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This study aimed to facilitate a rapid evaluation of track service status and vehicle ride comfort based on car body acceleration. Consequently, a low-cost, data-driven approach was proposed for analyzing speed-related acceleration limits in metro systems.

A portable sensing terminal was developed to realize easy and efficient detection of car body acceleration. Further, field measurements were performed on a 51.95-km metro line. Data from 272 metro sections were tested as a case study, and a quantile regression method was proposed to fit the control limits of the car body acceleration at different speeds using the measured data.

First, the frequency statistics of the measured data in the speed-acceleration dimension indicated that the car body acceleration was primarily concentrated within the constant speed stage, particularly at speeds of 15.4, 18.3, and 20.9 m/s. Second, resampling was performed according to the probability density distribution of car body acceleration for different speed domains to achieve data balance. Finally, combined with the traditional linear relationship between speed and acceleration, the statistical relationships between the speed and car body acceleration under different quantiles were determined. We concluded the lateral/vertical quantiles of 0.8989/0.9895, 0.9942/0.997, and 0.9998/0.993 as being excellent, good, and qualified control limits, respectively, for the lateral and vertical acceleration of the car body. In addition, regression lines for the speed-related acceleration limits at other quantiles (0.5, 0.75, 2s, and 3s) were obtained.

The proposed method is expected to serve as a reference for further studies on speed-related acceleration limits in rail transit systems.

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.

This paper examines the evolving landscape of accounting and finance research on the Chinese capital market, building on a previous study published at Abacus in 2018.

By incorporating data from 1999 to 2023, our analysis offers a detailed examination of shifts in academic focus, methodological advancements and thematic expansions over the last quarter-century.

The study reveals a substantial increase in accounting and finance publications related to the Chinese capital market in both Tier 1 and Asia-Pacific journals. The dynamic growth of the Chinese capital market during this period reflects profound economic transformations, characterized by technological innovations, sustainability commitments and regulatory reforms.

We conclude that the globally important Chinese capital market has attracted increasing academic attention, significantly advancing the understanding of accounting and finance research in China’s capital market.

This study aims to investigate the influence of external factors identified by the Political, Economic, Social, Technological, Environmental and Legal (PESTEL) framework on corporate social responsibility (CSR) performance in Vietnamese construction firms.

The snowball sampling method was employed to gather 182 validated responses. Employing Partial Least Squares Structural Equation Modeling (PLS-SEM), the research analyzed how these factors correlate with CSR practices under institutional theory.

Results indicated that social, economic, environmental, legal and technological factors positively impacted CSR performance. Among these, social factors had the most significant effect, followed sequentially by economic, environmental, legal and technological influences. Intriguingly, political factors demonstrated no significant association with CSR performance.

The strong impact of social factors confirms that societal norms and cultural values are critical in shaping corporate behavior in Vietnam. Firms can leverage this insight by intensifying their community engagement and social investment. Additionally, the negligible role of political factors in shaping CSR suggests that firms might not need to focus heavily on political engagement in Vietnam. However, firms should remain aware of legal changes as legal factors influence CSR outcomes.

Despite CSR’s growing importance, there remains a notable research gap regarding how external macro-environmental factors influence CSR performance, particularly within the construction industry. The findings emphasize the importance of aligning business strategies with socioeconomic and environmental aspects.

Prefabricated buildings (PBs) have proven to effectively mitigate carbon emissions in the construction industry. Existing studies have analyzed the environmental performance of PBs considering the shift in construction methods, ignoring the emissions abatement effects of the low-carbon practices adopted by participants in the prefabricated building supply chain (PBSC). Thus, it is challenging to exploit the environmental advantages of PBs. To further reveal the carbon reduction potential of PBs and assist participants in making low-carbon practice strategy decisions, this paper constructs a system dynamics (SD) model to explore the performance of PBSC in low-carbon practices.

This study adopts the SD approach to integrate the complex dynamic relationship between variables and explicitly considers the environmental and economic impacts of PBSC to explore the carbon emission reduction effects of low-carbon practices by enterprises under environmental policies from the supply chain perspective.

Results show that with the advance of prefabrication level, the carbon emissions from production and transportation processes increase, and the total carbon emissions of PBSC show an upward trend. Low-carbon practices of rational transportation route planning and carbon-reduction energy investment can effectively reduce carbon emissions with negative economic impacts on transportation enterprises. The application of sustainable materials in low-carbon practices is both economically and environmentally friendly. In addition, carbon tax does not always promote the implementation of low-carbon practices, and the improvement of enterprises' environmental awareness can further strengthen the effect of low-carbon practices.

This study dynamically assesses the carbon reduction effects of low-carbon practices in PBSC, informing the low-carbon decision-making of participants in building construction projects and guiding the government to formulate environmental policies.

The research aims to explore the influence mechanism of peer feedback and users' knowledge contribution behavior. This study draws on the social identity theory and considers social identity as a mediating factor into the research framework.

This paper collected users' activity data of 142,191 ideas submitted by 76,647 users from the MIUI community between October 2010 and May 2018 via Python software, and data were processed using Stata 16.0.

The results indicate that knowledge feedback and social feedback positively influence users' knowledge contribution (quantity and quality), respectively. User's cognitive identity positively mediates the relationship between peer feedback and knowledge contribution behavior, affective identity positively mediates the relationship between peer feedback and knowledge contribution behavior, while evaluative identity positively mediates the relationship between peer feedback and knowledge contribution quality, but there is no mediating effect between peer feedback and knowledge contribution quantity.

This study advances knowledge management by highlighting peer feedback on online innovation communities. By demonstrating the significant mediating effect of social identity, this study empirically clarifies the relationships of peer feedback (knowledge feedback and social feedback) to specific dimensions of knowledge contribution, thereby providing managerial guidance to the online innovation community on incentivizing and managing user interaction to foster the innovation development of firms.

An understanding of the impact of construction workers informal safety communication (CWISC), a form of parallel safety communication between workers, on safety performance among construction workers is crucial in order to develop effective strategies for improving safety performance in the construction industry. However, research remains scant on the impact of CWISC on safety performance. This study empirically aims to test the relationship between these important constructs.

Statistical analysis was used to examine the relationship in a hypothetical model with two latent variables; the exogenous variables represented by two groups of informal safety communication: friends and crew members and the endogenous variables represented by two groups of Safety performance metrics: safety compliance and safety participation, was tested.

The emergent findings revealed that there is a significant relationship between informal safety communication among crew members and safety compliance, and also between informal safety communication among friends on construction sites and safety participation. These findings emphasize the importance of fostering effective safety communication and collaboration within construction crews, as well as recognizing the influence friendships on safety performance. Stakeholders can leverage on these findings to implement policies to improve safety performance.

The study presents insightful practical knowledge on how CWISC impacts safety performance on construction sites. Practical recommendations for organizations are also proposed, e.g., development of team-building activities, platforms for sharing safety-related information and experiences, mentorship programs and initiatives that encourage social interaction among workers.

Nano graphitic-carbon nitride (g-C₃N₄) is an emerging lubrication technology with excellent performance and significant potential for future applications. This study aims to investigate the effect of nano g-C₃N₄ as a lubricant additive on the wear performance of bearing steel disk.

Various mass fractions of g-C₃N₄ were introduced into the base oil. Combining tribological testing, rheological testing and surface analysis methods, the anti-wear properties and lubrication mechanisms were analyzed.

Transmission electron microscopy images revealed that the size of the nanoparticles of g-C₃N₄ ranges from 10 to 100 nm. Phase analysis of the g-C₃N₄ sample was conducted using X-ray diffraction. Further, 1.0% mass fraction of g-C₃N₄ in the base oil provides excellent anti-wear and friction-reducing performance. Compared to the base oil alone, it reduces the average friction coefficient by 63.8% and decreases the wear rate by 43.1%, significantly reducing the depth and width of the wear scar. Energy-dispersive X-ray spectroscopy and scanning electron microscope analysis revealed that the oil sample containing nano g-C₃N₄ can form a lubricating film on the sliding surface of bearing steel after wear, which enhances the lubricating properties of the base oil.

The synergistic effect of the base oil and nanoparticles reduces friction and wear and is expected to extend the service life of bearing steel. These findings suggest that incorporating nano g-C₃N₄ as a lubricant additive offers significant potential for improving the performance of mechanical components.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2024-0456/

The purpose of this study is to investigate the relationship between tourism development and urban housing prices in Chinese cities. Specifically, the study aimed to explore whether there is a relationship between the two variables in tourist and non-tourist cities and whether there is a non-linear relationship between them.

In this study, the entropy method was used to construct the China City Tourism Development Index, which provides a more comprehensive measure of the level of tourism development in different cities. In total, 45 major cities in China were studied using the panel data approach for the period of 2011 to 2019.

The empirical analysis conducted for this study found that tourism development affects urban house prices, and that there is an inverted U-shaped relationship. However, this varies across cities, with house prices in tourist cities tending to be more influenced by tourism development than non-tourist cities. Also, foreign direct investment, population size, fixed asset investment and disposable income per capita were found to have an impact on house prices in both tourism and non-tourism cities.

There are significant differences in tourism development and urban house prices in different cities in China. This study considers these differences when examining the impact of tourism on house prices in 45 major cities in China by dividing the sample cities into tourist and non-tourist cities.

This study aimed to propose a performance-oriented approach of automatically generative design and optimization of hospital building layouts in consideration of public health emergency, which intended to conduct reasonable layout design of hospital building to meet different performance requirements for both high efficiency during normal periods and low risk in the pandemic.

The research design follows a sequential mixed methodology. First, key points and parameters of hospital building layout design (HBLD) are analyzed. Then, to meet the requirements of high efficiency and low risk, adjacent preference score and infection risk coefficient are constructed as constraints. On this basis, automatic generative design is conducted to generate building layout schemes. Finally, multi-objective deviation analysis is carried out to obtain the optimal scheme of hospital building layouts.

Automatic generative design of building layouts that integrates adjacent preferences and infection risks enables hospitals to achieve rapid transitions between normal (high efficiency) and pandemic (low risk) periods, which can effectively respond to public health emergencies. The proposed approach has been verified in an actual project, which can help systematically explore the solution for better decision-making.

The form of building layouts is limited to rectangles, and future work can explore conducting irregular layouts into optimization for the framework of generative design.

The contribution of this paper is the developed approach that can quickly and effectively generate more hospital layout alternatives satisfying high operational efficiency and low infection risk by formulating space design rules, which is of great significance in response to public health emergency.