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Intelligent new energy vehicles (INEVs) are becoming the competitive hotspot for the automobile industry. The major purpose of this study is to determine how to increase innovation efficiency through knowledge sharing and technology spill between new energy vehicle (NEV) enterprises and technology enterprises. This will help to improve the core competence of the automobile industry in China. Also, it serves as a guide for the growth of other strategic.

The authors construct a tripartite evolutionary game model to study the cross-border cooperative innovation problem. Firstly, the payment matrix of NEV enterprise, technology enterprise and government is established, and the expected revenue of each participant is determined. Then, the replication dynamic equations and evolutionary stability strategies are analyzed. Finally, the theoretical research is validated through numerical simulation.

Results showed that: (1) An optimal range of revenue distribution coefficient exists in the cross-border cooperation. (2) Factors like research and development (R&D) success rate, subsidies, resource and technology complementarity, and vehicles intelligence positively influence the evolution towards cooperative strategies. (3) Factors like technology spillover risk cost inhibit the evolution towards cooperative strategies. To be specific, when the technology spillover risk cost is greater than 2.5, two enterprises are inclined to choose independent R&D, and the government chooses to provide subsidy.

The research perspective and theoretical analysis are helpful to further explore the cross-border cooperation of the intelligent automobile industry. The findings suggest that the government can optimize the subsidy policy according to the R&D capability and resource allocation of automobile industry. Moreover, measures are needed to reduce the risk of technology spillovers to encourage enterprise to collaborate and innovate. The results can provide reference for enterprises’ strategic choice and government’s policy making.

The INEV industry has become an important development direction of the global automobile industry. However, there is limited research on cross-border cooperation of INEV industry. Hence, authors construct a tripartite evolutionary game model involving NEV enterprise, technology enterprise and the government, and explore the relationship of cooperation and competition among players in the INEV industry, which provides a new perspective for the development of the INEV industry.

Global economic growth provides new opportunities for the development of clothing enterprises, but at the same time, the rapid growth of clothing customization demand and the gradual increase of clothing costs also pose new challenges for the development of clothing enterprises. In this context, 3D printing technology is injecting new vitality and providing a new development direction for the vigorous development of clothing enterprises. However, with the application of 3D printing technology, more and more clothing enterprises are facing the problem of business model innovation. In view of the lack of relevant research, it is necessary to carry out exploratory research on this issue.

The business model canvas method was adopted to design business model for clothing enterprises using 3D printing. The simulation model of the designed business model was constructed by a system dynamics method, and the application of the designed business model was analysed by a scenario simulation.

Mass selective customization-centralized manufacturing (MSC-CM) business model was constructed for clothing enterprises using 3D printing, and a static display was carried out using the BMC method. A dynamic simulation model of the MSC-CM business model was constructed. The future scenario of clothing enterprises using 3D printing was developed, and a simulated enterprise was analysed. The results show that the MSC-CM business model has a good application value. The simulation model of the MSC-CM business model performs the function of a business strategy experiment platform and also has a good practical application value.

The MSC-CM business model is only a typical business model for clothing enterprises using 3D printing. It is necessary to further develop other business models, and some elements of the MSC-CM business model need to be further improved. In addition, the MSC-CM business model simulation uses a general model, which is not suitable for all clothing enterprises using 3D printing. When the model is applied, the relevant enterprises can further adjust and optimize it, thereby improving the validity of the simulation model.

To the best of the authors’ knowledge, this is the first paper on the MSC-CM business model for garment enterprises using 3D printing. Secondly, it is the first time that the business model of clothing enterprises using 3D printing has been simulated. In particular, the proposed business model simulation provides the possibility for testing the business strategy of clothing enterprises using 3D printing. In addition, a positive attempt has been made in the collaborative research of using both a static display business model and a dynamic simulation business model.

This paper aims to systematically demonstrate a methodology to determine the relative and absolute encapsulation efficiencies (α_Re and α_Ab) for thermally- and chemically-robust inorganic pigments, typically like ZrSiO₄-based pigments, thereby enhancing their coloring performance.

The authors designed a route, surplus alkali-decomposition and subsequently strong-acid dissolution (SAD2) to completely decompose three classic zircon pigments (Pr–ZrSiO₄, Fe₂O₃@ZrSiO₄ and CdS@ZrSiO₄) into clear solutions and preferably used inductively coupled plasma-optical emission spectrometry (ICP-OES) to determine the concentrations of host elements and chromophores, thereby deriving the numeric data and interrelation of α_Re and α_Ab.

Zircon pigments can be thoroughly decomposed into some dissoluble zirconate–silicate resultants by SAD2 at a ratio of the fluxing agent to pigment over 6. ICP-OES is proved more suitable than some other quantification techniques in deriving the compositional concentrations, thereby the values of α_Re and α_Ab, and their transformation coefficient K_RA, which maintains stably within 0.8–0.9 in Fe₂O₃@ZrSiO₄ and CdS@ZrSiO₄ and is slightly reduced to 0.67–0.85 in Pr–ZrSiO₄.

The SAD2 method and encapsulation efficiencies are well applicable for both zircon pigments and the other pigmental or non-pigmental inhomogeneous systems in characterizing their accurate composition.

The authors herein first proposed strict definitions for the relative and absolute encapsulation efficiencies for inorganic pigments, developed a relatively stringent methodology to determine their accurate values and interrelation.