Logistics plays an important role in globalized companies and contributes to the development of foreign trade. A large number of external conditions, such as recession and inflation, affect logistics. Therefore, managers should find ways to improve operational performance, enabling them to increase efficiency while considering environmental sustainability due to the industry’s large scale of energy consumption. Based on data collected from the financial reports of top global logistics companies, this study uses a DEA model to calculate corporate efficiency by implementing a Grey forecasting approach to forecast future sustainability values. Consequently, the study addresses the problem of how to enhance operational performance while accounting for the impact of external conditions. This research can help logistics companies develop operation strategies in the future that will enhance their competitiveness vis-à-vis rivals in a time of global economic volatility.

Logistics plays an important role in globalized companies and contributes to the development of foreign trade. A large number of external conditions, such as recession and inflation, affect logistics. Therefore, managers should find ways to improve operational performance, enabling them to increase efficiency while considering environmental sustainability due to the industry’s large scale of energy consumption. Based on data collected from the financial reports of top global logistics companies, this study uses a DEA model to calculate corporate efficiency by implementing a Grey forecasting approach to forecast future sustainability values. Consequently, the study addresses the problem of how to enhance operational performance while accounting for the impact of external conditions. This research can help logistics companies develop operation strategies in the future that will enhance their competitiveness vis-à-vis rivals in a time of global economic volatility.

Background: Strategic alliance is a popular strategic option for business entities to strengthen the competitive advantages of all partners in a partnership. The global logistics industry has witnessed the formulation of several successful strategic alliances. However, the Vietnamese logistics industry seems to grow slowly and lacks long-term inter-firm partnerships. In such a context, it is critical to have a more effective approach to selecting partners in strategic alliances to increase long-term relationships and firm performance. Method: Thus, this study proposes using the SBM-I-C DEA model to examine and suggest partners for Vietnamese logistics firms to form strategic alliances. Results: Our findings show that integrating technology in managing strategic alliances will foster companies in the alliance to formulate a better strategy with up-to-date information on policies. Conclusion: Using the SBM-I-C DEA model, companies can minimize operating costs and optimize delivery time. Thus, companies can better satisfy customers. From the research findings, some implications are proposed for Vietnamese logistics companies.

Coffee is the most traded commodity after petroleum. The Vietnamese coffee bean industry has raised concerns lately over an inefficient coffee value chain; bets on coffee price uncertainty are increasing worldwide in the current. Accurate optimization of coffee bean prices helps manufacturers to control an unpredictable market and upgrade cooperativeness in sustainable agriculture. The authors proposed a forecasting method to deal with demand volatility and uncertainty in volumes and coffee bean prices. In this paper, we applied the forecasting nonlinear grey Bernoulli model (NGBM) (1,1). NGBM (1,1), which is based on the parameter optimization algorithm, can increase the precision of predictions. NGBM (1,1) was integrated with Fourier residual modification model to forecast coffee bean price, which was a crucial factor in the Vietnamese coffee bean supply chain. The price of coffee beans was calculated using a differential equation in an uncertain system, along with actual data collected over the past six years. The results of this study demonstrate that an integrated forecasting model is an effective forecasting method. This research can help companies to control risks that come with uncertain coffee prices and reduce risks in the sustainable agriculture supply chain.

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.