Although Machine Learning (ML) in supply chain management (SCM) has become a popular topic, predictive uses of ML in SCM remain an understudied area. A specific area that needs further attention is the prediction of late deliveries by suppliers. Recent approaches showed promising results but...

This study investigates the potential of predictive analytics in improving Key Performance Indicators (KPIs) forecasting by leveraging Lean implementation data in supply chain enterprises. A novel methodology is proposed, incorporating two key enhancements: using Lean maturity assessments as a...

The real estate market in China has been growing rapidly during the past decade, with different property price patterns across various regions. Among different types of properties, prices of retail properties have not been sufficiently analyzed. This study focuses on forecasting problems of...

Sports analytics has gained rapid popularity in recent years and will likely continue to evolve. In this study, we construct predictive analytics models to forecast the NFL games outcomes in a season using decision trees and logistics regression. Several variables are used as predictors...

Access to microcredit has received a lot of attention, but, its role in the adoption of climate change adaptation strategies and improvement of rice yield is not often debated. This study investigated the impacts of access to microcredit on the adoption of climate change adaptation strategies...

Direct payments are regarded as a suitable instrument to safeguard jobs in the agricultural sector. However, empirical findings to date do not unambiguously support this expectation. We further empirically investigate this research question on dairy farms with a focus on family work. Using a...

Forecasting stock market movements is a challenging task from the practitioners' point of view. We explore how model selection via the least absolute shrinkage and selection operator (LASSO) approach can be better used to forecast stock closing prices using real-world datasets of daily stock...