This study reviews the methodologies used in the literature to predict failure in small and
medium-sized enterprises (SMEs). We identified 145 SMEs' default prediction studies from …

Industry 4.0 affects nearly every aspect of life by making it more technologically advanced,
creative, environmentally friendly and ultimately, more interconnected. It also represents the …

Identifying the vital role of climate risk in developing technology is significant to promote the
Fourth Industrial Revolution. The research utilises the full and sub-sample methodologies to …

The corporate bankruptcy prediction literature has traditionally relied on data from public,
audited companies. However, the vast majority of firms worldwide are privately-held and …

We propose a novel stacking ensemble learning model to predict the outage duration during
typhoon disaster to help users prevent disasters. The model integrates extra tree (ET) …

A crucial issue in financial economics pertains to enhancing the transparency of accounting
and financial reporting within companies. This paper focuses on China, aiming to quantify …

Research background: Effective monitoring of financial health is essential in the financial
management of enterprises. Early studies to predict corporate bankruptcy were published at …

Transportation, logistics, storage, and many other sectors provide a wide space for applying
Industry 4.0. This era, with its components, represents the equipment necessary to obtain a …

Credit-risk models that are designed for general application across sectors may not be
suitable for the construction industry, which has unique characteristics and financial risks …

Financial distress prediction (FDP) is a topic that has received wide attention in the finance
sector and data mining field. Applications of combining cost-sensitive learning with …