Timely and accurate wheat yield forecasts using Unmanned Aircraft Vehicles (UAV) are crucial for crop management decisions, food security, and ensuring the sustainability of agriculture worldwide. While traditional machine learning algorithms have already been used in crop yield modelling,...

Identifying at-risk populations is essential for designing effective energy poverty interventions. Using data from the HILDA Survey, a longitudinal dataset representative of the Australian population, and a multidimensional index of energy poverty, we develop a machine learning model combined...

Identifying at-risk populations is essential for designing effective energy poverty interventions. Using data from the HILDA Survey, a longitudinal dataset representative of the Australian population, and a multidimensional index of energy poverty, we develop a machine learning model combined...

Despite the cross-border availability of almost all goods and services online due to global Internet access, the domestic origin of sellers remains significant. This study examines the preferences for domestic versus cross-border goods and services in online purchases in the EU online market...

Marketplace lending has fundamentally changed the relationship between borrowers and lenders in financial markets. As with many other financial products that have emerged in recent years, internet-based investors may be inexperienced in marketplace lending, highlighting the importance of...

Black box machine learning models are currently being used for high-stakes decision making in various parts of society such as healthcare and criminal justice. While tree-based ensemble methods such as random forests typically outperform deep learning models on tabular data sets, their built-in...

Marketplace lending has fundamentally changed the relationship between borrowers and lenders in financial markets. As with many other financial products that have emerged in recent years, internet-based investors may be inexperienced in marketplace lending, highlighting the importance of...