In this literature review, we investigate machine learning techniques that are applied for
stock market prediction. A focus area in this literature review is the stock markets …

With the ever‐growing adoption of artificial intelligence (AI)‐based systems, the carbon
footprint of AI is no longer negligible. AI researchers and practitioners are therefore urged to …

Virtual teams (ie, geographically distributed collaborations that rely on technology to
communicate and cooperate) are central to maintaining our increasingly globalized social …

Digital transformation creates challenges in all industries and business sectors. The
development of digital transformation has also clearly triggered the emergence of fintech …

Recent advancements in deep learning architecture have increased its utility in real-life
applications. Deep learning models require a large amount of data to train the model. In …

Recent progress in artificial intelligence and machine learning has led to the growth of
research in every aspect of life including the health care domain. However, privacy risks and …

This study aims to explore the current status, potential applications, and future directions of
blockchain technology in supply chain management. A literature survey, along with an …

Purpose Inscrutable machine learning (ML) models are part of increasingly many
information systems. Understanding how these models behave, and what their output is …

Construction and demolition waste (CDW) is a priority for many policies at global level. This
is due to the high volume of CDW that is produced and its inadequate management. This …

Abstract Project-Based Learning (PBL) and Computational Thinking (CT), a teaching
strategy and a problem-solving method, respectively, have been widely used in teaching …