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The development and evolution of stakeholder collaborative innovation in megaprojects is impacted by various influencing factors. The effect of influencing factors on collaborative innovation performance (CIP) in megaprojects is not a simplistic linear relationship but an iterative and non-linear relationship that requires a dynamic perspective to analyze. Therefore, this paper adopts the system dynamic (SD) approach to investigate the dynamic and interactive relationships between the CIP and the influencing factors.

The study first develops a research framework with the system boundary of “CIP system – organizational collaboration subsystem – knowledge collaboration subsystem – strategic collaboration subsystem”. Then, the causal relationship model, the stock-flow model, and the mathematical equations were determined based on the literature review and the expert interviews. Finally, five performance improvement scenarios were designed according to the practice context of CIP in megaprojects, and simulations were performed using the Vensim PLE software to investigate the CIP from a dynamic perspective.

The findings reveal that the effect of different influencing factors on CIP grows non-linearly, with the cumulative effect becoming more pronounced as time advances. The incentive mechanism has the most significant effect, and the combined effect of multiple influencing factors has a highly significant facilitating effect on improving CIP. Strategic collaboration, organizational collaboration and knowledge collaboration are mutually conditional and reinforcing with each other, which ultimately promotes the improvement of CIP.

This study uncovers the inherent pattern and the interactive dynamic mechanism of factors for improving CIP in the context of megaprojects. It enriches the theoretical research in the area of collaborative innovation in megaprojects and provides practical management strategies for improving CIP.

This study aims to examine how young consumers perceive the advertising effectiveness of endorsements by virtual idols and how endorsements by virtual idols differ from endorsements by real human celebrities such as traditional celebrities and online influencers.

An experimental study was conducted with 400 randomly selected young respondents in China in December 2022. A 3 × 2 factorial design was used to test how the type of celebrity endorser and level of product involvement influence the persuasiveness of advertising aimed at young adults. Among 400 respondents, the average age was 21.5 years. A total of 193 male and 207 female respondents participated in the experiment.

Young consumers find virtual idols, online influencers and traditional celebrities attractive. Although virtual idols are the least credible among the three types of celebrity endorsers, young consumers tend to be more convinced by their endorsements of products with low levels of consumer involvement than those with high levels of involvement. Among the three types of celebrity endorsements, young consumers find traditional celebrities the most effective. In addition, young consumers’ attitudes toward celebrity endorsers mediate the impact of celebrity endorsers’ attractiveness and credibility on their attitudes toward the advertisements. The perceived level of product involvement moderates the transfer of meaning from the attitude toward the celebrity endorsers to the attitude toward the advertisement.

First, when choosing celebrity endorsers to advertise products targeting young consumers, marketing communication practitioners should give priority to the endorsers’ perceived credibility, as young consumers have a variety of views about them that can significantly affect their attitudes toward the advertisement. Second, real human celebrity endorsers are more effective than virtual idols in celebrity endorsements. However, virtual idols may be suited for use in advertisements to promote products with low involvement levels, such as soft drinks.

To the best of the authors’ knowledge, this is the first experimental study to attempt to analyze the effectiveness of virtual idols in advertising aimed at young consumers. This is also the first comparative study to introduce virtual idols as celebrity endorsers in product advertising and to compare their effectiveness with that of the two other types of commonly discussed celebrity endorsers, traditional celebrities and online influencers.

Given the heavy pollution feature of the construction industry, construction corporations need to adopt an effective environmental governance strategy. The quality and quantity of environmental information disclosure (EID) implementation, as an essential part of a corporate environmental governance strategy, is impacted by the characteristics of the top management team (TMT). This paper aims to analyze the relationship between the demographic characteristics of the TMT (i.e. gender, age, tenure, educational level, and duality) and corporate EID.

Using data from listed construction corporations generated between 2014 to 2018 in China, this study employs the Tobit regression model to test the research hypotheses. Also, this study applies a novel analytical approach, necessary condition analysis (NCA), to conduct a series of additional tests.

The results reveal that tenure and educational level are significantly and positively related to EID, while gender, age, and duality in the executive role are not significantly related to EID. When considering the TMT size as a moderator, the TMT age is positively related to the corporate EID, and the size of the TMT acts as a moderator to weaken the positive effect of the TMT age on the EID. The NCA results show that TMT gender, age, tenure, and educational level are necessary when the levels of EID exceed 40%.

Our findings suggest that TMT characteristics have a relatively significant effect on corporate EID levels, which extends EID research to the construction industry. Corporate planners can endeavor to shape TMT characteristics to improve EID levels. The results of NCA provide insights into what TMT characteristics construction corporations need to satisfy in their pursuit of transparent EID, as well as the levels at which these characteristics are desired.

The growing attention to green supply chain transparency prompts firms to disclose their environmental efforts and manage environmental issues along supply chains. Drawn upon diffusion theory, this study aims to investigate how customers’ environmental efforts can be diffused to suppliers for similar actions, as well as how customers’ (diffusors’) characteristics and suppliers’ (followers’) capability in digital technology application moderate the relationship.

This study collects secondary data of 1,514 unique customer-supplier dyad year observations of Chinese listed firms and their disclosed environmental efforts from 2009 to 2022. A fixed-effect regression model is used to test the hypotheses.

This study reveals a positive association between customers’ disclosed environmental efforts and those of their suppliers. Furthermore, the relationship is strengthened when customers are state-owned or when suppliers possess higher levels of digital technology application capability. These findings remain robust when alternative measures of variables are employed.

This study contributes to the supply chain transparency literature by uncovering the diffusion mechanism of environmental efforts from customers to their suppliers. It further identifies moderators for this diffusion, including customers’ (diffusors’) ownership and suppliers’ (followers’) capability. Lastly, our study extends the applicability of diffusion theory within a buyer–supplier context.

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.

The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to discuss the accuracy and stability of improved empirical mode decomposition (EMD) algorithm in bearing fault diagnosis.

This paper adopts the improved adaptive complementary ensemble empirical mode decomposition (ICEEMD) to process the nonlinear and nonstationary signals. Two data sets including a multistage centrifugal fan data set from the laboratory and a motor bearing data set from the Case Western Reserve University are used to perform experiments. Furthermore, the proposed fault diagnosis method, combined with intelligent methods, is evaluated by using two data sets. The proposed method achieved accuracies of 99.62% and 99.17%. Through the experiment of two data, it can be seen that the proposed algorithm has excellent performance in the accuracy and stability of diagnosis.

According to the review papers, as one of the effective decomposition methods to deal with nonlinear nonstationary signals, the method based on EMD has been widely used in bearing fault diagnosis. However, EMD is often used to figure out the nonlinear nonstationarity of fault data, but the traditional EMD is prone to modal confusion, and the white noise in signal reconstruction is difficult to eliminate.

In this paper only the top three optimal intrinsic mode functions (IMFs) are selected, but IMFs with less correlation cannot completely deny their value. Considering the actual working conditions of petrochemical units, the feasibility of this method in compound fault diagnosis needs to be studied.

Different from traditional methods, ICEEMD not only does not need human intervention and setting but also improves the extraction efficiency of feature information. Then, it is combined with a data-driven approach to complete the data preprocessing, and further carries out the fault identification and classification with the optimized convolutional neural network.

Companies are increasingly benefiting from artificial intelligence (AI) applications in various domains, but also facing its negative impacts. The challenge lies in the lack of clear governance mechanisms for AI. While documentation is a key governance tool, standard software engineering practices are inadequate for AI. Practitioners are unsure about how to document AI, raising questions about the effectiveness of current documentation guidelines. This review examines whether AI documentation guidelines meet regulatory and industry needs for AI applications and suggests directions for future research.

A structured literature review was conducted. In total, 38 papers from top journals and conferences in the fields of medicine and information systems as well as journals focused on fair, accountable and transparent AI were reviewed.

This literature review contributes to the literature by investigating the extent to which current documentation guidelines can meet the documentation requirements for AI applications from regulatory bodies and industry practitioners and by presenting avenues for future research. This paper finds contemporary documentation guidelines inadequate in meeting regulators’ and professionals’' expectations. This paper concludes with three recommended avenues for future research.

This paper benefits from the insights from comprehensive and up-to-date sources on the documentation of AI applications.

This study aims to improve the maneuverability and stability of four-wheel chassis in a small paddy field; a front axle swing steering four-wheel chassis with optimal steering is designed.

When turning, the front inner wheel stops and the rear inner wheel is in the following state. The hydraulic drive system of the walking wheel adopts a driving mode in which two front-wheel motors are connected in series and two rear wheel motors in parallel. The chassis uses a combination of a gasoline engine with a water cooling system, a CVT continuously variable transmission and a hydraulic drive system to increase the control capability. The front axle rotary chassis adopts a step-less variable speed engine and a hydraulic control system to solve the hydraulic stability of the chassis in uphill and downhill conditions so as to effectively control the over-speed of the wheel-side drive motors. Through the quadratic orthogonal rotation combination design test, the mathematical models of uphill and downhill front-wheel pressures and test factors are established.

The results show that the chassis stability is optimal when the back pressure is 0.5 MPa, and the rotating slope is 4°. The uphill and downhill pressures of the front wheels are 2.38 MPa and 1.5 MPa, respectively.

The influence of external changes on the pressure of hydraulic motors is studied through experiments, which lays the foundation for further research.

This study aims to quantify the influence of urbanization on housing prices at the district-based level, while also investigating the heterogeneous impacts across different quantiles of housing prices.

The study uses remote-sensed spectral images from the Landsat 7 ETM+ satellite to measure urbanization, replacing prior reliance solely on urban population metrics. Subsequently, the two-step system generalized method of moments is used to evaluate how urbanization influences district-based housing prices through three spectrometries: Urban Index (UI), Normalized Difference Built-up Index (NDBI) and Built-Up Index (BUI). Finally, this study examines the heterogeneous impacts across various housing price quantiles through Dynamic Panel Quantile Regression with non-additive fixed effects under Markov Chain Monte Carlo simulation.

The study demonstrates that urbanization leads to an increase in regional housing prices. However, these impact magnitudes vary across housing price quantiles. Specifically, the impact exhibits an inverse V-shaped curve, with urbanization exerting a more pronounced influence on the 60th percentile of housing prices, while its effect on the 10th and 90th percentiles is comparatively weaker.

This study uses a novel method of remote sensing to measure urbanization and investigates its effects on housing prices. Furthermore, it provides an empirical application of non-additive fixed effect quantile regression for analyzing heterogeneity.

The modernization of China’s economy is an integral part of Chinese-style modernization. According to the principle of unifying theoretical, historical and practical logic, theoretically explaining the modernization of China’s economy is both a political necessity and a higher scientific requirement.

Following this evolutionary line – from modes of production to the general economic development mechanism and then to patterns of economic operation and development – this paper employs the principal contradiction analysis method to offer an interpretation of China’s economic modernization from the broad Marxist political economy perspective.

In economic terms, “get organized” primarily refers to the development and mutual promotion of team-based and market-based division of labor organizations, as discussed by Karl Marx. “Get organized” (specifically the development of team-based division of labor organizations) acts as the engine of China’s economic modernization and serves as the historical logical starting point. Division of labor is the theoretical logical starting point for interpreting China’s economic modernization. The two of them are congruent, achieving the unity of theoretical and historical logic at the starting point. The development and mutual promotion of these “two types of division of labor” inherently generate the general mechanism of economic development first comprehensively discussed by Marx and Friedrich Engels, which involves the division of labor development and market expansion accumulating cyclically and reinforcing each other. This mechanism drives both the high-speed and high-quality development of China’s economic modernization.

The broad Marxist political economy paradigm facilitates explaining China’s economic modernization theoretically, historically and practically with unified logic. “Get organized” serves as both the engine and the realization mechanism of this modernization, with the Communist Party of China (CPC) consistently being the core force of this organizational effort.