...Damilare Ogunjobi; Rania Shibl; Shahrzad Saremi Purpose This study investigates the effectiveness of machine learning, deep learning and traditional time-series approaches for predicting agricultural commodity prices in Nigeria, focussing on improving forecasting reliability through temporal...

...Shripad Bhat; T.M. Kiran Kumara; Shiv Kumar Purpose This study aims to evaluate the predictive performance of traditional econometric time series models and modern machine learning (ML) approaches for forecasting black pepper prices in India's Cochin market, a key benchmark market in the Indian...

... Karnataka and only 14.29% in the North, revealing a significant regional disparity. Design/methodology/approach To identify key factors of this variation, support vector machine (SVM), a supervised machine learning technique, was employed. Findings Promoting institutions (PIs) (+0.81), primary...

.../approach This study integrates quantitative analysis using multiple national representative datasets with machine learning techniques to predict farmer income with high accuracy data. Focus group discussions and field interviews are also used to get qualitative insights into regional disparities...

...Sapna Jarial; Jayant Verma Purpose This study aimed to understand the agri-entrepreneurial traits of undergraduate university students using machine learning (ML) algorithms. Design/methodology/approach This study used a conceptual framework of individual-level determinants of entrepreneurship...