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Megaprojects provide an ideal context for exploring the dynamic characteristics of stakeholders within a collaborative innovation system. This research aims to examine the changes in stakeholder salience and functional roles during the evolution of such a system.

This study is empirically grounded on the Hong Kong-Zhuhai-Macao Bridge (HZMB) megaproject in China, analyzed with the stakeholder salience, stakeholder functional role, stakeholder dynamics and collaborative innovation system theoretical lens.

The megaproject collaborative innovation system can be divided into four stages: the birth stage, development stage, mature stage and re-innovation stage. Stakeholder salience generally remains unchanged throughout the lifecycle of the collaborative innovation system, except for engineering consulting firms (ECF). ECF transitioned from a definitive stakeholder to an expectant stakeholder upon project completion. The number of definitive stakeholders during the first three stages increases gradually. Besides, stakeholder functional roles shift in eight different directions throughout the lifecycle of the megaproject collaborative innovation system because they possess different core resources necessary for implementing innovations and are positioned differently within the collaborative innovation system.

This study contributes to the theory and practice of collaborative innovation in megaprojects. First, it offers insights into the evolution of megaproject collaborative innovation systems from the perspective of stakeholder interactions. Second, it has significant implications for managing stakeholder relationships based on their salience and functional roles at different stages of the collaborative innovation system.

Green innovation (GI) in megaprojects has become a significant research topic that attracts both megaproject management scholars' and practitioners' attention. Green transformational leadership (GTL) is acknowledged as an important antecedent to GI in the permanent context. However, limited research investigates the mechanism and condition of how GTL effectively affects GI in the temporary (i.e. megaproject) context. This study seeks to examine the mechanism and condition of GTL in improving GI by assessing the mediating role of green knowledge sharing (GKS) and the moderating effect of innovation climate (IC).

Regression analysis was performed on data obtained from 303 experts who have been involved in megaprojects.

GTL has a significant positive impact on two aspects of GI, including green product innovation (GPDI) and green process innovation (GPCI). Besides, GKS mediates the relationship between GTL and the two aspects of GI. Moreover, IC plays a significantly positive moderating role in the relationship between GTL and GKS and the relationship between GKS and the two aspects of GI.

This study adds knowledge to the theory and practice by unveiling the “black box” between GTL and GI in the temporary (i.e. megaproject) context. First, this study extends the continuing discussion on the direct effect of GTL on GI to the temporary (i.e. megaproject) context. Second, this study facilitates the understanding of the mechanism to generate better GI performance considering the mediating role of GKS and the moderating effect of IC in the temporary (i.e. megaproject) context. The results can illuminate megaproject practitioners on generating better GI performance.

With the rapid development of the pipeline transportation and exploitation of mineral resources, it is urgent requirement for the high-performance polymer matrix composites with low friction and wear to meet the needs of solid material transportation. This paper aims to prepare high-performance ultrahigh molecular weight polyethylene (UHMWPE) matrix composites and investigate the effect of service condition on frictional behavior for composite.

In this study, UHMWPE matrix composites with different content of MoS₂ were prepared and the tribological performance of the GCr15/composites friction pair in various sliding speeds (0.025–0.125 m/s) under dry friction conditions were studied by ball-on-disk tribology experiments.

Results show that the frictional behavior was shown to be sensitive to MoS2 concentration and sliding velocity. As the MoS2 content is 2 Wt.%, composites presented the best overall tribological performance. Besides, the friction coefficient fluctuates around 0.21 from 0.025 to 0.125 m/s sliding speed, while the wear rate increases gradually. Scanning electron microscopy images, energy-dispersive spectroscopy and Raman Spectrum analysis present that the main wear mechanisms were abrasive and fatigue wear.

The knowledge obtained herein will facilitate the design of UHMWPE matrix composites with promising self-lubrication performances which used in slag transport engineering field.

This study aims to analyze government hotline text data and generating forecasts could enable the effective detection of public demands and help government departments explore, mitigate and resolve social problems.

In this study, social problems were determined and analyzed by using the time attributes of government hotline data. Social public events with periodicity were quantitatively analyzed via the Prophet model. The Prophet model is decided after running a comparison study with other widely applied time series models. The validation of modeling and forecast was conducted for social events such as travel and educational services, human resources and public health.

The results show that the Prophet algorithm could generate relatively the best performance. Besides, the four types of social events showed obvious trends with periodicities and holidays and have strong interpretable results.

The research could help government departments pay attention to time dependency and periodicity features of the hotline data and be aware of early warnings of social events following periodicity and holidays, enabling them to rationally allocate resources to handle upcoming social events and problems and better promoting the role of the big data structure of government hotline data sets in urban governance innovations.

This study aims to provide a new perspective and path to reduce the unsafe behavior of new generation of construction workers (NGCWs) in China. The purpose of this study is to explore the influencing mechanism of work-family balance on the unsafe behavior of NGCWs and test the mediating effect of job satisfaction and the moderating effect of group safety climate.

A theoretical model on the influencing mechanism of work-family balance on unsafe behavior of NGCWs was constructed through theoretical analysis. Research data were collected from 502 NGCWs via a questionnaire survey, and research hypotheses were testified with regression analysis.

The results show that work-family balance not only directly reduces NGCWs’ unsafe behavior but also indirectly reduces it through job satisfaction, which plays a partial mediating role. In addition to positively moderating the relationship between work-family balance and NGCWs’ unsafe behavior, group safety climate can also moderate the relationship between work-family balance and job satisfaction in a positive way.

This study provides practical implications for construction companies to reduce the unsafe behaviors of NGCWs from the perspective of work-family balance. Specifically, construction companies should adopt more flexible work rules, such as flexible organization and rotation systems, to increase their work autonomy. Meanwhile, construction companies need to improve the work environment and basic conditions for NGCWs, establish a reasonable salary system and provide attractive promotion opportunities to increase their job satisfaction. In addition, construction companies should provide active safety lectures and training, and supervisors should improve safety communication and interaction levels. Co-workers should remind workers about their safety attitudes and behaviors promptly. A good group safety climate will be created through the efforts of construction companies, supervisors and co-workers.

This study clarifies the influencing mechanism of work-family balance on the NGCWs’ unsafe behavior and further tests the partial mediating role of job satisfaction and the positively moderating effect of group safety climate on the influence relationship of work-family balance on job satisfaction and NGCWs’ unsafe behavior, which defines the boundary conditions of the relationship between work-family balance and NGCWs’ unsafe behavior, and promotes the effective integration of social exchange theory and theoretical system of influencing mechanism of construction workers’ unsafe behavior.

The purpose of this study is to provide a holistic understanding of the factors that either promote or hinder the adoption of artificial intelligence (AI) in supply chain management (SCM) and operations management (OM). By segmenting the AI lifecycle and examining the interactions between critical success factors and critical failure factors, this study aims to offer predictive insights that can help in proactively managing these factors, ultimately reducing the risk of failure, and facilitating a smoother transition into AI-enabled SCM and OM.

This study develops a knowledge graph model of the AI lifecycle, divided into pre-development, deployment and post-development stages. The methodology combines a comprehensive literature review for ontology extraction and expert surveys to establish relationships among ontologies. Using exploratory factor analysis, composite reliability and average variance extracted ensures the validity of constructed dimensions. Pearson correlation analysis is applied to quantify the strength and significance of relationships between entities, providing metrics for labeling the edges in the resource description framework.

This study identifies 11 dimensions critical for AI integration in SCM and OM: (1) setting clear goals and standards; (2) ensuring accountable AI with leadership-driven strategies; (3) activating leadership to bridge expertise gaps; (4) gaining a competitive edge through expert partnerships and advanced IT infrastructure; (5) improving data quality through customer demand; (6) overcoming AI resistance via awareness of benefits; (7) linking domain knowledge to infrastructure robustness; (8) enhancing stakeholder engagement through effective communication; (9) strengthening AI robustness and change management via training and governance; (10) using key performance indicators-driven reviews for AI performance management; (11) ensuring AI accountability and copyright integrity through governance.

This study enhances decision-making by developing a knowledge graph model that segments the AI lifecycle into pre-development, deployment and post-development stages, introducing a novel approach in SCM and OM research. By incorporating a predictive element that uses knowledge graphs to anticipate outcomes from interactions between ontologies. These insights assist practitioners in making informed decisions about AI use, improving the overall quality of decisions in managing AI integration and ensuring a smoother transition into AI-enabled SCM and OM.

This study investigates the factors influencing the saving behaviour of Chinese Generation Z (Gen Z) through Internet wealth management (IWM) services. It adopts the unified theory of acceptance and use of technology (UTAUT) as the theoretical framework, focusing on key determinants such as performance expectancy (PE), effort expectancy (EE), social influence (SI) and facilitating conditions (FC). The research also explores the mediating role of the intention to save via IWM and its subsequent influence on actual saving behaviour.

The hypotheses were assessed using data collected from 274 Gen Z users in China. The data were analysed using the partial least squares structural equation modelling.

The results suggest that the formation of intention among Gen Z to save through IWM services is directly affected by factors such as PE, EE, SI and FC. Intention to save via IWM positively influences actual saving behaviour. Mediation analysis further confirms the mediating role of intention to save via IWM in these relationships.

The findings have direct implications for financial institutions and policymakers engaged in promoting the practice of saving via IWM services among Gen Z, thereby fostering a culture of proactive financial management and encouraging saving behaviour.

The study contributes to the existing literature by being among the first to examine Gen Z’s IWM adoption as a personal saving tool through the theoretical lens of the UTAUT.

In China, it is prevalent for parents to share health information on WeChat and receive feedback from their children. This study aims to investigate the feedback from younger generations regarding their parents’ health information sharing. It will examine the different types of feedback, explore the factors influencing it and analyze the outcomes that result from this feedback exchange.

The empirical findings draw on the qualitative analysis using grounded theory. This study collects data from 34 participants (17 pairs of one young person and one parent) through in-depth interviews and WeChat chat records. Then, a theoretical model was developed through open, axial and selective coding.

Feedback can be classified into five types: support, correction, perfunctoriness, ostracism and rejection as well as into “Affective-Behavioral-Cognitive” dimensions. Younger generations’ feedback types are influenced by a variety of factors, including information, emotion and individual and family-related factors. Each feedback type has distinct effects, such as altering older generations’ emotional and communication responses.

This pioneering study explores how younger generations in China perceive their parents’ health information sharing on social media. It highlights the importance of feedback in this context, providing actionable insights to enhance digital literacy among older adults, strengthen family bonds and enhance the spread of valuable and scientific health information online.

Taking attribution theory as an overarching framework, the study aims to examine how employees attribute and respond to a colleague's approach crafting.

Two complementary studies, including a scenario experiment (Study 1; N = 114) and an online survey (Study 2; N = 220), were conducted to test the hypothesized model.

Study 1 found support for the attribution of a prosocial motive to approach crafting, which in turn led to more social support and less social undermining among observers. This mediation was stronger when the job crafter was perceived as less other-oriented. Study 2 replicated the findings of Study 1 and further showed that when observers attributed both high impression management and prosocial motives to approach crafting, the positive relationship between their prosocial motive attribution and social support for the job crafter got weakened, while the negative relationship between their prosocial motive attribution and social undermining of the job crafter was strengthened.

The findings demonstrate that approach crafting gives rise to specific attributions and reactions toward the job crafter, which enrich the understanding of the social consequences of job crafting in the workplace.

Financial technology (FinTech) has enhanced the inclusivity and accessibility of traditional finance, offering a novel pathway for rural revitalization and development. The paper aims to assess the rural revitalization development level in prefecture-level cities in China and investigate the potential impact mechanism of FinTech.

This paper develops an index system to evaluate the rural revitalization level across 279 cities in China from 2011 to 2021. In addition, multi-mediation and threshold models are employed to analyze how FinTech influences rural revitalization.

The results reveal that, first, FinTech has significantly promoted rural revitalization. Second, entrepreneurial activeness, innovation capability, and industrial structure advancement are intermediary factors within the benchmark path. Third, FinTech exhibits varied threshold effects in entrepreneurial activeness, innovation capability, and industrial structure advancement, influencing rural revitalization with diverse impacts.

First, this paper expands the rural revitalization evaluation to include 30 indexes, enhancing overall measurement comprehensiveness. Second, in contrast to previous research concentrating on provincial-level assessments, this paper explores rural revitalization across 279 cities in China from 2011 to 2021, broadening the study’s scope and timeline. Third, this paper delves into empirical evidence illustrating how FinTech contributes to rural revitalization through entrepreneurial activeness, urban innovation capability, and industrial structure advancement, thereby deepening research in this domain.