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To explore the economical and reasonable semi-rigid permeable base layer ratio, solve the problems caused by rainwater washing over the pavement base layer on the slope, improve its drainage function, improve the water stability and service life of the roadbed pavement and promote the application of semi-rigid permeable base layer materials in the construction of asphalt pavement in cold regions.

In this study, three semi-rigid base course materials were designed, the mechanical strength and drainage properties were tested and the effect and correlation of air voids on their performance indexes were analyzed.

It was found that increasing the cement content increased the strength but reduced the air voids and water permeability coefficient. The permeability performance of the sandless material was superior to the dense; the performance of the two sandless materials was basically the same when the cement content was 7%. Overall, the skeleton void (sand-containing) type gradation between the sandless and dense types is more suitable as permeable semi-rigid base material; its gradation is relatively continuous, with cement content? 4.5%, strength? 1.5 MPa, water permeability coefficient? 0.8 cm/s and voids of 18–20%.

The study of permeable semi-rigid base material with large air voids could help to solve the problems of water damage and freeze-thaw damage of the base layer of asphalt pavements in cold regions and ensure the comfort and durability of asphalt pavements while having good economic and social benefits.

Targeting the common functions of the Zhejiang Library website, elderly individuals were invited to complete six experimental tasks on the improved website interfaces, and subjective data (PAD emotion scale and usability evaluation) and objective data (eye movement data) were recorded to verify the effects of graphic layout and navigation position on the information-seeking experience of elderly individuals.

This study analyzes the effect of the graphic layout and navigation position of the Zhejiang Library’s website interface on the emotional state, perceived usability and information-seeking time of elderly individuals, with the aim of providing guidance and suggestions for the elderly-oriented reform of the public library website.

The experimental results show that the graphic layout has a significant effect on the emotional state and perceived usability of elderly individuals, and the navigation position has a significant effect on the information-seeking time; the interaction between graphic layout and navigation position exerts a significant effect on the information-seeking time of elderly individuals. The eye movement data show that elderly individuals have a better information-seeking experience when the top navigation bar and image-text matched arrangement are used for the interface layout.

This study adopts a new approach combining subjective data and eye movement data to evaluate the effect of the public library website’s interface layout on the information-seeking experience for older people. The findings can provide a theoretical basis and methodological support for the elderly-oriented reform of public library websites. They can also provide scientific design suggestions for age-friendly interface layouts of other Internet products and service applications.

Traffic flow prediction has always been a top priority of intelligent transportation systems. There are many mature methods for short-term traffic flow prediction. However, the existing methods are often insufficient in capturing long-term spatial-temporal dependencies. To predict long-term dependencies more accurately, in this paper, a new and more effective traffic flow prediction model is proposed.

This paper proposes a new and more effective traffic flow prediction model, named channel attention-based spatial-temporal graph neural networks. A graph convolutional network is used to extract local spatial-temporal correlations, a channel attention mechanism is used to enhance the influence of nearby spatial-temporal dependencies on decision-making and a transformer mechanism is used to capture long-term dependencies.

The proposed model is applied to two common highway datasets: METR-LA collected in Los Angeles and PEMS-BAY collected in the California Bay Area. This model outperforms the other five in terms of performance on three performance metrics a popular model.

(1) Based on the spatial-temporal synchronization graph convolution module, a spatial-temporal channel attention module is designed to increase the influence of proximity dependence on decision-making by enhancing or suppressing different channels. (2) To better capture long-term dependencies, the transformer module is introduced.

This paper identifies the development of and gaps in knowledge in various management disciplines, including international marketing in relation to political ties in emerging markets, based on a systematic review of the related literature. The paper develops a synthesized integrative framework and provides a research agenda and pathways for future research.

The study adopts the systematic literature review protocol to investigate the ways in which political ties have been examined in the management literature in various disciplines, such as international business, marketing, entrepreneurship, strategy, innovation, and organization. In total, 114 articles published in peer-reviewed journals from 2000 to 2022 were analyzed.

The authors believe that studying the impact of political ties on firm outcomes is timely and important as interest in this area of research is growing rapidly. The review reveals that the diverse conceptual and methodological approaches adopted in different management disciplines have resulted in inconclusive and mixed findings on the relationship between political ties and performance.

This is one of the few systematic literature reviews of political ties and firm performance in emerging markets. The authors clarify some of the ambiguities around the subject and offer a path forward for developing current understanding and insights. The study also highlights the major perspectives in management and clarify the similarities and differences in the conceptualization of political ties. In addition, the authors develop an integrative framework of the political ties–performance link in emerging markets.

Unconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.

The surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.

To address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.

This study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.

This chapter proposes a conceptualization of joyful leadership as a unique leadership style and identifies a future research agenda to further explore the concept. While the concept of joyful leadership appears repeatedly in the nonacademic literature, including in blogs, vlogs, and podcasts, there is limited reference to joyful leadership in the academic literature highlighting a lack of academic rigor around the concept. Joyful leadership is proposed as a unique leadership style with specific patterns of behavior demonstrated by the leader. This research draws on understandings of emotion, positive affect, and leadership in the academic literature to develop a conceptualization of joyful leadership.

The proposed conceptualization is based on an extensive literature review drawing from both the leadership field and the study of emotions including various theoretical perspectives from these diverse fields.

Based on discrete emotion theory a conceptualization of joyful leadership as a unique leadership style is presented, identifying key patterns of behavior associated with joyful leadership including discrete autonomic patterns, actions, nonverbal signals, and identified feelings.

This research outlines a conceptual model to provide an understanding of the concept of joyful leadership as a unique leadership style. It draws on the current study of emotion, positive affect, and leadership and more specifically examines the concept of joyful leadership aligned to discrete emotion theory. This particular theory of emotion, when examined in relation to leadership, provides a basis for the concept of joyful leadership as a leadership style and the basis for its proposed characteristics and outcomes.

Despite the opportunities of digital twins (DTs) for smart buildings, limited research has been conducted regarding the facility management stage, and this is explained by the high complexity of accurately representing and modelling the physics behind the DTs process. This study thus organises and consolidates the fragmented literature on DTs implementation for smart buildings at the facility management stage by exploring the enablers, applications and challenges and examining the interrelationships amongst them.

A systematic literature review approach is adopted to analyse and synthesise the existing literature relating to the subject topic.

The study revealed six main categories of enablers of DTs for smart building at the facility management stage, namely perception technologies, network technologies, storage technologies, application technologies, knowledge-building and design processes. Three substantial categories of DTs application for smart buildings were revealed at the facility management stage: efficient operation and service monitoring, efficient building energy management and effective smart building maintenance. Subsequently, the top four major challenges were identified as being “lack of a systematic and comprehensive reference model”, “real-time data integration”, “the complexity and uncertainty nature of real-time data” and “real-time data visualisation”. An integrative framework is finally proposed by examining the interactive relationship amongst the enablers, the applications and the challenges.

The findings could guide facility managers/engineers to fairly understand the enablers, applications and challenges when DTs are being implemented to improve smart building performance and achieve user satisfaction at the facility management stage.

This study contributes to the knowledge body on DTs by extending the scope of the existing studies to identify the enablers and applications of DTs for smart buildings at the facility management stage and the specific challenges.

New generation of construction workers (NGCWs) who were born in the 1980s and later have gradually become the main workforce of Chinese construction industry. They may behave differently when dealing with knowledge-related activities due to divergent characteristics caused by generational discrepancy. To provide a theoretical foundation for construction companies and safety managers to improve safety management, this research explores the factors and paths impacting the NGCWs' ability to share their safety knowledge.

Based on literature review, main factors that influence the safety knowledge sharing of the NGCWs were identified. Decision-Making Trial and Evaluation Laboratory and Interpretive Structural Modeling were applied to identify the hierarchical and contextual relations among the factors influencing the safety knowledge sharing of the NGCWs.

The results showed that sharing atmosphere ranked first in centrality and had a high degree of influence and being influenced, indicating itself an extremely important influencing factor of safety knowledge sharing of NGCWs. Six root influencing factors were identified, including individual characteristics, work pressure, sharing platform, incentive mechanism, leadership support and safety management system.

The number of influencing factors of safety knowledge sharing of the NGCWs identified in this study is limited, and the data obtained by the expert scoring method is subjective. In future studies, the model should be further developed and validated by incorporating experts from different fields to improve its integrity and applicability.

The influencing factors identified in this paper can provide a basis for construction companies and safety managers to improve productivity and safety management by taking relevant measures to promote safety knowledge sharing. The research contributes to the understanding knowledge management in the context of the emerging market. It helps to answer the question of how the market can maintain the economic growth success through effective knowledge management.

This paper investigates the influencing factors of NGCWs' safety knowledge sharing from the perspective of intergenerational differences, and the 13 influencing factor index system established expands the scope of research on factors influencing safety knowledge sharing among construction workers and fills the gap in safety knowledge sharing research on young construction workers. Furthermore, this paper establishes a multi-layer recursive structure model to clarify the influence path of the influencing factors and contributes to the understanding of safety knowledge sharing mechanism.

From an agency perspective, the authors investigate whether family ownership and control configurations are systematically associated with a firm's choice of auditor and audit fees. Agency theory is an economic theory that purposes the existence of a contract between two parties, principals and agents. Auditor choice and audit fees by family firms provide interesting insights given the unique nature of the agency problems faced by such firms.

The authors employ Big-4 auditors (PWC, KPMG, E&Y and Deloitte) as a proxy for high quality auditor (Big N) for the auditor choice model. For the audit fee model, the dependent variable is the natural logarithm of audit fees (LnAF). The authors use two measures for family firm as explanatory variables: (1) a dummy variable (FAM_Control), which equals one if the firm is classified as a family firm and (2) FAM_Ownership, which is an indicator variable with a value of one if a firm has family members who hold CEO position, occupy board seats, or hold at least 10% of the firm's equity. Data of Chinese listed firms from 2011 to 2021 are used. The authors adopt the Heckman (1979) two-stage model to mitigate the potential endogeneity issue involved in the selection of Big-N auditors.

The findings suggest that compared with non-family firms, Chinese family firms have a less tendency to employ Big-4 auditors due to less severe agency problems between owners and managers. Additionally, Chinese family firms sustain higher audit fees than non-family firms. Similar to the prior literature, however, Chinese family firms audited by Big-4 auditors incur lower audit fees than family firms audited by non-Big-4 auditors in this study. In contrast to young-family firms, old-family firms are less likely to pick top-tier auditors and sustain lower audit fees. Consistent and robust results are found from endogeneity tests and sensitivity analyses.

The empirical evidence provides a unique insight, for accounting practitioners, policymakers, family owners and other capital market participants concerning the diverse effects of various family ownership and control features on selecting high-quality auditors and audit fees. This study advances the understanding, showing that a lower demand for audit quality occurs in Chinese family firms as they encounter less severe Type I agency problems. However, the more severe Type II agency problems in Chinese family firms sustain higher audit fees due to higher audit risk and greater audit effort.

The multisource uncertainties, including material dispersion, load fluctuation and geometrical tolerance, have crucial effects on fatigue performance of turbine bladed disks. In view of the aim of this paper, it is essential to develop an advanced approach to efficiently quantify their influences and evaluate the fatigue life of turbine bladed disks.

In this study, a novel combined machine learning strategy is performed to fatigue assessment of turbine bladed disks. Proposed model consists of two modeling phases in terms of response surface method (RSM) and support vector regression (SVR), namely RSM-SVR. Two different input sets obtained from basic variables were used as the inputs of RSM, then the predicted results by RSM in first phase is used as inputs of SVR model by using a group data-handling strategy. By this way, the nonlinear flexibility of SVR inputs is improved and RSM-SVR model presents the high-tendency and efficiency characteristics.

The accuracy and tendency of the RSM-SVR model, applied to the fatigue life estimation of turbine bladed disks, are validated. The results indicate that the proposed model is capable of accurately simulating the nonlinear response of turbine bladed disks under multisource uncertainties, and SVR-RSM model provides an accurate prediction strategy compared to RSM and SVR for fatigue analysis of complex structures.

The results indicate that the proposed model is capable of accurately simulate the nonlinear response of turbine bladed disks under multisource uncertainties, and SVR-RSM model provides an accurate prediction compared to RSM and SVRE for fatigue analysis of turbine bladed disk.