The equipment maintenance services have become a new profit center and an important way to gain sustainable competitive advantage for manufacturing enterprises. The business model is an important tool for manufacturing enterprises to derive economic benefits from sustainable competitive advantage in the context of digitalization technologies, such as IoT, big data, and cloud computing. At present, the concept of equipment maintenance business model innovation is still vague, and it is rare to report on the innovation behaviors and types of equipment maintenance business models adopted by manufacturing enterprises. Based on literature analysis of equipment maintenance services and business model innovation, following business model gestalt theory, the concept of equipment maintenance business model innovation is analyzed at the business-level, the types are divided into novel and efficient following value sources—“innovation and efficiency”. The initial scale is developed through literature investigation, semi-structured interviews and expert reviews, and tested by exploratory and confirmatory factor analysis by using the data of two independent large-sample questionnaires. The results indicate that the behavior and types of equipment maintenance business model innovation can be described by two types and 19 items.

The fierce competition in the recycling industry and the rapid development of internet technology has prompted recycling centers to develop a dual-channel reverse supply chain with both offline and online recycling channels. After the introduction of online channels, recycling centers and third-party recyclers (TPR) have paid attention to the division of profits in supply chain systems and the behavior of fairness concerns. Therefore, it is necessary to help recycling enterprises make pricing decisions in consideration of fairness concerns. This paper is aimed at answering the following two main questions: (1) When the recycling center or TPR have fairness concerns, how does the optimal pricing and revenue of supply chain members change when both sides are neutral? (2) When the fairness concern coefficient changes, how does the overall revenue of the supply chain system change? How should supply chain members adjust their pricing decisions to maximize their own profits? In order to solve the above problems, Stackelberg game models were made from three aspects: both sides are neutral, only the TPR has fairness concerns, and only the recycling center has fairness concerns. Based on the results of the example analyses for the model, we found that when only the TPR has fairness concerns, the profit of the recycling center and the transfer price of offline channels will decrease, while the profit of TPR is the opposite. Furthermore, when only a recycling center has fairness concerns, it will lead to the reduction of not only the recycling price and transfer price of offline channels, but also the profits of the entire supply chain system. Specially, whether it is for a recycling center or TPR, a lower level of fairness concern coefficient has a stronger impact on pricing and revenue than at high levels.

With the prevalence of Internet technology, many recycling centers have developed a dual-channel reverse supply chain by introducing online recycling channels on the basis of offline third-party recyclers (TPR). In addition, great imbalanced development has been observed in different regions in China, as supported by the literature review. It is necessary to help companies in the supply chain to adjust their pricing strategies according to regional differences. This paper is aimed at answering the following two questions: (1) After introducing online channels, what strategies should the recycling center adopt to adjust online recycling prices and to readjust the transfer price of offline channels? (2) How do recycling centers and TPR in city A & B modify their pricing strategies in accordance with logistics costs or consumers’ awareness of sustainability changes in city B? To solve the above questions, models were made to study the pricing strategies of recycling centers and the TPR based on the Stackelberg game in a dual-channel reverse supply chain in two cities. The results indicate that recycling centers will benefit from the increase in consumers’ awareness of sustainability and the reduction in logistics costs of the online channel in city B; this is in contrast to the TPR in this city. We also find that the revenue of the TPR in city A will be affected when the above two factors in city B change. Its increase or decrease depends on the selection of pricing strategy by the recycling center.

The rapid development of e-commerce technologies has encouraged collection centers to adopt online recycling channels in addition to their existing traditional (offline) recycling channels, such the idea of coexisting traditional and online recycling channels evolved a new concept of a dual-channel reverse supply chain (DRSC). The adoption of DRSC will make the system lose stability and fall into the trap of complexity. Further the consumer-related factors, such as consumer preference, service level, have also severely affected the system efficiency of DRSC. Therefore, it is necessary to help DRSCs to design their networks for maintaining competitiveness and profitability. This paper focuses on the issues of quantitative modelling for the network design of a general multi-echelon, dual-objective DRSC system. By incorporating consumer preference for the online recycling channel into the system, we investigate a mixed integer linear programming (MILP) model to design the DRSC network with uncertainty and the model is solved using the ε-constraint method to derive optimal Pareto solutions. Numerical results show that there exist positive correlations between consumer preference and total collective quantity, online recycling price and the system profits. The proposed model and solution method could assist recyclers in pricing and service decisions to achieve a balance solution for economic and environmental sustainability.

Facing the increasingly serious waste electrical and electronic equipment (WEEE) recycling problem, recycling enterprises actively introduce online recycling channels, build dual channel reverse supply chains (DRSC), and use high-level recycling price and service levels to enhance consumers’ recycling enthusiasm and recycling amount. Nevertheless, in China, where the imbalance of regional development is widespread, the recycling center, third-party recycler (TPR), and third-party platform (TPP) are faced with the choices of pricing and service level when facing multi-regional consumers. This paper mainly answers the following questions: (1) When the recycling center and TPP introduce online recycling channels in multi-regional situations, how should they set online recycling price, transfer price, and service level? (2) When consumer preference for online channels changes in a certain region, how should recycling enterprises adjust their optimal pricing and service level decisions for different regions to maximize their own profits? How do the profits of recycling enterprises change? In order to solve the above problems, in this paper, we propose three pricing and service level decision models for the recycling center with online channels, namely, keeping prices unchanged, unifying all prices, and maximizing its own profits. By using the Stackelberg game to solve the model, we get the optimal pricing, service level decisions, as well as the maximum profits of the recycling center, TPP, and TPR when consumer preference changes. By analyzing the results of the model, we find that the change of consumer preference for online channels in a certain region will affect the decision and profits of multi-regional recycling enterprises. Specifically, consumer preference for online channels in a certain region will not only lead to an increase in the profits of the recycling center and TPP and a decrease in the profit of local TPRs, but also an increase in the profit of TPRs in other regions. In addition, at the beginning of introducing online channels, the recycling center can adopt two strategies to avoid conflicts among channels: keeping offline transfer prices unchanged and unifying all transfer prices, but the former promotes its economic profits more significantly.

In recent years, there have been frequent online public opinion events against the quality of new energy vehicles. Enterprises in the supply chain must adopt effective information prediction and sharing strategies for consumers' perceived quality to optimize their decisions and profits. In this paper, we construct and solve the Stackelberg game model for a supply chain structure composed of new energy vehicle manufacturers, battery manufacturers, and fuel vehicle manufacturers, respectively, under the scenarios of sharing or not sharing perceived quality information of new energy vehicles under the dual credit policy. Based on the analysis of the model solving results, this paper further uses the numerical example method to analyze the influence trend of the credit price and information prediction accuracy on the decisions and profits of enterprises, and finally puts forward management enlightenment for enterprises. The results show that: When the credit price and information prediction accuracy change, enterprises should adopt different decision-making optimization schemes under different information sharing scenarios; new energy vehicle manufacturers should actively seek cooperation with battery manufacturers in information sharing, which will not only optimize the profits of battery manufacturers, but also benefit the profits of new energy vehicle manufacturers, fuel vehicle manufacturers and the entire channel; if new energy vehicle manufacturers insist on not sharing information, it will lead to a "lose-lose" situation.