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This study aims to explore the factors influencing the evolution of emerging technology innovation network (ETIN) in combination with the key attributes and life cycle of emerging technologies, particularly the impact of multiple knowledge attributes and technology life cycle on the ETIN evolution.

This study collects 5G patent data and their citation information from the Derwent Innovations Index to construct a 5G technology innovation network (5GIN) as a sample network and conducts an empirical analysis of the 5GIN using the temporal exponential random graph model (TERGM).

The results indicate that during the 5GIN evolution, the network scale continues to expand and exhibits increasingly significant core-periphery structure, scale-free characteristic, small-world characteristic and community structure. Furthermore, the findings suggest that the multiple knowledge attributes based on the key attributes of emerging technologies, including knowledge novelty, coherence, growth and impact, have a significant positive influence on the ETIN evolution. Meanwhile, the temporal evolution of ETIN is also found to be correlated with the life cycle of emerging technologies.

This study extends the exploration of emerging technology research from a complex network perspective, providing a more realistic explanatory framework for the factors influencing ETIN evolution. It further highlights the important role that multiple knowledge attributes and the technology life cycle play within this framework.

Existing research on stock price manipulation driven by equity incentives has mainly focused on earnings management, without considering other potential manipulation methods. Therefore, we examine whether management engages in tone management during earnings communication conference following equity incentives.

Using Chinese A-share listed companies from 2006 to June 2023 as the sample, we explore the impact mechanism of equity incentives on the tone of earnings communication conference.

Equity incentives are found to increase abnormal tone in earnings communication conferences. The characteristics of equity incentives themselves affect tone management. For instance, equity incentives based on stock options, as well as those within the exercise feasibility year, have a more pronounced effect on facilitating tone management. The mechanisms through which equity incentives affect different tones vary: the increase in positive tone is associated with improved financial performance, while the increase in abnormal tone is linked to executives reducing their holdings to obtain cash. Further discussions reveal that the impact of equity incentives on abnormal tone is weaker when there is a higher degree of real or accrual-based earnings management, suggesting a possible substitution relationship between earnings management and abnormal tone. Additionally, when a company experiences low investment efficiency, high executive compensation and a lower proportion of negative news coverage in the external information environment, the impact of equity incentives on abnormal tone becomes more pronounced.

Our study primarily focuses on conducting exploratory research into the mechanism, purpose, timing and alternative selection of tone management in the year following the grant of equity incentives. We have not provided a detailed theoretical explanation regarding the transmission channels or mechanisms through which tone management affects investor sentiment and trading behavior.

We provide valuable insights for identifying the quality of information disclosure in earnings communication conference.

We clarify the mechanism of equity incentives on management’s tone, reveals the timing preferences of tone management during the earnings communication conference.

Audit firms have a strong historical tradition of professionalism, but they are also commercial entities. This study aims to investigate the relationship between auditor cash compensation and office-level financial performance.

This study uses proprietary compensation expense and financial performance data from audit offices in China. Using the ordinary least squares regressions, this study tests the association between per capita compensation and office-level financial outcomes.

This study provides evidence that audit offices offering higher compensation achieve more profitable performance, as reflected in increased market share, higher return on assets and greater operating profit margins. Mechanism tests suggest that reductions in auditor turnover, driven by compensation incentives, partially account for this performance improvement. Additional tests show that the benefits of compensation incentives are particularly pronounced in audit firms licensed to conduct listed firm audits or when accompanied by staff training and technical development. Furthermore, both partner-level and staff auditor compensation significantly enhance office-level financial performance. The results might be of interest to both practitioners and regulatory bodies.

To the best of the authors’ knowledge, this study is the first to examine the relationship between auditor cash compensation and audit-office profitability. The findings highlight important policy implications for audit firms seeking to retain high-caliber auditors and maximize their economic benefits through human capital investments, including compensation, education, training and technical development.

This systematic review aimed to evaluate the effectiveness of using immersive virtual reality as an innovative and novel technology for managing depression, anxiety and psychological distress among patients with cancer.

The relevant literature was searched and extracted using the following online bibliographic databases: Cumulative Index to Nursing and Allied Health Literature (CINAHL), ProQuest, MEDLINE, Google Scholar, SAGE Journals and Science Direct, in addition, reference lists for all included studies were thoroughly examined to find relevant articles. This systematic review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards. Several online databases were used to find eligible studies in peer-reviewed journals relevant to the study keywords. The included studies were systematic reviews and clinical trials that used immersive virtual reality–based intervention among patients with cancer and suffering from cancer-related fatigue, older than 18 years and were published in the English language from 2015 to 2024. Two researchers independently contributed to study selections, data extraction and evaluation from different aspects: quality assessment, risk of bias and study synthesis.

A total of 13 published studies were included in this review study: 7 articles were quantitative clinical trial studies and the other 6 were systematic review and meta-analysis studies. The quality of 7 included clinical trials was assessed using the Effective Public Health Practice Project (EPHPP) Quality Assessment Tool for quantitative studies, the overall result showed that 28.6% of studies rated with moderate quality, no study was rated with low quality and (71.4%) studies rated as high-quality study. As well as the quality assessment of all review studies showed that the majority of included systematic reviews and meta-analyses with a low risk of bias and high to moderate power of evidence. The result of this extensive and comprehensive review showed that immersive virtual reality has a significant positive impact on reducing depression, anxiety and psychological distress among patients with different types of cancer.

The findings of this systematic review provide compelling evidence for the transformative potential of immersive virtual reality as a therapeutic intervention for managing depression, anxiety and psychological distress in cancer patients. By synthesizing data from 13 rigorous studies, this review not only underscores the efficacy of this innovative technology but also highlights its role as a novel approach in the psychosocial care of individuals facing the challenges of cancer. This research opens new avenues for integrating immersive virtual reality into clinical practice, paving the way for future investigations that could further elucidate its mechanisms of action and optimize its application in oncology settings.

This study aims to examine the combinations of internal and external knowledge flows between research and development (R&D) incumbents and start-ups in the context of open innovation. While there is a growing body of knowledge that has examined how, in a knowledge economy, a firm’s knowledge and innovation activities are closely linked, there is no systematic review available of the key antecedents, perspectives, phenomenon and outcomes of knowledge spillovers.

The authors have conducted dual-stage research. First, the authors conducted a systematic review of literature (97 research articles) by following the theories–contexts–methods framework and the antecedent-phenomenon-outcomes logic. The authors identified the key theories, contexts, methods, antecedents, phenomenon and outcomes of knowledge spillovers between R&D-driven incumbents and start-ups in the open innovation context. In the second stage, the findings of stage one were leveraged to advance a nomological network that depicts the strength of the relationship between the observable constructs that emerged from the review.

The findings demonstrate how knowledge spillovers can help incumbent organisations and start-ups to achieve improved innovation capabilities, R&D capacity, competitive advantage and the creation of knowledge ecosystems leading to improved firm performance. This study has important implications for practitioners and managers – it provides managers with important antecedents of knowledge spillover (knowledge capacities and knowledge types), which directly impact the R&D intensity and digitalisation driving open innovation. The emerging network showed that the antecedents of knowledge spillovers have a direct relationship with the creation of a knowledge ecosystem orchestrated by incumbents and that there is a very strong influence of knowledge capacities and knowledge types on the selection of external knowledge partners/sources.

This study has important implications for practitioners and managers. In particular, it provides managers with important antecedents of knowledge spillover (knowledge capacities and knowledge types), which directly impact the R&D intensity and digitalisation driving open innovation. This will enable managers to take important decisions about what knowledge capacities are required to achieve innovation outcomes. The findings suggest that managers of incumbent firms should be cautious when deciding to invest in knowledge sourcing from external partners. This choice may be driven by the absorptive capacity of the incumbent firm, market competition, protection of intellectual property and public policy supporting innovation and entrepreneurship.

Identification of the key antecedents, phenomenon and outcomes of knowledge spillovers between R&D-driven incumbents and start-ups in the open innovation context. The findings from Stage 1 helped us to advance a nomological network in Stage 2, which identifies the strength and influence of the various observable constructs (identified from the review) on each other. No prior study, to the best of the authors’ knowledge, has advanced a nomological network in the context of knowledge spillovers between R&D-driven incumbents and start-ups in the open innovation context.

Focusing on the resource crowding-out effect, this study aims to examine the relationship between an enterprise’s digital transformation and the internalisation of environmental costs.

This paper manually collects environmental cost data and measures corporate digital transformation constructed through a machine learning word vector (Word2Vec) technology approach based on the text information of annual reports (MD&A) for heavily polluting firms.

Corporate digital transformation has a significant inhibitory effect on the internalisation of corporate environmental costs. This is because low-level digital transformation has crowded out cash flows, preventing China’s heavily polluting firms from having the extra capacity needed to internalise environmental costs. This crowding-out effect emerges when companies face problems such as capital shortages, short-term profit pressure and intense market competition. These results have the following important implications.

The research highlights the need for enterprises to align digital transformation and sustainability strategies by strengthening resource endowment and optimising internal resource allocation. This requires effective use of digital technology and a long-term sustainability vision for heavily polluting firms facing environmental policy pressures.

Enterprises should assume more social responsibility and achieve sustainable socioeconomic development. It will also help mitigate the adverse environmental externalities stemming from their operations.

To the best of the authors’ knowledge, this study considers the impact of enterprise digital transformation on the internalisation level of enterprise environmental costs for the first time and uses enterprises’ financial, management, market characteristics and ownership characteristics to analyse the impact mechanism.

Damage of engineering structures is a nonlinear evolutionary process that spans across both material and structural levels, from mesoscale to macroscale. This paper aims to provide a comprehensive review of damage analysis methods at both the material and structural levels.

This study provides an overview of multiscale damage analysis of engineering structures, including its definition and significance. Current status of damage analysis at both material and structural levels is investigated, by reviewing damage models and prediction methods from single-scale to multiscale perspectives. The discussion of prediction methods includes both model-based simulation approaches and data-driven techniques, emphasizing their roles and applications. Finally, summarize the main findings and discuss potential future research directions in this field.

In the material level, damage research primarily focuses on the degradation of material properties at the macroscale using continuum damage mechanics (CDM). In contrast, at the mesoscale, damage research involves analyzing material behavior in the meso-structural domain, focusing on defects like microcracks and void growth. In structural-level damage analysis, the macroscale is typically divided into component and structural scales. The component scale examines damage progression in individual structural elements, such as beams and columns, often using detailed finite element or mesoscale models. The structural scale evaluates the global behavior of the entire structure, typically using simplified models like beam or shell elements.

To achieve realistic simulations, it is essential to include as many mesoscale details as possible. However, this results in significant computational demands. To balance accuracy and efficiency, multiscale methods are employed. These methods are categorized into hierarchical approaches, where different scales are processed sequentially, and concurrent approaches, where multiple scales are solved simultaneously to capture complex interactions across scales.

This study aims to provide a comprehensive overview of thin-film temperature sensors (TTS), focusing on the interplay between material properties and fabrication techniques. It evaluates the current state of the art, addressing both low- and high-temperature sensors, and explores the potential applications across various fields. The study also identifies challenges and highlights emerging trends that may shape the future of this technology.

This study systematically examines existing literature on TTS, categorizing the materials and fabrication methods used. The study compares the performance metrics of different materials, addresses the challenges encountered in thin-film sensors and reviews the case studies to identify successful applications. Emerging trends and future directions are also analyzed.

This study finds that TTS are integral to various advanced technologies, particularly in high-performance and specialized applications. However, their development is constrained by challenges such as limited operational range, material degradation, fabrication complexities and long-term stability. The integration of nanostructured materials and the advancement of wireless, self-powered and multifunctional sensors are poised to drive significant advancements in this field.

This study offers a unique perspective by bridging the gap between material science and application engineering in TTS. By critically analyzing both established and emerging technologies, the study provides valuable insights into the current state of the field and proposes pathways for future innovation in terms of interdisciplinary approaches. The focus on emerging trends and multifunctional applications sets this review apart from existing literature.

This research is aimed to examine how environmental pollution affects consumers' preference for self-improvement products.

Through a series of three experimental studies, this research substantiates our hypotheses by employing various manipulations of environmental pollution and examining different types of self-improvement products.

The research demonstrates that environmental pollution enhances consumers' preference for self-improvement products via the mediation of perceived environmental responsibility. And the effect is negatively moderated by social equity sensitivity.

The recurrent incidence of environmental pollution has elicited significant concern among the general public and academic scholars. An overwhelming majority of research examining the impact of pollution on consumer behavior has concentrated on its influence on environmentally friendly and healthy consumption patterns. Nevertheless, the current research proposes that pollution fosters a preference for products associated with self-improvement, mediated by perceived environmental responsibility, with the effects being moderated by social equity sensitivity.

This study aims to examine the determinants that influence housing prices in Dammam metropolitan area (DMA), Saudi Arabia, by using the analytic hierarchy process (AHP) model. The study considers determinants such as building age (BLD AG), building size (BLD SZ), building condition (BLD CN), access to parking (ACC PK), proximity to transport infrastructure (PRX TRS), proximity to green areas (PRX GA) and proximity to amenities (PRX AM).

The AHP decision model was used to assess the determinants of housing prices in DMA, using a pair-wise comparison matrix to determine the influence of the investigated factors on housing prices.

The study’s results revealed that building size (BLD SZ) was the most critical determinant affecting housing prices in DMA, with a weight of 0.32, trailed by proximity to transport infrastructure (PRX TRS), with a weight of 0.24 as the second most influential housing price determinant in DMA. The third most important determinant was proximity to amenities (PRX AM), with a weight of 0.18.

This study addresses a research gap by using the AHP model to assess the spatial determinants of housing prices in DMA, Saudi Arabia. Few studies have used this model in examining housing price factors, particularly in the context of Saudi Arabia. Consequently, the findings of this study provide unique insights for policymakers, housing developers and other stakeholders in understanding the importance of building size, proximity to transport infrastructure and proximity to amenities in influencing housing prices in DMA. By considering these determinants, stakeholders can make informed decisions to improve housing quality and prices in the region.