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Construction activities conducted in urban areas are often a source of significant noise disturbances, which cause psychological and health issues for residents as well as long-term auditory impairments for construction workers. The limited effectiveness of passive noise control measures due to the close proximity of the construction site to surrounding neighborhoods often results in complaints and eventually lawsuits. These can then lead to delays and cost overruns for the construction projects.

The paper proposes a novel approach to integrating construction noise as an additional dimension into scheduling construction works. To achieve this, a building information model, including the three-dimensional construction site layout object geometry, resource allocation and schedule information, is utilized. The developed method explores further project data that are typically available, such as the assigned equipment to a task, its precise location, and the estimated duration of noisy tasks. This results in a noise prediction model by using noise mapping techniques and suggesting less noisy alternative ways of construction. Finally, noise data obtained from sensors in a case study contribute real values for validating the proposed approach, which can be used later to suggest solutions for noise mitigation.

The results of this study indicate that the proposed approach can accurately predict construction noise given a few available parameters from digital project planning and sensors installed on a construction site. Proactively integrating construction noise control measures into the planning process has benefits for both residents and construction managers, as it reduces construction noise-related disturbances, prevents unexpected legal issues and ensures the health and well-being of the workforce.

While previous research has concentrated on real-time data collection using sensors, a more effective solution would also involve addressing and mitigating construction noise during the pre-construction work planning phase.

This study aims to prepare a low-formaldehyde and environmentally friendly glucose-lignin-based phenolic resin.

The authors directly used lignin to substitute formaldehyde to prepare lignin-based phenolic resin (LPF) with urea as formaldehyde absorbent. To improve the performance of the adhesive, the biobased glucose was introduced and the modified glucose-LPF (GLPF) was obtained.

The results showed that when the replacing amount of lignin to formaldehyde reached 15 Wt.%, the physical properties of the prepared LPF met the Chinese national standard, and the bonding strength increased by 21.9%, from 0.75 to 0.96 MPa, compared with PF. The addition of glucose boost the performance of wood adhesive, for example, the free phenol content of the obtained GLPF was significantly reduced by 79.11%, from 5.60% to 1.17%, the bonding strength (1.19 MPa) of GLPF increased by 19.3% in comparison to LPF and the curing temperature of GLPF decreased by 13.08%.

The low-formaldehyde and environmentally friendly GLPF has higher bonding strength and lower curing temperature, which is profitable to industrial application.

The prepared GLPF has lower free formaldehyde and formaldehyde emission, which is cost-effective and beneficial to human health.

The joint work of lignin and glucose provides the wood adhesive with increased bonding strength, decreased free phenol content and reduced curing temperature.

Mobile messaging groups (MMGs) have been widely adopted in construction practice, yet, little is known about how to foster knowledge sharing (KS) in MMGs, characterized by communication visibility. This study is thus motivated to investigate mechanisms for KS in this context.

The paper employs knowledge governance theory to construct a theoretical model and develop hypotheses. Specifically, psychological safety is identified as a mediator between knowledge governance mechanism (KGM) and KS, and promotion regulatory focus is identified as a moderator between KGM and psychological safety. Data from 208 Chinese construction project team members are collected to test the proposed theoretical model.

The results suggest that both formal and informal KGM positively affect psychological safety, which in turn improves KS (quantity and quality). Moreover, the mediating role of psychological safety is confirmed, and the moderating role of promotion regulatory focus is validated.

This study explores how to foster KS in MMGs, which are pervasive in today’s digital age. The findings in this study enhance the understanding of KS in digital environments and afford important insights into knowledge management within construction project teams.

Over the past decade, artificial intelligence (AI) technologies have rapidly advanced organizational management, with many organizations adopting AI-based algorithms to enhance employee management efficiency. However, there remains a lack of sufficient empirical research on the specific impacts of these algorithmic management practices on employee behavior, particularly the potential negative effects. To address this gap, this study constructs a model based on the psychological ownership theory, aiming to investigate how algorithmic management affects employees’ knowledge hiding.

This study validates the model through a situational experiment and a multi-wave field study involving full-time employees in organizations implementing algorithmic management. Various analytical methods, including analysis of variance, regression analysis and path analysis, were used to systematically test the hypotheses.

The study reveals that algorithmic management exerts a positive indirect influence on knowledge hiding through the psychological ownership of personal knowledge. This effect is particularly pronounced when employees have lower organizational identification, highlighting the critical role of organizational culture in the effectiveness of technological applications.

This study is among the first empirical investigations to explore the relationship between algorithmic management and employee knowledge hiding from an individual perception perspective. By applying psychological ownership theory, it not only addresses the current theoretical gap regarding the negative effects of algorithmic management but also provides new theoretical and empirical support for the governance and prevention of knowledge hiding within organizations in the context of AI algorithm application. The study highlights the importance of considering employee psychology (i.e. psychological ownership of personal knowledge) and organizational culture (i.e. organizational identification) under algorithmic management. This understanding aids organizations in better managing knowledge risks while maximizing technological advantages and effectively designing organizational change strategies.

The purpose of this paper is to synthesize a polyacrylate-based dispersant with a determined target molecular weight for oily systems and to determine the optimal dispersant level and monomer ratio of the dispersant.

The dispersant was synthesized by conventional radical polymerization using methacrylic acid, butyl acrylate and dimethylamino ethyl methacrylate as the monomer. It was characterized by Fourier transform infrared spectroscopy, nuclear magnetic hydrogen spectroscopy, gel permeation chromatography and thermogravimetric analysis. The dispersant was used to disperse TiO₂, and the performance of the dispersant was evaluated by measuring the viscosity, particle size and dispersive force of the slurry.

The dispersant exhibited high thermal stability and was successfully anchored to the surface of the TiO₂ pigment. When used to disperse a TiO₂ slurry, it effectively made the TiO₂ slurry more fluid, indicating its strong viscosity-reducing properties. The viscosity, particle sizes and dispersion capabilities of the TiO₂ slurry were found to vary depending on the contents and monomer ratios of the dispersant.

P(MAA-BA-DM) dispersant increases the wettability of TiO₂ only in oily solvents but not in aqueous solvents.

P(MAA-BA-DM) dispersant makes it easier to disperse TiO₂ pigments in oily solvents, increasing the amount of pigment in the solvent and making the preparation of highly pigmented pastes easier.

A dispersant containing suitable carboxyl and tertiary amine groups was initially synthesized to disperse TiO₂ in an oily system. The findings are anticipated to be used in the formulation of pigment concentrates, industrial coatings and other solvent-based coatings.

This study mainly focused on the long-term effect of different risk exposure levels and prior anti-epidemic experience of healthcare workers in mitigating COVID-19 on their work stress in the post-COVID era.

The study sample included 359 physicians, 619 nurses, 229 technicians and 212 administrators, for a total of 1,419 healthcare workers working in the Lanzhou area during the investigation. Data were analyzed by multivariate regression models.

Our findings indicated that the interaction between pandemic effect mitigation experience and high-risk exposure significantly affected healthcare workers in the post-COVID era by increasing their work stress (p < 0.001) and reducing their rest time (p < 0.001). Healthcare workers may have experienced worse outcomes in the long term if they had higher levels of risk exposure and more experience in fighting epidemics. Furthermore, poor mental health (p < 0.001) and prior experience with SARS (p < 0.001) further amplified these adverse effects. However, surprisingly, we did not observe any effect of prior anti-epidemic experience or high-risk exposure on the mental health of healthcare workers in the post-COVID era (p > 0.1).

The adverse impact of COVID-19 may have left long-lasting effects on Health professionals (HPs), particularly those with high Risk exposure (RE) and more mitigation experience. Poor Mental health (MH) and previous experience in mitigating previous similar outbreaks (such as SARS) are risk factors that should be considered. Support programs must be designed and promoted to help HPs respond and improve their performance.

Our study presents compelling evidence that the COVID-19 pandemic will have long-term detrimental effects on the work stress of healthcare workers.

Network embeddedness has been widely considered in enterprise innovation as an effective means of overcoming resource dilemmas. However, while focussing on acquiring external innovation resources, the existing research often ignores the vital role of internal routine updates. Therefore, this study explores the mechanism by which network embeddedness affects innovation performance of enterprises from the perspective of organisational routine updating.

This paper proposes a theoretical model based on social network theory and organisational routines–immune response theory. A total of 328 pieces of research data on high-tech enterprises in China were collected, and the hypotheses were verified using hierarchical regression analysis.

The results show that the two forms of network embeddedness – structural embeddedness and relational embeddedness, have a positive effect on enterprise innovation performance and a significant positive effect on organisational routine revision and organisational routine creation. Both organisational routine revision and organisational routine creation positively affect enterprise innovation performance and partially mediate the relationship between network embeddedness and enterprise innovation performance.

This conclusion provides a new perspective on the impact of network embeddedness on enterprise innovation performance and expands the related research on organisational routine updating. This study provides a theoretical reference for high-tech enterprises to improve their competitiveness and innovation performance through network embeddedness and organisational routine updating.

This study examines the existing literature on generative artificial intelligence (Gen AI) and its impact across many sectors. This analysis explores the potential, applications, and challenges of Gen AI in driving innovation and creativity and generating ideas.

The study adopts a comprehensive literature review approach, carefully assessing current scientific articles on Gen AI published from 2022 to 2024. The analysis examines trends and insights derived from research.

The review indicates that Gen AI has significant potential to augment human creativity and innovation processes as a collaborative partner. However, it is imperative to prioritize responsible development and ethical frameworks in order to effectively tackle biases, privacy concerns, and other challenges. Gen AI is significantly transforming business models, processes, and value propositions in several industries, but with varying degrees of effect. Findings indicate also that despite the theory-driven approach to investigating Gen AI's creative and innovative potential, cutting-edge applications research prioritizes examining the possibilities of Gen AI models.

Although this review offers a picture of great possibilities, it concurrently underlines the necessity for a deep knowledge of Gen AI nuances to fully harness its capabilities. The findings indicate that continuous research and exploration efforts are required to address the challenges of Gen AI and assure its responsible and ethical implementation. Therefore, more study is needed on enhancing human-AI collaboration and defining ethical norms for varied circumstances.

This study presents a relevant analysis of Gen AI's transformational potential as an innovation catalyst. It emphasizes major potential, applications across industries, and ethical issues for responsible integration.

Workforce agility (WFA) is an emergent research topic in volatile times. However, there is a lack of research in understanding the leadership dimension that triggers such an attribute in organizations. Our study aims to understand the impact of workforce agility on empowering leadership behavior and employee performance dimensions (task performance, contextual performance and counterproductive work behavior).

We collected data from 236 employees using reliable, validated scales and conducted various statistical analyses.

Our results demonstrated that WFA (1) partially mediated the relationship between empowering leadership and contextual performance (CP), (2) has not mediated the relationship between empowering leadership and counterproductive behavior (CWB) and (3) mediated the relationship between empowering leadership and task performance (TP).

Our research has practical implications for management practitioners. It suggests hiring and developing an agile workforce through appropriate training and development programs can significantly impact organizational performance. Furthermore, it provides insights into building leadership capabilities that sustain workforce agility practices, empowering leaders to make informed decisions.

Our research fills a significant gap in the existing literature by exploring the effects of WFA on leadership and performance. This novel approach provides a fresh perspective on the dynamics of organizational behavior, making it a valuable addition to the field.

The purpose of this study is to investigate the relationship between digital transformational leadership (DTL) and innovation capability (IIC) in multinational (MNC) firms’ settings. The current study emphasises the mediating-moderating impact of symmetrical internal communication (SIC) and trust in leadership (TIL) in further shaping this relationship.

The researchers adopted three-wave data consisting of responses from 323 cross-border team members working in MNC firms. A moderated-mediation model was tested using Hynes’ Process Macro and IBM Amos.

The empirical findings underscore a positive relationship between DTL and IIC and the mediation by SIC. Furthermore, the researchers also identified a moderated mediation relationship of TIL.

To the best of the authors’ knowledge, this is the first study to investigate the moderated mediation relationship among DTL, SIC, IIC and TIL using the complexity leadership theory perspective.