The growth of the construction industry is severely limited by the myriad complex challenges
it faces such as cost and time overruns, health and safety, productivity and labour shortages …

In practice, as a well-known statistical method, the logistic regression model is used to
evaluate the credit-worthiness of borrowers due to its simplicity and transparency in …

The high proportion of energy consumed in buildings has engendered the manifestation of
many environmental problems which deploy adverse impacts on the existence of mankind …

Bankruptcy prediction is a crucial application in financial fields to aid in accurate decision
making for business enterprises. Many models may stagnate to low-accuracy results due to …

Financial distress prediction provides an effective warning system for banks and investors to
correctly guide decisions on granting credit. Ensemble methods have demonstrated their …

The emergence and continued reliance on the Internet and related technologies has
resulted in the generation of large amounts of data that can be made available for analyses …

Corporate financial distress prediction research has been ongoing for more than half a
century, during which many models have emerged, among which ensemble learning …

Purpose This study aims to explore the relative efficiency of the working capital management
(WCM) for Emirati firms before and during the coronavirus crisis. Next, this study explores …

This study applies an artificial neural network (ANN) to develop models for forecasting
carbon emission intensity for Australia, Brazil, China, India, and USA. Nine parameters that …

The substantial amount of energy consumption in buildings and the associated adverse
effects prompts the importance of understanding building energy efficiency. Developing an …