Business failure prediction has become crucially important for today's firms, enabling them to reduce financial risks and make informed decisions. This study uses a dataset of 6819 companies and 96 financial and macroeconomic variables to present a comparative analysis of machine learning (ML)...

Adopting AI (Artificial Intelligence) in the provision of psychiatric services has been groundbreaking and has presented other means of handling some of the issues related to traditional methods. This paper aims at analyzing the applicability and efficiency of AI in mental health practices based...

Technology is evolving and being implemented across nearly every sector of society, including health, nutrition, and sustainability. Specifically, artificial intelligence (AI) has become an essential tool in gastronomy, not only facilitating chefs' work but also fostering business innovation...

This article examines how design thinking and artificial intelligence (AI) work together and what it means for the design sector. The goal is to understand how AI technologies may advance the design process, encourage innovation, and produce more individualized and user-centric solutions. This...

It is well-established that a country's economic outcomes, including productivity, future income, and labour market performance, are profoundly influenced by the happiness of its people. Traditionally, survey data have been the primary source for determining people's happiness. However, this...

Insurance companies are experiencing unprecedented growth due to several emerging technology functionalities that have transformed the industry's operations. Through the Three Horizons framework, this study explores the technical skills required to use artificial intelligence (AI) for the...

While extensive research studies exist on the influence of AI solutions on organizations as a whole, there is a paucity of comprehensive studies examining the adoption of these solutions in product development and subsequent management processes. This article presents an exploratory...

This study utilizes machine learning models, including Logistic Regression, Support Vector Machine, Decision Tree, and Random Forest, in the early warning system for debt group migration in a Vietnamese commercial bank. In predicting customers' overdue debt migration (B Score), the RF model...