Using AI techniques to investigate and analyze carbon footprints in the business.
- AI-based techniques to present climate-resilient practices in business.
- Analyzing SDGs’ deployment in the global market using AI approaches.
- Analysis of complex data in sustainable business.
- Procurement management of business using AI techniques.
- AI products and their impact on sustaining business resources.
- AI techniques in analyzing market revenues, with an emphasis on sustainable goals.
Dr. Mehrbakhsh Nilashi
Dr. Rabab Ali Abumalloh
Guest Editors
Manuscript Submission Information
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Keywords
- AI techniques
- sustainable business management
- machine learning
- data analytics
- sustainable development goals
- deep learning
- prediction
- analysis
