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To further promote application of BIM technology in construction of prefabricated buildings, influencing factors and evolution laws of willingness to apply BIM technology are explored from the perspective of willingness of participants.

In this paper, a tripartite game model involving the design firm, component manufacturer and construction firm is constructed and a system dynamics method is used to explore the influencing factors and game evolution path of three parties' application of BIM technology, from three perspectives, cost, benefit and risk.

The government should formulate measures for promoting the application of BIM according to different BIM application willingness of the parties. When pursuing deeper BIM application, the design firm should pay attention to reducing the speculative benefits of the component manufacturer and the construction firm. The design firm and the component manufacturer should pay attention to balancing the cost and benefit of the design firm while enhancing collaborative efforts. When the component manufacturer and the construction firm cooperate closely, it is necessary to pay attention to balanced distribution of interests of both parties and lower the risk of BIM application.

This study fills a research gap by comprehensively investigating the influencing factors and game evolution paths of willingness of the three parties to apply BIM technology to prefabricated buildings. The research helps to effectively improve the building quality and construction efficiency, and is expected to contribute to the sustainability of built environment in the context of circular economy in China.

The paper aims to elucidate effective strategies for promoting the adoption of green technology innovation within the private sector, thereby enhancing the value of public–private partnership (PPP) projects during the operational phase.

Utilizing prospect theory, the paper considers the government and the public as external driving forces. It establishes a tripartite evolutionary game model composed of government regulators, the private sector and the public. The paper uses numerical simulations to explore the evolutionary stable equilibrium strategies and the determinants influencing each stakeholder.

The paper demonstrates that government intervention and public participation substantially promote green technology innovation within the private sector. Major influencing factors encompass the intensity of pollution taxation, governmental information disclosure and public attention. However, an optimal threshold exists for environmental publicity and innovation subsidies, as excessive levels might inhibit technological innovation. Furthermore, within government intervention strategies, compensating the public for their participation costs is essential to circumvent the public's “free-rider” tendencies and encourage active public collaboration in PPP project innovation.

By constructing a tripartite evolutionary game model, the paper comprehensively examines the roles of government intervention and public participation in promoting green technology innovation within the private sector, offering fresh perspectives and strategies for the operational phase of PPP projects.

The anticorrosion coatings used in marine and atmospheric environment are subjected to many environmental factors. And the aging failure has been puzzling researchers. The purpose of this study is to find the correlation between the initial aging of epoxy coatings and the typical marine atmospheric environmental factors.

The epoxy coatings were subjected to a one-year exposure in three typical marine atmospheres. Meanwhile, principal component analysis, linear regression and Spearman and gray correlation analysis were applied to quantify the environmental characteristics and establish correlations with the coating aging.

The results indicate that the coating will undergo macroscopic fading and chalking upon exposure to the marine atmosphere, while microscopic examination reveals holes, cracks and partial peeling. The adhesion performance and electrochemical properties of the coating deteriorated with prolonged exposure, coating aging mainly occurs with the generation of O-H bonds and the breakage of molecular chains such as C-N and C-O-C. The coating was most deeply aged after exposure to the Xisha, followed by Zhoushan and finally Qingdao. Environmental factors affect the photooxidative aging and hydrolytic degradation processes of coatings and thus coating aging. To further demonstrate the correlation between environmental factors and coating aging, principal component analysis was used. The correlation model between environmental factors and coating aging was subsequently obtained. The correlation model between the rate of coating adhesion loss (E) and the comprehensive evaluation parameter of environmental factors (Z) is expressed as E = 0.142 + 0.028Z. Meanwhile, the Spearman correlation analysis and gray correlation method were used to investigate the impact of each environmental factor on coating aging. Solar irradiation, relative humidity and wetting time have the highest correlation with coating aging, which are all above 0.8 and have the greatest influence on coating aging; wind speed and temperature have the smallest correlation with coating aging, which are about 0.6 and have the least influence on coating aging.

This paper establishes a correlation between typical marine environmental factors and coating aging performance, which is crucial for predicting the service life of other coatings in diverse environments.

This paper aims to introduce corporate social responsibility into the green supply chain and analyse the impact of different decision makers’ decision-making schemes on carbon emission reduction in the supply chain.

This study uses a two-stage low-carbon supply chain composed of a manufacturer and retailer as the research object. It uses the Stackelberg game model to analyse optimal carbon emission reduction and its influence under different decision-making modes.

Increased consumer green preferences and trust can improve the manufacturing enterprises’ carbon emission reduction rate. The carbon emission reduction rate decreases with increased green innovation costs. When green technology innovation costs remain constant, the greater the market capacity, the higher the carbon emission reduction rate. Market capacity has the most significant impact on the optimal carbon emission reduction rate without considering social responsibility decisions and has the least impact on the optimal carbon emission reduction rate while fully considering the social responsibility decision. To achieve decarbonisation production, the market capacity must be small, and when green innovation costs are high, it is the optimal choice without considering social responsibility. To achieve a higher level of carbon emission reduction, when the market capacity is low and the research and development cost is high or when the market capacity is large, it is the optimal choice.

The results provide scientific policy decisions and management significance for governments and enterprises in low-carbon subsidies and supply chain management. The findings also provide a basis for future theoretical research and enterprise practice.

The current research aimed to investigate the external enablement role of Digital Infrastructures (DI) in the interplay of entrepreneurial cognitions and innovation.

Data from the Global Entrepreneurship Monitor (GEM) and Digital Economy and Society Index (DESI) were used for analyses. This yielded a sample of 8,601 Generation Z entrepreneurs operating in 25 European countries.

Applying hierarchical moderated regressions showed that socio-cognitive components of an entrepreneurial mindset (self-efficacy, risk propensity, opportunity identification) affect innovation among Generation Z entrepreneurs. More importantly, DI plays an external enablement role in the interplay of cognitions and innovation among Generation Z entrepreneurs.

This study contributes to the socio-cognitive theory of entrepreneurship by integrating an external enablement perspective into the study of cognitions and entrepreneurial outcomes (here, innovation). It contributes to the digital technology perspective of entrepreneurship by connecting the conversation about the socio-cognitive perspective of entrepreneurship regarding the role of cognitions in innovation to the conversation in information systems (IS) regarding technology affordances and constraints. This study extends the application of the external enabler framework to the post-entry stage of entrepreneurial activity and integrates a generational perspective into it.

The construction of geographical indications agri-food (GIAF) brands play an important role in rural revitalization in China, this study aims to explore how to jointly promote brand building among multiple parties.

A tripartite game model of the producers, sales operating enterprises, and local governments is constructed to analyze the strategy choice of the parties in the complex system behavior evolution stability, and the simulation analysis of the influence factors of brand construction of GIAF and verify the game result.

(1) Increased government subsidies and supervision costs are beneficial to accelerating variety improvement and quality improvement of agri-food, but it is not conducive to the government, Therefore, it is necessary to ensure that the subsidy and supervision cost is kept within a reasonable range; (2) The dividend distributed to producers by sales operating enterprises play an important role in encouraging producers to improve the quality safety of agri-food, but it must be kept within a reasonable range to avoid discouraging the enthusiasm of sales operating enterprises; (3) Cost reduction, and revenue improvement are also effective ways to cooperate with all parties in brand co-construction.

This study does not consider consumers or logistics companies in the evolutionary game model.

This study proposes innovative policies and suggestions for improvement of the brand co-construction of all parties.

Based on the “Rural Revitalization” initiative, this study enriches research methods about brand value and provides a new perspective for brand value co-construction, and theoretical guidance, and empirical basis for formulating innovation policies and recommendations.

This paper aims to design an active shock absorber scheme for use in conjunction with a passive shock absorber to suppress the horizontal vibration of elevator cars in a smaller range and shorter time. The developed active shock absorber will also improve the safety and comfort of passengers driving in ultra-high-speed elevators.

A six-degree of freedom dynamic model is established according to the position and condition of the car. Then the active shock absorber and disturbance compensation-based adaptive control scheme are designed and simulated in MATLAB/Simulink. The results are analysed and compared with the traditional shock absorber.

The results show that, compared with traditional spring-based passive damping systems, the designed active shock absorber can reduce vibration displacement by 60%, peak acceleration by 50% and oscillation time by 2/3 and is more robust to different spring stiffness, damping coefficient and load.

The developed active shock absorber and its control algorithm can significantly reduce vibration amplitude and converged time. It can also adjust the damping strength according to the actual load of the elevator car, which is more suitable for high-speed elevators.

To simplify the circuit design and control complexity of the magnetic coupling resonant wireless charging system, the radio energy transmission constant current and constant voltage charging is realized.

The purpose of this study is to simplify the circuit design and control complexity of the magnetic coupling resonance wireless charging system, in order to achieve constant current and constant voltage charging for wireless energy transmission. First, the principle of LCC/S-S compensation structure is analyzed, and the equivalent mathematical model is established; then, the system characteristics under constant current and constant voltage mode are analyzed, and the design method of system parameters is given; finally, a simulation and experimental system is built to verify the correctness and feasibility of the theoretical analysis.

The results show that the proposed hybrid topology can achieve a constant current output of 2 A and a constant voltage output of 30 V under variable load conditions, and effectively suppress the current distortion problem under light load conditions. The waveform distortion rate of the inverter current is reduced from 33.97% to 10.45%.

By changing the high-order impedance characteristics of the compensation structure, the distortion of the current waveform under light load is suppressed, and the overall stability and efficiency of the system are improved.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

Porosity is a commonly analyzed defect in the laser-based additive manufacturing processes owing to the enormous thermal gradient caused by repeated melting and solidification. Currently, the porosity estimation is limited to powder bed fusion. The porosity estimation needs to be explored in the laser melting deposition (LMD) process, particularly analytical models that provide cost- and time-effective solutions compared to finite element analysis. For this purpose, this study aims to formulate two mathematical models for deposited layer dimensions and corresponding porosity in the LMD process.

In this study, analytical models have been proposed. Initially, deposited layer dimensions, including layer height, width and depth, were calculated based on the operating parameters. These outputs were introduced in the second model to estimate the part porosity. The models were validated with experimental data for Ti6Al4V depositions on Ti6Al4V substrate. A calibration curve (CC) was also developed for Ti6Al4V material and characterized using X-ray computed tomography. The models were also validated with the experimental results adopted from literature. The validated models were linked with the deep neural network (DNN) for its training and testing using a total of 6,703 computations with 1,500 iterations. Here, laser power, laser scanning speed and powder feeding rate were selected inputs, whereas porosity was set as an output.

The computations indicate that owing to the simultaneous inclusion of powder particulates, the powder elements use a substantial percentage of the laser beam energy for their melting, resulting in laser beam energy attenuation and reducing thermal value at the substrate. The primary operating parameters are directly correlated with the number of layers and total height in CC. Through X-ray computed tomography analyses, the number of layers showed a straightforward correlation with mean sphericity, while a converse relation was identified with the number, mean volume and mean diameter of pores. DNN and analytical models showed 2%–3% and 7%–9% mean absolute deviations, respectively, compared to the experimental results.

This research provides a unique solution for LMD porosity estimation by linking the developed analytical computational models with artificial neural networking. The presented framework predicts the porosity in the LMD-ed parts efficiently.