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The embedding of digital technology and the fuzzy organizational boundary have changed the operation of platform innovation ecosystem (PIE). Specifically, as an important energy of PIE, the internal logic of knowledge flow needs to be reconsidered in the context of digital age, which will be helpful to select the cultivation and governance strategy of PIE.

A dual case-analysis is applied to open the “black box” of knowledge flow in the PIE from the perspective of enabled by digital technology, by taking the intellectual property (IP) operation platform as cases.

The research findings are as follow: (1) The knowledge flow mechanism of PIE is mainly demonstrated through the processes of knowledge acquisition, knowledge integration and knowledge spillover. During this process, connectivity empowerment and scenario empowerment realize the digital empowerment of the platform. (2) Connectivity empowerment provides a channel of knowledge acquisition for the digital connection between participants in PIE. In the process of knowledge integration, scenario empowerment improves the opportunities for accurate matching and collaborative innovation between knowledge supplier and demander, and enhance the value of knowledge. The dual effect of connectivity empowerment and scenario empowerment has accelerated the knowledge spillover in PIE. Particularly, connectivity empowerment expands the range of knowledge spillover, and scenario empowerment affects the generativity of the platform, resulting in the enhancement of platform’s capability to embed and expand its value network. (3) Participants have been benefitted from the PIE enabled by digital technology through three key modules (knowledge acquisition, knowledge integration and knowledge spillover), as the result of knowledge flow.

This study focuses on the knowledge flow mechanism of PIE enabled by digital technology, which enriches the PIE theory, and has enlightenments for the cultivation of digital platform ecosystem.

In response to the complex external structure of high-precision aviation plugs, which makes it difficult to search outside the hole and adjust inside the hole during automated assembly. This paper aims to propose an assembly framework that combines multi-agent search and variable parameter compliant control to solve this problem.

First, a multi-agent search strategy (MAS) based on Gaussian Mixture Model and Deep Q-Network was proposed to optimize displacement direction and actions, thereby improving search speed and success rate. Then, a variable parameter admittance control method (RL-VPA) based on dual delay depth deterministic policy gradient (TD3) was proposed, which dynamically optimized the internal parameters of the admittance controller and adopted state space discretization to improve convergence speed and assembly efficiency.

Compared to spiral search and single-agent search, the average search success rate has improved by approximately 10% and 6.6%. Compared to fixed admittance control and other RL-based methods, the average assembly success rate has increased by approximately 38.6%, 22% and 8.6%. Compared with the training results of the model without state discretization, it was found that state discretization helps the model converge quickly. To verify the generalization ability of the assembly framework, experiments were conducted on three different pin counts of aviation plugs, the assembly success rate reached 86.7%, all of which showed good assembly results. Finally, combining state space discretization to reduce the impact of environmental noise, improve training effectiveness and convergence speed.

MAS has been proposed to optimize displacement direction and action, improving search speed and success rate. RL-VPA is designed to dynamically optimize the internal parameters of the admittance controller, enhancing the robustness and generalization ability of the model. Additionally, state space discretization is combined to improve training effectiveness and convergence speed.

Titanium alloys and composites have proven to contain desirable properties for use at elevated temperatures. One such material is the Ti750 composite, which can be used at temperatures up to 750°C for a brief period. This paper aims the microstructure, phase compositions, apparent porosity and hardness of both sintered and heat-treated TiC reinforced Ti750 composites for consideration in aircraft engine design.

The fabrication of TiC-reinforced Ti750 composites was achieved through spark plasma sintering (SPS). To analyze the microstructure and X-ray diffraction, a scanning electron microscope (SEM) with model number S-3400N and a D8 advance model machine were used, respectively. The microhardness of the samples was measured using a Vickers hardness tester with model HV-1000. The research incorporated three solid solution treatments: 975°C/3 h/AC, 1,010°C/3 h/AC and 1,025°C/3 h/AC, along with a solid-solution aging treatment at 1,010°C/3 h/AC + 750°C/8 h/AC. Additionally, oxidation analysis was conducted on the samples.

The microstructures contained enhanced TiC and Ti5Si3 phases in the near a-Ti matrix. The microhardness of the sintered composite was over twice that of the matrix alloy, and its porosity was reduced by about 0.35%. The sample treated at 1,010°C/3 h/AC had the highest enhanced peaks and microhardness of 1,277.1 HV. After oxidation at 800°C for 100 h, the accumulated weight of the solid solution composite at 1,010 °C/3 h/AC was the lowest (3.0 mg.cm^-2). The surface microstructure contained oxides of TiO2 and a spalling white area containing a small amount of Al₂O₃ and SiO₂.

There is limited research on Ti-Al-Sn-Zr-Mo-Si-based TMCs using a combination of the SPS method. This study used SiCp as a reinforcement for the Ti750 matrix alloy. The consolidation of SiCp and Ti750 powders using the SPS method, heat treatment of the resulting TiC reinforced Ti750 composites and study of the microstructure and properties of the composites are not found in literature or under consideration for publication in any media.

This paper aims to investigate the influence of the regional business environment on local firm innovation, considering various dimensions such as administrative, financial and legal environments.

Multiple regression analysis is employed to analyze archival data for firms listed on Chinese stock markets.

We find that the optimizations of the administrative and financial environments positively affect firm innovation, whereas the legal environment does not exert a similar impact. Our analysis also reveals that the business environment’s optimization significantly influences innovation in firms that are small, non-state-owned and operating in high-tech industries. Furthermore, the business environment acts as a moderating variable in the relationship between firm innovation and firm value.

This study contributes to a more comprehensive understanding of institutional-level determinants of firm innovation, highlighting the nuances of the legal environment and the importance of context-specific analysis, especially in emerging markets like China.

Developing countries can significantly enhance firm innovation by improving the business environment, including the optimization of administrative and financial systems, reducing transaction costs and ensuring capital supply. Tailored legal frameworks and alternative institutional strategies may also be explored.

This study explicitly emphasizes the governmental role in promoting firm innovation, shedding light on policy formulation and strategic alignment with local administrative policies.

To the best of our knowledge, this paper is the first to explore the relationship between the business environment and firm innovation using World Bank indicators in an emerging market context, providing novel insights into the unique dynamics of legal, financial and administrative sub-environments.