Due to increasing global environmental awareness, supply chains that consider environmental protection tend to be favored by green-minded customers. In addition to adapting to the technology required for green supply chains and developing contingency plans, organizations must consider reducing their carbon footprint to meet corporate objectives and reducing their carbon footprint. To address this issue, this paper aims at establishing a decision-making process for buyers with sustainability in mind. A fuzzy data envelopment analysis (FDEA) model was developed to select the most suitable supplier. Production costs, lead time, and supply chain carbon footprints were used as the input criteria, and quality and demand quantity were used as the output criteria. Buyer-seller supply chains and non-cooperative and cooperative models were employed separately to calculate associative efficiency. Sensitivity analysis was conducted to understand the effects carbon footprints have on efficiency. This study found that suppliers with low carbon footprints exhibited poor efficiency, which may be attributed to the additional effort required to select raw materials. Additionally, suppliers with different supply chain operation models exhibited differing efficiencies. Therefore, suppliers must consider the balance between carbon footprint reduction and costs, and buyers must consider environmental criteria when selecting green suppliers.

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.