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This study is dedicated to systematically collating the distribution and utilization circumstances of geothermal resources in China. Moreover, it endeavors to formulate a comprehensive utilization scheme for geothermal resources during the construction and operation phases of the railway, thereby furnishing robust support and valuable reference for the holistic utilization of geothermal resources along the railway corridor.

Through an in-depth analysis of the extant utilization of geothermal resources in China, it is discerned that the current utilization modalities are relatively rudimentary, bereft of rational planning and characterized by a low utilization rate. Concurrently, by integrating the practical requisites of railway construction and operation and conducting theoretical dissections, a comprehensive utilization plan for the construction and operation periods of railway is proffered.

In light of the railway’s construction and operation characteristics, geothermal utilization models are categorized. During construction, comprehensive modalities include tunnel illumination power generation, construction area heating, tunnel antifreeze using shallow geothermal energy, tunnel pavement antifreeze and construction concrete maintenance. During operation, they comprise operation tunnel antifreeze, railway roadbed antifreeze, railway switch snow melting and deicing, geothermal power station establishment and railway hot spring health tourism planning.

According to the characteristics and actual needs of railway construction and operation, it is of great significance to rationally utilize geothermal resources to promote the construction and operation of green railways.

Online customer reviews is an important information resource for product innovation. This study aims to investigate the impact of online customer reviews on iterative innovation of software products and the moderating roles of product complexity in the process of online reviews influencing product iterative innovation.

To empirically test the hypotheses, this paper built a panel data of 500 software products from 2019 to 2021 and applied Poisson regression analysis.

Empirically results reveal that both sentiment and quantity of online customer reviews have positive effects on iteration innovation of software products. In addition, the authors find that product complexity negatively moderates the relationship between online reviews and iterative innovation.

This study suggests that firms can acquire valuable information from customers’ online reviews for product iterative innovation and improvement. However, for high-complexity products, it may be difficult for enterprises to obtain useful information for iterative innovation from online reviews. On the other hand, this study provides a reference for firms to choose more useful online reviews from the perspective of sentiment.

This paper provides a new finding that there is a positive relationship between online customer reviews and iterative innovation of software products. Moreover, the authors also provide a deeper understanding of how online customer reviews affects iterative innovation by examining the moderating roles of product complexity.

Three-dimensional (3D) food printers are revolutionizing food production with personalized, sustainable and efficient meal creation. This study aims to explore the factors driving consumer intentions to purchase three-dimensional (3D) food printers. These innovative devices are gaining popularity for their ability to produce intricate, customizable food designs with remarkable precision and convenience. By leveraging the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, the research examines key variables such as performance expectancy, effort expectancy, social influence, facilitating conditions (FCD), hedonic motivation and perceived product value. The aim is to understand how these factors shape consumer behavior and decision-making, providing insights into the adoption dynamics of 3D food printers for professional and domestic use.

This study collected 973 valid responses through an online survey. The data were analyzed using partial least squares structural equation modeling.

Performance expectancy, social influence and perceived product value significantly enhance consumers’ intention to purchase 3D food printers. In contrast, effort expectancy, FCD and hedonic motivation show no statistically significant impact on their usage intention.

Companies in the 3D food printing industry should prioritize improving product performance and leveraging social influencers to spark consumer interest. Educating the public about the benefits of 3D food printing is essential for building market acceptance and demand. Governments should contemplate implementing policies and regulations encouraging companies to invest in research and development in this field. This study acknowledges its limitations and recommends directions for future research.

This study establishes its originality by integrating hedonic motivation and perceived product value with the original UTAUT framework to investigate Chinese households’ intentions to use a 3D food printer.

Implementing big data analytics (BDA) for supply chain ambidexterity (agility and adaptability) and green supply chain (GRSC) presents various organizational challenges. These include leveraging BDA capabilities to balance agility and adaptability, integrating this combined approach with GRSC and aligning these efforts to enhance firm performance. This study explores the associations between BDA, supply chain agility and adaptability, GRSC and their impact on firm performance.

Incorporating a resource-based view and contingency theory, we developed a research framework and validated it with data from 355 Chinese firms. Partial least squares structural equation modeling was used to analyze the data.

The findings demonstrate that BDA capabilities had direct impact on supply chain agility and adaptability, GRSC and firm performance. Moreover, the combination of supply chain agility and adaptability affected GRSC; which in turn significantly influenced firm performance. Supply chain agility and adaptability mediated the relationship between BDA capabilities and GRSC. Additionally, GRSC mediated the relationship between BDA capabilities, supply chain agility and adaptability and firm performance.

This study offers both a theoretical and empirical examination of the relationships between BDA capabilities, supply chain agility and adaptability, GRSC and firm performance. By assessing the direct and mediating effects of these factors on China’s industrial sector, it presents new theoretical and practical insights into BDA and GRSC, thereby enhancing the value of the existing literature.

In the realm of open innovation (OI) networks, coopetition—where competition and cooperation coexist—plays a pivotal role in shaping the dynamics between diverse projects. This dual relationship is crucial for the propagation of knowledge and the bolstering of the network's overall resilience. While competition drives the quality of products and services, thereby reinforcing network resilience, cooperation facilitates knowledge diffusion, which is essential for the network's robustness.

We delve into the interplay between coopetition intensity and network resilience through the lens of knowledge diffusion. Our methodology begins with a sensitivity analysis to gauge the direct effects of coopetition on resilience. This is followed by a principal component analysis to identify the key determinants of coopetition intensity among projects. Finally, we utilize linear regression and moderation analysis to explore the mediating role of knowledge diffusion in the resilience of OI networks.

Our work is grounded in network theory, which provides a robust theoretical framework for understanding project coopetition and knowledge diffusion within the OI paradigm. This research not only offers a nuanced understanding of coopetition's impact on OI network resilience but also highlights the significance of knowledge diffusion as a critical mediating variable.

1) Identifies the significant influences in project coopetition (competition and cooperation). (2) Puts the conceptual framework and calculation method of the open innovation network resilience based on the project coopetition and knowledge diffusion. (3) Explores the moderating role of knowledge diffusion in project coopetition influencing open innovation networks resilience. (4) Measures the influence of project coopetition relationship on open innovation network resilience from the perspective of knowledge diffusion. (5) Encourages project management to consider the portfolios of coopetition.

To maximize health synergistic benefits and provide a scientific foundation for enhancing air pollution control policies, this research proposed a causal inference framework with a decomposition ensemble prediction model for comprehensive policy assessment.

We introduced the CD-OASVR-Ensemble-CC method, a policy assessment approach that combined machine learning-based decomposition ensemble prediction (CD-OASVR-Ensemble) with counterfactual contrast (CC) analysis. The CD-OASVR-Ensemble model incorporated support vector regression (SVR) optimized through swarm intelligent optimization algorithms (OA), complete ensemble empirical model decomposition of adaptive noise (CD) and a linear ensemble model (Ensemble). This approach was applied to analyze patterns in historical PM2.5 data and predict the future trend. The predicted PM2.5 served as a counterfactual trend, enabling an evaluation of the policy’s environmental and health effects.

Analysis of prediction errors confirmed the proposed CD-OASVR-Ensemble model’s accuracy and robustness in predicting PM2.5 levels. The findings indicated that the implementation of “Regulation 2019” led to a significant reduction in PM2.5 concentration, preventing an estimated 7,960 premature deaths and saving approximately 2,602.95 m yuan in health-related economic costs.

This study introduces an innovative framework for evaluating the environmental effect of policies, with a specific emphasis on health synergistic benefits.

The development of an effective corporate vision is a necessary issue for corporate performance, and it is a key issue for corporate sustainable development as well. The recognition of questions like “what is the role of corporate vision in corporate performance” is directly related to the attitude and practice of entrepreneurs and managers toward the development of corporate vision as well as the effectiveness of the corporate vision itself. To better answer the questions concerning the role of corporate vision development and effectively guide the practice of corporations, the authors study the pathways and mechanisms by which corporate visions operate to assist businesses in achieving high performance.

The article completes the construction of indicators to measure each dimension of the corporate vision in line with social cognitive theory and analyzes the relationship between corporate vision and corporate performance by combining qualitative comparative analysis (QCA) and necessary condition analysis (NCA) research methods. The article provides insights into the logic of constructing and adjusting corporate visions from a process perspective.

The mechanisms by which corporate visions can be articulated, accepted and transformed within the organization are also the means by which corporate visions can improve corporate performance. In a dynamic environment, the corporate vision setting and acceptance process integrates the requirements of various stakeholders, leading to the adjustment and acceptance of the corporate vision. As a result, the vision has continuous validity in a changing environment. Both start-ups and non-start-ups can benefit from the guidance provided by a strong corporate vision in overcoming a variety of issues and obstacles to produce strong business performance.

This is the first study that shows the relationship between corporate vision and corporate performance from a process perspective. The authors are interested in understanding which characteristics for building a corporate vision are more accepted by organizational members and, in turn, create high corporate performance. The authors also explore the conditions for corporate vision acceptance. This research has positive implications for shedding some light on the mechanisms by which corporate visions improve corporate performance.

This study illustrates the conceptual framework that expands the knowledge of the fundamental components that describe how AI-driven servant leadership (SEL) influences the job resources (JR), work engagement (WE) and job performance (JP) of tourism and hospitality employees.

The empirical study was conducted on a sample of 953 international tourism and hospitality employees who were selected via a purposive and snowball sampling approach in a cross-sectional survey. The analysis was performed using a partial least square-structural equation modeling.

The results of this study confirmed the positive impact of AI-driven SEL on employee JR with the boundary conditions of AI-driven SEL.

This study finding assists tourism and hospitality practitioners in understanding that in the near future, AI will have a major effect on the nature of work, including the impact on leadership styles. Hence, AI-driven SEL holds both positive (through direct impact on JR) and negative (via boundary conditions) impacts on employees’ JP and ultimately organizational success. Accordingly, managers should employ AI-driven SEL to increase employees’ JR, and once employees achieve high WE, they should constrict AI-driven SEL boundary conditions and their influence between JR and WE and WE and JP.

This study offers a novel and original conceptual model that advances AI-driven social theory, SEL theory and job demands-resources (JD-R) theory by synthesizing, applying and generalizing gained knowledge in a methodical way.

Drawing on the principal-agent theoretical perspective, we assert that sellers’ opportunism is acknowledged as an essential component that could determine the quality of the relationship between buyers (principals) and sellers (agents). The primary aim of this research is to investigate the influence of seller behavior vs outcome-based reputation and seller’s perceived freedom on opportunistic behavior in the Chinese e-commerce platform context.

The data collected from 436 e-commerce platform sellers were analyzed and interpreted using structural equation modeling.

The results indicate that both behavior-based and outcome-based reputations positively impact sellers’ perceived freedom but negatively impact their opportunism. Additionally, while perceived freedom of objectives reduces opportunism, freedom of action increases it. The study also highlights the significant moderating roles of prevention mechanisms and ethical ideology.

This study extends the principal-agent perspective by integrating the seller’s reputation as a potential source of preventing sellers from behaving opportunistically on e-commerce platforms.

China has recently introduced a new audit law that aims to increase the scope of audit supervision and raise the standards for preventing risks in auditing national public projects. This paper presents a systematic research study on the causes of audit risks in national public projects and discusses the process by which these causes contribute to the emergence of such risks. Furthermore, the paper investigates the core risk sources in various types of national construction project audit. This paper aims to provide theoretical support for auditors of national construction projects in risk avoidance when conducting audits.

In this study, the authors carefully selected five national public audit projects from China and performed a comprehensive analysis of 85 relevant audit documentation. The textual analysis was conducted using Nvivo12 software, and the grounded theory approach was adopted for generalization purposes.

Based on the research results, the findings suggest that there are five key causes contributing to the audit risk of national construction projects: professional competence, risk awareness, management capacity, level of attention and deliberate fraud. The most critical factor identified is management capability, with 59.93% of the data supporting this view. This conclusion was based on an analysis of state-owned enterprises, administrative organs and public institutions. Building upon this, a framework titled “the mechanism of audit risk factors with management capability as the core” was constructed.

This paper employs qualitative analysis methods to examine national construction projects in China, contributing new literature to the theoretical study of audit risk management. The article also provides practical recommendations for auditors on how to mitigate audit risks and improve the quality of audit services in national project governance.