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Job stressors have a considerable influence on workplace safety behaviors. However, the findings from previous studies regarding the effect of different types of job stressors have been contradictory. This is attributable to, among other factors, the effectiveness of job stressors varying with occupations and contexts. This study examines the effects of challenge and hindrance stressors on construction workers' informal safety communication at different levels of coworker relationships.

A three-dimensional framework of informal safety communication is adopted, including self-needed, citizenship and participatory safety communication. Stepwise regression analysis is then performed using questionnaire survey data collected from 293 construction workers in the Chinese construction industry.

The results demonstrate that both challenge and hindrance stressors are negatively associated with self-needed and citizenship safety communication, whereas their relationships with participatory safety communication are not significant. Meanwhile, the mitigation effects of the coworker relationship (represented by trustworthiness and accessibility) on the above negative impacts vary with the communication forms. Higher trustworthiness and accessibility enable workers faced with challenge stressors to actively manage these challenges and engage in self-needed safety communication. Similarly, trustworthiness promotes workers' involvement in self-needed and citizenship safety communication in the face of hindrance stressors, but accessibility is only effective in facilitating self-needed safety communication.

By introducing the job demands-resources theory and distinguishing informal safety communication into three categories, this study explains the negative effects of challenge and hindrance job stressors in complex and variable construction contexts and provides additional clues to the current inconsistent findings regarding this framework. The diverse roles of challenge and hindrance job stressors also present strong evidence for the need to differentiate between the types of informal safe communication.

This study aims to explore the influence mechanism of inclusive leadership on employees' innovative behavior, in order to provide useful inspiration for leaders and enterprises to develop.

This study constructs a moderated mediation model based on the valid questionnaire data of 211 employees in service in enterprises and used SPSS23.0 and AMOS24.0 analysis software to analyze the data and test the theoretical hypotheses, and explore the influence mechanism of inclusive leadership on employees' innovative behavior.

The empirical findings show that inclusive leadership has a significant positive impact on employees' innovative behavior; organizational harmony plays a mediating role in the relationship between inclusive leadership and employees' innovative behavior; and innovation self-efficacy plays a positive moderating role between organizational harmony and employees' innovative behavior. Therefore, inclusive leadership can create a harmonious organizational climate and further improve employees' innovative behavior under the influence of employees' creative self-efficacy, which can promote innovative behavior and sustainable development of enterprises.

The authors put two variables, organizational harmony and employees' innovation self-efficacy, into the same model for correlation tests for the first time, and introduced into the mechanism of inclusive leadership's influence on employees' innovation behavior, which broadened people's understanding of organizational harmony and innovation self-efficacy and broadened the ideas for the subsequent research about the relationship between them.

Aspect-based sentiment analysis (ASA) is a task of sentiment analysis that requires predicting aspect sentiment polarity for a given sentence. Many traditional techniques use graph-based mechanisms, which reduce prediction accuracy and introduce large amounts of noise. The other problem with graph-based mechanisms is that for some context words, the feelings change depending on the aspect, and therefore it is impossible to draw conclusions on their own. ASA is challenging because a given sentence can reveal complicated feelings about multiple aspects.

This research proposed an optimized attention-based DL model known as optimized aspect and self-attention aware long short-term memory for target-based semantic analysis (OAS-LSTM-TSA). The proposed model goes through three phases: preprocessing, aspect extraction and classification. Aspect extraction is done using a double-layered convolutional neural network (DL-CNN). The optimized aspect and self-attention embedded LSTM (OAS-LSTM) is used to classify aspect sentiment into three classes: positive, neutral and negative.

To detect and classify sentiment polarity of the aspect using the optimized aspect and self-attention embedded LSTM (OAS-LSTM) model. The results of the proposed method revealed that it achieves a high accuracy of 95.3 per cent for the restaurant dataset and 96.7 per cent for the laptop dataset.

The novelty of the research work is the addition of two effective attention layers in the network model, loss function reduction and accuracy enhancement, using a recent efficient optimization algorithm. The loss function in OAS-LSTM is minimized using the adaptive pelican optimization algorithm, thus increasing the accuracy rate. The performance of the proposed method is validated on four real-time datasets, Rest14, Lap14, Rest15 and Rest16, for various performance metrics.

Using the Shanghai pilot free trade zone (SPFTZ) as the testing ground for further reform and opening up,the links between global value chain (GVC) and pilot free trade zone (PFTZ) programs are mutually reinforcing. GVC creates opportunities for companies to use PFTZ to reduce their costs and increase their competitiveness, while PFTZ can facilitate the movement of goods within GVC and promote the development of GVC by attracting foreign investment. Overall, in SPFTZ, the industrial structure is promoted due to trade and investment facilitation, innovation promotion, and comprehensive service platform inside SPFTZ.

This study examined industrial upgrading in GVC (IUGVC) using five indicators under three quantitative dimensions: product, process, and skill upgrading. Difference-in-Differences (DID) model is employed for the impact assessment of SPFTZ. Parallel trend analysis and Granger causality analysis are performed to check the reliability of DID outcome. Finally, robustness test using exogenous control variables are carried out.

A positive impact of SPFTZ is found on IUGVC, which is due to promoting effect of SPFTZ on foreign direct investment and technological innovation. Based on the study's findings, policy recommendations are given, such as providing business support to enterprises operating inside a PFTZ.

From a GVC perspective, the impact of theSPFTZ establishment on IUGVC cannot be ignored, and is so far missing in the literature.

This study aims to clarify the relationship between the coefficient of friction (COF) and temperature of aluminum-based brake discs.

Three friction blocks with different COFs are examined by a TM-I-type reduced-scale inertial braking dynamometer. On this basis, the thermo-mechanically coupled model of friction pairs is established to study the evolution of brake disc temperature under different COFs using ADINA software.

Results indicate that the calculated disc temperature field matches the experimental well. The effect of COF on the peak temperature is magnified by the braking speed. With the COF increasing, the rise rate of instantaneous peak temperature is accelerated, and the dynamic equilibrium period and cooling-down period are observed in advance. The increase in COF promotes the area ratio of the high-temperature zone and the maximum radial temperature difference. When the COF is increased from 0.245 to 0.359 and 0.434 at 140 km/h, the area ratio of high-temperature zone increases from 12% to 44% and 49% and the maximum radial temperature difference increases from 56°C to 75°C and 83°C. The sensitiveness of the axial temperature difference to the COF is related to the braking time. The maximum axial temperature difference increases with COF in the early stages of braking, while it is hardly sensitive to the COF in the later stages of braking.

The effect of COF on the aluminum-based brake disc temperature is revealed, providing a theoretical reference for the popularization of aluminum-based brake discs and the selection of matching brake pads.

This study aims to investigate the influence of parent company personnel embedding on the stock price crash risk (SPCR) of listed companies, along with the moderating effect of disparate locations between parent and subsidiary companies and other major shareholders.

This research empirically tests hypotheses based on a sample of listed subsidiaries in China during the period between 2006 and 2021.

Our results demonstrate that personnel embeddedness in the parent company significantly alleviates SPCR in subsidiaries. This effect is even more substantial when the parent and subsidiary companies are in different places. However, other major shareholders in the subsidiary company weaken it. Our additional analysis indicates that, relative to executive embeddedness, director embeddedness exerts a stronger effect on the SPCR of the subsidiary. Mechanism examination reveals that the information asymmetry and the level of internal control (IC) within the subsidiary are significant channels through which the personnel embeddedness from the parent company influences the SPCR of the subsidiary.

This study expands the literature on how personnel arrangements in corporate groups within emerging countries influence SPCR. We have extended the traditional concept of interlocking directorates to corporate groups, thereby broadening the understanding of the governance effects of interlocking directors and executives from a group perspective.

This study aims to integrate the resource-based view (RBV) with other theories that consider external factors necessary to respond successfully to dynamic and uncertain entrepreneurial business conditions.

The paper introduces an multi-criteria decision-making (MCDM) approach, utilizing the axial-distance-based aggregated measurement (ADAM) method with weights determined by the preference selection index (PSI) method, to rank eight European countries based on the Global Entrepreneurship Monitor (GEM) data. Additionally, the paper extends the existing entrepreneurial ecosystem taxonomy (EET), offering an additional classification.

The performed analysis emphasizes the importance and necessity of involving different dimensions of EE in assessing the countries' entrepreneurship performance, which facilitates creating adequate policy measures.

The crucial limitations are assessments based only on the GEM data from a particular period, possibly leading to a certain bias. Future research should involve data from various resources to increase the results' reliability.

The ranking results and country classification obtained using the ADAM-based approach and two distinct taxonomies served as the basis for formulating tailored policy recommendations, aiming to formulate tailored policy implications for increasing the number of new entrepreneurs and improving innovativeness, sustainability and internationalization of existing entrepreneurs for each group of countries.

The study aims to examine the indirect relationships via application (app) brand self-relevance emotions and self-relevance that underlie the relationships between perceived value of mobile apps and (brand) love with respect to mobile apps. The study further investigates the moderating role of user–app relationship duration in the formation process of brand love for mobile apps from a dynamic and long-term perspective.

A multiple moderated-mediation model is developed and empirically tested with a sample of 396 users of popular Chinese mobile educational apps.

The study reveals that utilitarian value exhibits positive indirect relationships with brand love for mobile apps through increased positive self-relevance emotions. All three types of perceived value of mobile apps (utilitarian, hedonic and social) affect app brand love positively via self-relevance. These three types of perceived value were found to be serially linked to brand love through self-relevance and self-relevance emotions. Furthermore, empirical evidence is found for the moderating effects of user–app relationship duration.

By testing mechanisms simultaneously in an integrative model, this study investigates the reasons for app brand love that attract a user into a lasting relationship with an app and extends knowledge of the app brand love building process in inducing strong and positive brand–self connections. Our study also makes practical contributions by offering insights into delivering the most desired benefits to mobile app users according to different contextual conditions, in order to attract and retain users in a more cost-effective manner.

The classical advection-dispersion equation (ADE) model cannot accurately depict the gas transport process in natural geological formations. This paper aims to study the behavior of CO₂ transport in fractal porous media by using an effective Hausdorff fractal derivative advection-dispersion equation (HFDADE) model.

Anomalous dispersion behaviors of CO₂ transport are effectively characterized by the investigation of time and space Hausdorff derivatives on non-Euclidean fractal metrics. The numerical simulation has been performed with different Hausdorff fractal dimensions to reveal characteristics of the developed fractal ADE in fractal porous media. Numerical experiments focus on the influence of the time and space fractal dimensions on flow velocity and dispersion coefficient.

The physical mechanisms of parameters in the Hausdorff fractal derivative model are analyzed clearly. Numerical results demonstrate that the proposed model can well fit the history of gas production data and it can be a powerful technique for depicting the early arrival and long-tailed phenomenon by incorporating a fractal dimension.

To the best of the authors’ knowledge, first time these results are presented.

This study holistically and systematically consolidates the available research on digital reading to reveal the research trends of the past 20 years. Moreover, it explores the thematic evolution, hotspots and developmental characteristics of digital reading. This study, therefore, has the potential to serve as a research guide to researchers and educators in relevant fields.

The authors applied a bibliometric approach using Derwent Data Analyzer and VOSviewer to retrieve 2,456 publications for 2003–2022 from the Web of Science (WoS) database.

The results revealed that most studies' participants were university students and the experimental methods and questionnaires were preferred in digital reading researches. Among the influential countries or regions, institutions, journals and authors, the United States of America, University of London, Electronic Library and Chen, respectively, accounted for the greatest number of publications. Moreover, the authors identified the developmental characteristics and research trends in the field of digital reading by analyzing the evolution of keywords from 2003–2017 to 2018–2022 and the most frequently cited papers by year. “E-books,” “reading comprehension” and “literacy” were the primary research topics. In addition, “attention,” “motivation,” “cognitive load,” “dyslexia,” “engagement,” “eye-tracking,” “eye movement,” “systematic analysis,” “meta-analysis,” “smartphone” and “mobile reading/learning” were potential new research hotspots.

This study provides valuable insights into the current status, research direction, thematic evolution and developmental characteristics in the field of digital reading. Therefore, it has implications for publishers, researchers, librarians, educators and teachers in the digital reading field.