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The purpose of this paper is to examine the effect of application of a heat pipe in an aspect of hydrostatic thrust bearings on thermal balance and deformation and the role of this application in increasing the rotating speed of a workbench.

Numerical simulations of oil film temperature field, the temperature field and thermal deformation of the bearing’s workbench and base were performed by finite element analysis (FEA) software for both the traditional hydrostatic thrust bearings and the heat pipe ones.

Oil pad and workbench of the hydrostatic thrust bearings are fabricated with a heat pipe cooling structure, which can take away most of the heat generated by shearing of the oil film, control the temperature rise and thermal deformation of the hydrostatic thrust bearing effectively, avoid the dry friction phenomenon and finally improve the processing quality of equipment.

The heat pipe hydrostatic thrust bearings could control the temperature rise and thermal deformation of the hydrostatic thrust bearing effectively, avoid the dry friction phenomenon and improve the processing quality of equipment.

With the advent of the information age, this paper aims to apply risk analysis theories to study the risk prevention mechanism of information disclosure, thus supporting the green electricity supply.

This paper conducts a comprehensive evaluation and analysis of the impact of power market transactions, power market operations and effective government supervision, so as to figure out the core risk content of power market information disclosure. Moreover, AHP-entropy method is adopted to weigh different indicators of information disclosure risks for the participants in the electricity market.

The potential reasons for information disclosure risk in the electricity market include insufficient information disclosure, high cost of obtaining information, inaccurate information disclosure, untimely information disclosure and unfairness of information disclosure.

Some suggestions and implications on risk prevention mechanism of information disclosure in the electricity market are provided, so as to ensure the green electricity supply and promote the electricity market reform in China.

In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

The purpose of this study is to address a significant gap in the understanding of entrepreneurship at the microfoundation level. It focuses on how individual entrepreneurs, specifically Hongbang entrepreneurs in China from 1896 to 1949, shape and transform their contexts. The aim is to provide a deeper understanding of the mechanisms that facilitate entrepreneurial success.

The study adopts a microhistorical approach, investigating the case of Hongbang entrepreneurs in China during 1896-1949. It involves an in-depth examination of historical records to explore the strategic interactions between these entrepreneurs and core stakeholders such as consumers, financial intermediaries, government regulators, and human resources. The research methodology emphasizes a process-oriented view, examining the evolution of personalized networks into extensive connections.

The research reveals that Hongbang entrepreneurs successfully reshaped their unfavorable embedded contexts by strategically collaborating with key stakeholders. They influenced consumer tastes, allied with financial intermediaries, negotiated with governments on regulation policies, and developed human resource stocks. The transformation was facilitated by the evolution of their networks from personalized to extensive connections. These findings highlight the localized strategies such as cronyism in resource acquisition within China’s private property development industry.

This study contributes to the field by offering insights into entrepreneurial contextualization and networking. It sheds light on the complex interplay between entrepreneurs and their contexts, providing a nuanced understanding of localized strategies in the Chinese context. The findings add value to the discourse on entrepreneurship by elucidating the strategic and processual acts through which entrepreneurs engage with stakeholders and reshape their environments.

A tower crane mainly ensures the success or efficiency of building construction. Fatigue crack analysis is important for tower crane components to prevent any accidents to workers in construction sites caused by component failure and to ease the maintenance or replacement of failed components. This work aimed to characterise the damage of failed components, analyse the relationship between the metal magnetic memory (MMM) result and the damage of failed components, and to validate the relationship between MMM and finite element analysis (FEA).

MMM was used in this work to detect any irregularities or early failure on the basis of the high stress concentration zone of ferromagnetic steel using magnetic flux leakage. Magnetic flux leakage was used on the MMM device to achieve the first objective using the MMM system by detecting the irregularities. The results of MMM analysis were validated through comparison with FEA results by determining their relationship.

MMM results show that the position of defects on the tower crane pulley is within the stress area shown on FEA.

Hence, MMM method is a potential tool in monitoring failure mechanism in construction site.