Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …

Banking is a popular topic for empirical and methodological research that applies
operational research (OR) and artificial intelligence (AI) methods. This article provides a …

Machine-learning (ML) methods have gained prominence in the quantitative sciences.
However, there are many known methodological pitfalls, including data leakage, in ML …

This study aims to measure the relationship between technological progress, renewable
energy, and green economic growth (GEG). This study uses a data envelopment analysis …

We study the effects of technological change on financial intermediation, distinguishing
between innovations in information (data collection and processing) and communication …

Artificial Intelligence (AI) has the potential to improve public governance, but the use of AI in
public organizations remains limited. In this qualitative study, we explore how public …

Traffic analysis is the process of monitoring network activities, discovering specific patterns,
and gleaning valuable information from network traffic. It can be applied in various fields …

We create a culture dictionary using one of the latest machine learning techniques—the
word embedding model—and 209,480 earnings call transcripts. We score the five corporate …

Maintaining low carbon energy transitions is a phenomenon that is critical in curtailing
greenhouse emissions. However, such shifts usually warrant incremental capital …

Is the younger generation, including millennials and Generation Z, a driving force toward
achieving the Sustainable Development Goals (SDGs)? The younger generation is often …