Abstract
Coffee is not merely a refreshing beverage but also invigorates people, provides relaxation, contributes to human health, and fosters closer social connections. Coffee is one of the most widely consumed beverages worldwide and the most traded commercial commodity. Moreover, the rapid development of the Vietnamese coffee industry caused some concerns due to its insufficient performance and the fierce competition within the industry. It is significant to establish an efficient supply network; notwithstanding, supplier selection has always been a challenge for companies. Therefore, this paper employs a hybrid model to determine the supplier selection criteria, a vital factor for a manufacturer under practical operating conditions. Firstly, a combined model of Grey forecasting and the Grey Fourier series is applied to forecast future rainfall and temperature data for six consecutive years. Secondly, based on the criteria, strategies, and buyer requirements, the single-objective linear programming model helps identify the outperformed suppliers. The results found that prices and location change are determinants of supplier selection, and supplier shortage is an enormous barrier for the industry. In this study, these price forecasts allow supply chain management to make informed decisions about inventory levels, transportation routes, and resource allocation to ensure smooth operation and optimize coffee supply chain management.
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