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Torque is one of the main loads acting on the aircraft wing, the horizontal tail and the vertical tail. In flight load measurement, due to the significant influence of the bending moment and the shear force on the strain gauge, the accuracy of torque measurement is usually low. Therefore, aircraft torque measurement is difficult. Based on the characteristics of a certain type of horizontal tail, a measurement method for the torque with high accuracy was proposed in this paper.

A new simplified torque measurement method for the all-moving horizontal tail was proposed based on the spiral driver. The feasibility of the method and key points of the tests were analyzed and studied through a virtual load calibration test.

Based on the results of the real load calibration test, the torque load equation with high accuracy was established, and the torque measurement was achieved in load flight tests.

However, the proposed method is based on the structure of the spiral driver. If there is generally no spiral driver at the aircraft wings and vertical tails, then the appropriate torque measurement method needs to be derived according to the specific object.

The research in this paper provides a new idea for the torque measurement of aircraft structures, which can be used for the torque measurement of subsequent aircraft types.

The paper examines how local governments’ responses to citizens’ complaints about environment issues are affected when the complaints involve conflicting goals, particularly economic versus environmental goals. This study focuses on the responsiveness of provincial governments to citizen environmental complaints on the Local Leader Message Board (LLMB) in China.

This study collected 125,364 environment-related complaints lodged by citizens on the LLMB from 2013 to 2021 and identified complaints embodying conflicting goals through a Structural Topic Model (STM). Advanced supervised machine learning (ML) algorithms were employed to enhance the robustness of the findings.

The results indicate that provincial governments prioritize citizens’ complaints across different types of issues. However, complaints embodying conflicting goals (related to environmental issues) are less likely to get a response. This relationship is moderated by an inverted U-shaped effect of economic dependence on industries. This suggests that the impact of conflicting goals on government responsiveness is dynamic, with the likelihood of provincial governments responding to conflicting complaints initially increasing and then decreasing as economic dependence on industries rises.

The findings enrich the understanding of the consequences of conflicting goals by highlighting their potential as a mechanism to explain the strategic reactions of governments to citizens.

This research aims to investigate the impact of corporate digital transformation (CDT) on stock market activity.

A data set of Chinese listed manufacturing enterprises from 2012–2021 is used as a research sample.

This research finds that CDT can promote stock market activity. This study validates two potential mechanisms: increasing financial performance and mitigating information asymmetry. This study further suggests that internal control and analyst coverage can strengthen the impact of CDT on stock market activity.

The research exhibits certain limitations that should be considered in future research. Because the findings are based on the Chinese context, the applicability and generalizability of the findings to other environments may be limited. This research enriches the literature on the determinants of stock market activity from a technological perspective and incrementally contributes to understanding the impact of CDT on stock markets. After analyzing two opposing perspectives on the economic consequences of CDT, the favorable effect of CDT on stock market activity is proven based on the resource-based view and agency theory. This research extends the literature on the relationship between CDT and investor behavior, demonstrating that investors perceive CDT as beneficial. The results provide evidence that CDT can increase financial performance and improve the information environment, leading to increased investor attention and enhanced trading activity.

This research has incremental practical implications for enterprises and regulatory authorities to comprehend the economic consequences of CDT in developing countries. First, enterprises should increase their digital investments to improve their performance and decrease information asymmetry. Furthermore, enterprise managers should strengthen information systems to adapt to the process of CDT and train employees on digital skills. Second, regulatory authorities should provide comprehensive digital policies and programs supported by tax incentives, subsidies and digital infrastructure projects (Wang et al., 2023).

This research strengthens the debate on the market impact of CDT. Unlike prior literature, this study explores the influence of CDT on stock market activity for the first time, enriching the literature on CDT and stock market activity. Furthermore, the outcomes guide regulatory authorities to actively support CDT and expedite the digital upgrading of manufacturing industries to promote stock market activity.

Digital transformation provides a new impetus for the development of declining firms. However, there is currently a lack of sufficient research on whether digital transformation is beneficial for the turnaround of declining firms. This paper aims to explore the relationship between digital transformation and the turnaround of declining firms.

Drawing on the theoretical foundations of the resource-based view and dynamic capabilities theory, this research uses a comprehensive dataset of Chinese A-share listed companies from 2010–2021 to explore the influence of digital transformation on the turnaround of declining firms.

The research findings show that digital transformation contributes to the turnaround of declining firms. Mechanism analyses demonstrate that digital transformation enhances dynamic capabilities and attracts more analysts, thereby facilitating the turnaround process. Moreover, the moderation analysis reveals that CEO equity incentives strengthen the positive correlation between digital transformation and the turnaround of declining firms. Heterogeneity analysis indicates that the association between digital transformation and the turnaround of declining firms is particularly significant for firms with low financing constraints and high-tech firms. Moreover, this research reveals that digital transformation can facilitate the turnaround of firms in deep and long-term decline.

This research contributes to the literature on the digital transformation of enterprises and provides important insights for the turnaround of declining firms.

This paper examines the impact of corporate digital transformation on employee satisfaction. Therefore, this study extends our understanding of the economic consequences of corporate digital transformation from employees’ perspectives.

The data used to construct our main proxy of employee satisfaction are collected from Kanzhun.com, which provides reviews by rank-and-file employees on their employers. This study uses a large sample of Chinese firms and adopts various empirical methods to examine the impact of digital transformation on employee satisfaction.

We find a significant positive relationship between corporate digital transformation and employee satisfaction. Moreover, we document that the relationship between corporate digital transformation and employee satisfaction is more pronounced in firms with higher labor intensity and in state-owned enterprises (SOE).

One significant limitation is that corporate digital transformation is constructed based on word frequency analysis. This approach may be influenced by variations in corporate disclosure practices and might not accurately capture the true extent of corporate digital transformation. This limitation is not only present in our research but is also pervasive in many other studies that utilize similar methodologies. Therefore, our results should be interpreted with this caveat in mind.

Our study suggests that corporate digital transformation enhances employee satisfaction, providing direct evidence for managers and regulators to promote corporate digital transformation. Through digital transformation, companies can not only improve operational efficiency but also foster employee satisfaction. This dual benefit underscores the importance of investing in corporate digital transformation for long-term success.

Our study suggests that corporate digital transformation enhances employee satisfaction, providing direct evidence for managers and regulators to promote corporate digital transformation. Through digital transformation, companies can not only improve operational efficiency but also foster employee satisfaction. This dual benefit underscores the importance of investing in corporate digital transformation for long-term success.

Our study contributes to the literature on the economic consequences of corporate digital transformation and extends existing research on the determinants of employee satisfaction. Additionally, it provides a novel measurement of employee satisfaction for a large sample of Chinese firms.

This study aims to understand how the assembly of rotating ring affects the axial forced vibration of gas face seals.

A three-mass kinematic model is established to investigate the axial movement of the rotating ring with bilateral constraints. The separation, collision and frictional sliding of the rotating ring in sleeve are discussed under rotor excitation. The effects of operating parameters and O-ring dynamic characteristics on the separation degree and film thickness disturbance are analyzed. A dimensionless axial characteristic force is defined to determine the critical conditions for the occurrence of separation. Several effective methods to eliminate the separation are proposed based on the adjustment of typical installation parameters.

Under rotor excitation, there may be two collisions between the rotating ring and the sleeve surfaces in one excitation period. This will cause self-excited vibration of the fluid film, increasing the risk of seal failure. The separation and collision can be prevented by increasing the equilibrium ratio, the installation radius of the O-ring on the outer surface of the rotating ring and the friction in the sleeve.

The results develop the modeling of multibody dynamics of gas face seals, enabling more accurate prediction of vibration characteristics.

Information is presented in various modalities such as text and images, and it can quickly and widely spread on social networks and among the general public through key communication nodes involved in public opinion events. Therefore, by tracking and identifying key nodes of public opinion, we can determine the direction of public opinion evolution and timely and effectively control public opinion events or curb the spread of false information.

This paper introduces a novel multimodal semantic enhanced representation based on multianchor mapping semantic community (MAMSC) for identifying key nodes in public opinion. MAMSC consists of four core components: multimodal data feature extraction module, feature vector dimensionality reduction module, semantic enhanced representation module and semantic community (SC) recognition module. On this basis, we combine the method of community discovery in complex networks to analyze the aggregation characteristics of different semantic anchors and construct a three-layer network module for public opinion node recognition in the SC with strong, medium and weak associations.

The experimental results show that compared with its variants and the baseline models, the MAMSC model has better recognition accuracy. This study also provides more systematic, forward-looking and scientific decision-making support for controlling public opinion and curbing the spread of false information.

We creatively combine the construction of variant autoencoder with multianchor mapping to enhance semantic representation and construct a three-layer network module for public opinion node recognition in the SC with strong, medium and weak associations. On this basis, our constructed MAMSC model achieved the best results compared to the baseline models and ablation evaluation models, with a precision of 91.21%.

For survival and prosperity, enterprises need to simultaneously engage in exploitation and exploration. Digital transformation is of great significance to enterprise innovation. However, the impacts of digital transformation on exploitation and exploration remain unclear. Moreover, the impacts of technological diversity on the relationships between digital transformation and exploitation and exploration are also unknown.

Based on an integrated perspective of dynamic capability theory and organizational inertia theory and using data from Chinese listed enterprises from 2007 to 2020, this study clarifies the effects of digital transformation on exploitation and exploration and assesses the moderating effect of technological diversity.

The results show that digital transformation improves exploitation, but negatively impacts exploration. Technological diversity mitigates the negative effect of digital transformation on exploration, but the moderating effect on the relationship between digital transformation and exploitation is not significant.

This study contributes to the existing literature on the digital paradox and provides guidance for enterprises to clarify the direction of digital transformation.

This systematic review aims to comprehensively explore the existing literature on the use of corporate communication within the realm of social media.

A total of 136 peer-reviewed journal articles are explored and analysed using both performance and bibliometric analysis.

This review identifies five main findings: (1) trends in corporate social media research that highlight the growth trajectory of research on social media use for corporate disclosure, (2) geographical coverage of studies indicating the concentration of research in certain regions, such as the USA, followed by China and the UK, with notable gaps in others, such as developing countries, (3) theoretical frameworks employed demonstrate that various theoretical frameworks are utilized, although a significant portion of the studies do not specify any theoretical underpinning, (4) social media platforms studied, confirming Twitter to be the most studied channel followed by Facebook and (5) thematic analysis of articles on disclosure type that categorized the articles using bibliometric analysis into five themes of disclosure: general disclosure, corporate social responsibility-related information, financial information, CEO announcements and strategic news communication. A subsequent cross-theme analysis classifies disclosure determinants and consequences of corporate social media usage.

Through a comprehensive and systematic analysis of existing research, this review offers novel insights into the current state of corporate communication on social media. It consolidates current knowledge, highlights under-explored areas in the existing literature and proposes new directions and potential avenues for future research.

This paper aims to market analysis on the base many factors. Market analysis must be done correctly to increase the efficiency of smart grid technologies. On the other hand, it is not very possible for the company to make improvements for too many factors. The main reason for this is that businesses have constraints both financially and in terms of manpower. Therefore, a priority analysis is needed in which the most important factors affecting the effectiveness of the market analysis will be determined.

In this context, a new fuzzy decision-making model is generated. In this hybrid model, there are mainly two different parts. First, the indicators are weighted with quantum spherical fuzzy multi SWARA (M-SWARA) methodology. On the other side, smart grid technology investment projects are examined by quantum spherical fuzzy ELECTRE. Additionally, facial expressions of the experts are also considered in this process.

The main contribution of the study is that a new methodology with the name of M-SWARA is generated by making improvements to the classical SWARA. The findings indicate that data-driven decisions play the most critical role in the effectiveness of market environment analysis for smart technology investments. To achieve success in this process, large-scale data sets need to be collected and analyzed. In this context, if the technology is strong, this process can be sustained quickly and effectively.

It is also identified that personalized energy schedule with smart meters is the most essential smart grid technology investment alternative. Smart meters provide data on energy consumption in real time.