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Following the growing adoption of social media, many entrepreneurs are launching personal social media channels. This study focuses on the effect of entrepreneurs' shared information on We Media platforms on the value relevance of their earnings.

Using entrepreneurs' We Media data collected from A-share-listed companies on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2018, this study investigates the effect of the data on the value relevance of earnings using the modified Ohlson model. The authors applied textual analysis to retrieve entrepreneurial We Media data acquired manually from Weibo.

We Media platforms can increase the value relevance of earnings. Entrepreneurs can enhance investor trust by establishing social ties with investors. Investors are more likely to recognize earnings information publicized by enterprises, owing to internal consistency. Particularly, value relevance improves significantly with more personal information being posted and more “likes” being acquired on entrepreneurs' We Media accounts. This positive effect is more obvious in privately owned and highly marketized regions.

The findings extend the research on the economic consequences of We Media as an important information channel, enrich the research on the social media posting behavior of entrepreneurs and provide a reference for enterprises to instill trust using new information disclosure methods and for governments to establish a safe internet environment to promote the sustainable development of the capital market.

The purpose of this paper is to study the relationship between high temperature oxidation and temperature rise rate of engine oil attempted to explore a new indicator to evaluate oil degradation.

Accelerated oxidation test combined with molecular simulation and road test is carried out in this paper. The temperature rise characteristics of mineral oil and synthetic oil under different oxidation temperatures (140°C, 155°C and 170°C) and time (50 h, 100 h, 150 h and 200 h) were determined by accelerated oxidation. The mechanism of temperature change characteristics of used oils was analyzed with molecular simulation. Two experimental vehicles carried six road tests with synthetic and mineral oil.

The results of this study show that the temperature rise rate of oxidized mineral and synthetic oil is higher than the new oil. The temperature rise rate is proportional to the oxidation time and oxidation temperature. The synthetic engine oil temperature rise rate is lower than that of the mineral engine oil. The same result was obtained in road tests. Molecular simulation verifies that small molecules were generated after oil oxidation which results in intermolecular friction and increased heat generation.

This paper indicates that temperature rise rate has potential to be taken as an indicator to evaluate oil oxidation which provides a new way for engine oil analysis.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0177/

Under the repeated action of the construction load, opening deformation and disturbed deformation occurred at the precast box culvert joints of the shield tunnel. The objective of this paper is to investigate the effect of construction vehicle loading on the mechanical deformation characteristics of the internal structure of a large-diameter shield tunnel during the entire construction period.

The structural response of the prefabricated internal structure under heavy construction vehicle loads at four different construction stages (prefabricated box culvert installation, curved lining cast-in-place, lane slab installation and pavement structure casting) was analyzed through field tests and ABAQUS (finite element analysis software) numerical simulation.

Heavy construction vehicles can cause significant mechanical impacts on the internal structure, as the construction phase progresses, the integrity of the internal structure with the tunnel section increases. The vertical and horizontal deformation of the internal structure is significantly reduced, and the overall stress level of the internal structure is reduced. The bolts connecting the precast box culvert have the maximum stress at the initial stage of construction, as the construction proceeds the stress distribution among the bolts gradually becomes uniform.

This study can provide a reference for the design model, theoretical analysis and construction technology of the internal structure during the construction of large-diameter tunnel projects.

The purpose of this bibliometric study is to report research output and publications on the social determinants of health and health outcomes. This study condenses numerous studies into a single paper, which not only provides insights into the worldwide growth and advancement of the study field but also establishes a research agenda for the future.

Using the Scopus database, a thorough bibliometric study of the worldwide scientific output on social determinants of health from 2000 to 2021 was conducted. With the assistance of VOS viewer and R-based scientometric software, the worldwide development of research on social determinants of health was analysed through performance analysis and network map visualisation.

This study identified the most influential authors, studies, journals and affiliations in the field of social determinants of health, as well as the most co-cited authors and journals, based on a bibliometric analysis of 1,203 research papers retrieved from the Scopus database during the past two decades (2000–2021). Beginning in 2000 with one publication and ending in 2021, 274 articles were viewed online, relevant to the social determinants of health. From 2014 to 2021, publications continue to grow at an accelerating pace.

To the best of the authors’ knowledge, this is one of the first studies to review the social determinants of health and its outcomes. The findings of the chosen studies represent a novel and important addition to the study of social determinants of health. It offers a comprehensive bibliometric analysis of publications, in addition to the identification of vital research trends.

Digitally driven virtual streamers are increasingly utilized in live-streaming commerce, possessing distinct advantages compared to human streamers. However, the applicable scenarios of virtual streamers are still unclear. Focusing on product attribute variances, this paper compares the livestreaming effects of virtual and human streamers to clarify the applicable scenarios for each and assist companies in strategically choosing suitable streamers.

We conducted four experiments utilizing both images and video as stimulus materials, and each experiment employed different products. To test the proposed model, a total of 1,068 valid participants were recruited, encompassing a diverse group of individuals, including undergraduates and employed workers.

The results indicate no significant difference between virtual and human streamers in increasing consumers’ purchase intention for utilitarian products. In contrast, human streamers are more effective in enhancing consumer purchase intention for hedonic products, with a mediating role of mental imagery quality. Consumers’ implicit personality variances also influence their willingness to accept virtual streamers.

This paper is the first to compare the effects of virtual and human streamers in promoting different products to enhance our comprehension of virtual streamers. Given the potential risks associated with human streamers, a comprehensive understanding of the role of virtual streamers is imperative for brands when deploying live-streaming commerce activities.

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.

Construction workers’ safety behavior has been proven to be crucial in preventing occupational injuries and improving workplace safety, and organizational safety support provides essential resources to promote such behavior. However, the specific mechanisms of how organizational safety support affects safety behavior have not been thoroughly explored. Therefore, this study explored the relationship between workers’ perceived organizational safety support (perceived supervisor/coworker safety support) and safety behavior (safety task/contextual behavior), while considering the mediating effects of safety motivation, emotional exhaustion, and the moderating effect of psychosocial safety climate.

Based on the quantitative research method, the hypothesis was tested. The data were collected from 500 construction workers using a structured questionnaire. Observed variables were tested using confirmatory factor analysis, and the path coefficient of fitted model was then analyzed including the associated mediating and moderating effects.

The study found that (1) safety support from both supervisors and coworkers directly forecasted both types of safety behavior, (2) safety motivation was primarily predicted by perceived supervisor safety support, and perceived coworker safety support better predicted emotional exhaustion. Safety motivation mediated the relationship between perceived supervisor safety support and safety contextual behavior, and emotional exhaustion mediated the relationship between both types of safety support and both types of safety behavior, (3) psychosocial safety climate moderated the pathway relationships mediated by safety motivation and emotional exhaustion, respectively.

The samples of this study were mostly immersed in eastern culture and the construction industry, and the cultural and industry diversity of the samples deserves further consideration to enhance the universality of the results. The cross-sectional approach may have some impact on the accuracy of the results. In addition, other potential mediating variables deserve to be explored in future studies.

This study provides a new basis for extending current theoretical frameworks of organizational safety support and safety behavior by using a moderated mediation model. Some practical insights on construction safety management have also been proposed based on the research findings. It is recommended that practitioners should further raise awareness of the critical role of supervisor-worker and worker-coworker relationships, as high levels of safety support from the supervisor/worker respectively effectively encourage safety motivation, alleviate emotional exhaustion, and thus improve workers’ safety performance. Meanwhile, the psychosocial health conditions of workers should also receive further attention.

Graded honeycombs are materials that exhibit better energy absorption performance compared to uniform honeycombs without adding additional weight. This paper introduces a novel modularized graded honeycomb into a commercial crash box to improve its crashworthiness.

A modularized graded honeycomb is inserted into a commercial crash box to develop a novel crash box. Finite element analyses are conducted to investigate the crashworthiness. Pareto cumulative influence analysis is conducted to rank the effects of design parameters on crashworthiness. A surrogate model-based multi-objective optimization is carried out to improve energy absorption while limiting the impact peak force. An optimal Pareto solution set is obtained.

Modularized honeycomb-filled crash box outperforms that of its corresponding uniform honeycomb-filled crash box and empty crash box in resisting impact. Pareto cumulative influence analysis reveals that for most crashworthiness indicators, cell-wall thicknesses of crash box tube contribute the most, followed by average relative density and graded coefficient of modularized honeycomb (MH). Graded coefficient contributes nearly 10% on mean force and maximum displacement, but it has insignificant influence on peak force and weight. Optimization results show that the optimal designs can not only absorb more energy but also limit the peak force compared with those of uniform honeycomb-filled crash box.

This paper fills a MH into a commercial crash box to propose a novel crash box and demonstrates the positive impact of modularized design on crashworthiness compared with that of uniform honeycomb-filled crash box. Moreover, modularizing honeycomb does not change the weight of the filler, and thus, the novel crash box would benefit development of crash box with lightweight and excellent energy absorption capacity.

The purpose of this paper is to establish a maturity evaluation model for the application of construction steel structure welding robotics suitable for the actual situation and specific characteristics of engineering projects in China and then to assess the maturity level of the technology in the application of domestic engineering projects more scientifically.

The research follows a qualitative and quantitative analysis method. In the first stage, the structure of the maturity model is constructed and the evaluation index system is designed by using the ideas of the capability maturity model and WSR methodology for reference. In the second stage, the design of the evaluation process and the selection of evaluation methods (analytic hierarchy process method, multi-level gray comprehensive evaluation method). In the third stage, the data are collected and organized (preparation of questionnaires, distribution of questionnaires, questionnaire collection). In the fourth stage, the established maturity evaluation model is used to analyze the data.

The evaluation model established by using multi-level gray theory can effectively transform various complex indicators into an intuitive maturity level or score status. The conclusion shows that the application maturity of building steel structure welding robot technology in this project is at the development level as a whole. The maturity levels of “WuLi – ShiLi – RenLi” are respectively: development level, development level, between starting level and development level. Comparison of maturity evaluation values of five important factors (from high to low): environmental factors, technical factors, management factors, benefit factors, personnel and group factors.

In this paper, based on the existing research related to construction steel structure welding robot technology, a quantitative and holistic evaluation of the application of construction steel structure welding robot technology in domestic engineering projects is conducted for the first time from a project perspective by designing a maturity evaluation index system and establishing a maturity evaluation model. This research will help the project team to evaluate the application level (maturity) of the welding robot in the actual project, identify the shortcomings and defects of the application of this technology, then improve the weak links pertinently, and finally realize the gradual improvement of the overall application level of welding robot technology for building steel structure.

A precise estimation of the evolutionary power spectral density (EPSD) of typhoon wind speed is a difficult and significant undertaking in the analysis of turbulence effects on large-expansive structures. A majority of the prevailing EPSD estimation techniques rely on complex signal processing methodologies, such as wavelet decomposition, Hilbert–Huang transformation and time-varying autoregressive moving average (ARMA) model. However, these approaches often pose challenges in terms of comprehensibility and practical implementation for engineers. In light of this issue, the present study introduces a straightforward and effective EPSD estimation method tailored specifically for typhoon wind speed, aiming to facilitate its understanding and application in engineering contexts.

Firstly, the mathematical model of a uniformly modulated non-stationary process is employed to represent the typhoon wind speed. Secondly, the reverse arrangement test serves as an auxiliary tool in conjunction with wavelet transform or empirical mode decomposition, aiding in the determination of the optimal slowly varying mean wind speed. Thirdly, Kernel regression technique is utilized to discern the time-dependent standard deviation of wind speed fluctuations. Finally, the power spectral density (PSD) of wind speed residuals is computed to facilitate the estimation of the EPSD.

Firstly, the reverse arrangement test-assisted approach enables the determination of an optimal time-dependent mean from the candidate results obtained through discrete wavelet transform (DWT) and empirical mode decomposition (EMD). Secondly, the application of the Kernel regression technique facilitates accurate identification of the time-dependent variance from the fluctuating wind speed data. Thirdly, due to the influence of the extreme weather, the Gaussianity of the reduced turbulent fluctuations in typhoon wind is easily disturbed, resulting in the obvious non-Gaussian features.

This paper employs the mathematical model of uniformly modulated non-stationary process to characterize typhoon wind speeds and then proposes a straightforward and efficient method for estimating the EPSD of typhoon wind. The accuracy and efficacy of the presented estimation method are verified using the field-measured wind speed data from Typhoon Rammasun. The proposed EPSD estimation method for typhoon wind exhibits suitability for engineering applications owing to its simplicity and computational efficiency.