With increased environmental protection awareness, sustainability has been incorporated into supply chain management. Sustainable supplier selection and evaluation have become an acritical part of supply chain management. They can significantly improve the supply chain’s operational performance and enhance enterprises’ competitiveness. Based on trapezoidal interval type-2 fuzzy numbers (TIT2FNs) and cloud probability dominance relations (PDR), manufacturers can make more tangible and environmentally friendly decisions in the SSSE process. In this paper, a SSSE indicator system is first established using the necessary economic, environmental, and social factors. The importance of the indicators described in linguistic terms is transformed into TIT2FNs, and the weight of each indicator is calculated. In order to prevent candidate suppliers from promoting performance maliciously, different weights are given according to the impact of the enterprise’s historical performance on the present. Finally, the cloud PDR method is used to determine the optimal sustainable supplier. A case study and analysis are provided to show the feasibility and superiority of the proposed method.

The aim of this paper is to provide a method for selecting a green supplier in a dynamic environment, while considering the psychological behavior and the time factors of the decision maker from the manufacturer’s perspective. The supply selection method that is based on the Third Generation Prospect Theory (PT3) is proposed and an optimal ordinal number is obtained. First, the green supplier selection index system is established. Then, the indicators that are given by the manufacturer are used as reference points, and the income and loss matrices are established by calculating the gains and losses of the index values in the interval number relative to the reference points. Next, considering the time factor and calculating the variable weight based on the Gray correlation coefficient method and the time weight of the penalty mechanism method, the suppliers are chosen based on the comprehensive prospect value. Finally, the validity and the feasibility of the method are proven through a case analysis.

Low-carbon product design is an important way to reduce greenhouse gas emission. Customer collaborative product innovation (CCPI) has become a new worldwide product design trend. Based on this popularity, we introduced CCPI into the low-carbon product design process. An essential step for implementing low carbon CCPI is to clarify key low carbon requirements of customers. This study tested a novel method for perceiving key requirements of customer collaboration low-carbon product design based on fuzzy grey relational analysis and genetic algorithm. Firstly, the study considered consumer heterogeneity, allowing different types of customers to evaluate low carbon requirements in appropriate formats that reflected their degrees of uncertainty. Then, a nonlinear optimization model was proposed to establish the information aggregation factor of customers based on the genetic algorithm. The weight of customers was obtained simultaneously. Next, the key low carbon requirements of customer were identified. Finally, the effectiveness of the proposed method was illustrated with a case related to a low carbon liquid crystal display.

This paper studies the multi-level supply chain network equilibrium optimization problem of multi-energy-efficiency products under different government subsidies and demand scales. In the equilibrium optimization problem, manufacturers determine the production volume of the energy-saving products; retailers decide the transaction volume with manufacturers, distribution volume for markets, and marketing efforts of energy-saving products; markets determine the transaction price. Firstly, the optimal decision-making behaviors of manufacturers, retailers, and markets are described. Simultaneously, the global optimization problem is transformed into a finite-dimensional variational inequality formulation. Then, the equilibrium conditions of the whole supply chain network are derived by the Euler method. Finally, a case study verifies the effectiveness of the proposed method. Interestingly, we found that energy-saving subsidies and demand scales were negatively correlated with the marketing efforts of the subsidized retailers for high energy-efficient products and positively correlated with the marketing efforts of non-subsidized retailers for high energy-efficient products in the same market; the development of retailers in the same market tended to be consistent, and the differentiation of the demand scale eliminated the retailers without a competitive advantage.

In the current globalized business environment, multinational competition has become the norm for companies. This paper considers technology spillovers among manufacturers and develops a global supply chain network equilibrium model. Firstly, the optimal decision-making behaviors of manufacturers, retailers, and demand markets are characterized separately. Secondly, based on the variational inequality theory, the optimal decision-making behaviors of global supply chain members are transformed. Finally, the model is solved and analyzed using the Euler algorithm. The primary objective is to explore the impact of research and development (R&D) subsidies and intellectual property protection (IPP) strategies on manufacturers’ research and development technological levels. Furthermore, the study delves into their effects on the production and transactions of the global supply chain network and social welfare. The following conclusions are drawn: (1) Technology spillovers have a positive effect on the technological level achieved by manufacturers through research and development investment and social welfare. However, intense technological competition may harm manufacturers’ profits. (2) Under the symmetric subsidy policy, higher subsidies may lead to a decrease in social welfare. (3) Under symmetric intellectual property protection policies, increasing the intensity of intellectual property protection benefits manufacturers but is detrimental to retailers and social welfare. However, under an asymmetric intellectual property protection strategy, implementing high-intensity intellectual property protection by high-technology countries is advantageous for retailers and social welfare. This conclusion has contributed to the technical research and development and production operation decision making of global supply chain members, as well as government policy formulation, and has also provided a new perspective for theoretical research in the field of global supply networks.