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Drawing on bargaining power and the inequality aversion perspective, this study aims to probe employees’ influence on addressing income inequality between top executives and nonexecutive employees. Meanwhile, it examines the moderating role of employee-related factors and plan attributes.

This study uses a staggered difference-in-differences design with a propensity scoring match approach and verification of the parallel trend assumption to test the hypotheses.

The results support the hypothesis that employee stock ownership plans (ESOPs) significantly reduce within-firm income inequality. The negative effect is amplified by both the presence of trade unions and the unemployment rate at the regional level, as well as the duration of the lock-in period and the scale of participants within the stock ownership plan.

This study has implications for income inequality research and ESOP design and provides theoretical support for policymakers and corporate governance.

This study contributes to the literature on income inequality by examining the implementation of ESOPs from the employee perspective. Furthermore, it extends the current literature by investigating the strengthening effects of regional factors and ESOP attributes on the relationship between ESOPs and income inequality. The conclusions provide new empirical evidence to promote the effective implementation of ESOPs by combining internal and external factors.

This study reveals the green building development path and analyzes the optimal government subsidy equilibrium through evolutionary game theory and numerical simulation. This was done to explore the feasible measures and optimal incentives to achieve higher levels of green building in China.

First, the practice of green building in China was analyzed, and the specific influencing factors and incentive measures for green building development were extracted. Second, China-specific evolutionary game models were constructed between developers and homebuyers under the market regulation and government incentive mechanism scenarios, and the evolutionary paths were analyzed. Finally, real-case numerical simulations were conducted, subsidy impacts were mainly analyzed and optimal subsidy equilibriums were solved.

(1) Simultaneously subsidizing developers and homebuyers proved to be the most effective measure to promote the sustainability of green buildings. (2) The sensitivity of developers and homebuyers to subsidies varied across scenarios, and the optimal subsidy level diminished marginally as building greenness and public awareness increased. (3) The optimal subsidy level for developers was intricately tied to the building greenness benchmark. A higher benchmark intensified the developer’s responsiveness to losses, at which point increasing subsidies were justified. Conversely, a reduction in subsidy might have been appropriate when the benchmark was set at a lower level.

The expeditious advancement of green buildings holds paramount importance for the high-quality development of the construction industry. Nevertheless, the pace of green building expansion in China has experienced a recent deceleration. Drawing insights from the practices of green building in China, the exploration of viable strategies and the determination of optimal government subsidies stand as imperative initiatives. These endeavors aim to propel the acceleration of green building proliferation and materialize high-quality development at the earliest juncture possible.

The model is grounded in China’s green building practices, which makes the conclusions drawn more specific. Furthermore, research results provide practical references for governments to formulate green building incentive policies.

Most of the emphasis in the green building literature on the green performance of buildings has been on optimizing energy and resource efficiency. Admittedly, from the perspective of the sustainable construction industry, making optimally energy and resource efficiency, often seen as a technical challenge, has a premise role in green building projects. However, green buildings need to optimally meet the health, well-being and comfort requirements of their occupants and their environmental quality targets. In that context, perceived quality is a crucial determinant of occupant satisfaction and can play a critical role in the user-oriented improvement of the green performance of buildings. While previous research has highlighted issues related to occupant satisfaction, none of them examines green buildings from a perceived quality perspective. Therefore, the study attempts to fill this research gap.

Firstly, to reveal the positive and negative satisfaction of the building occupants according to the green building features, the review of previous research in the related literature is supplemented by an exploratory study of case studies evaluating occupant satisfaction in green buildings. Then, a conceptual framework is proposed to link perceived quality and green building features towards occupant satisfaction.

A review of the case studies in 49 research articles has shown deficiencies in a comprehensive understanding and approach to the perceived quality of green buildings. In response, the development of a framework for conceptual interrelationships may provide a pathway for more detailed quality assessments for future research. In this study, the proposed conceptual framework has the potential to provide a conceptual basis for future models in determining the relationship between quality expectations and quality experiences in green buildings. It can also serve as a constructive approach for assessing occupant satisfaction in the quality-driven improvements of green buildings and further investigation of the importance of various quality cues, quality attributes and their interactions.

This study aims to incorporate green building features and perceived quality concepts into a framework that can form the basis for assessing occupant satisfaction in green buildings. The ultimate goal of the proposed conceptual framework is to generate an insight that can contribute to rethinking the perceived quality of green buildings and developing more occupant-driven solutions for future green buildings.

Power plant projects are very complex and encounter serious cost overruns worldwide. Their cost overrun risks are not independent but interrelated in many cases, having structural relationships among each other. The purpose of this study is, therefore, to establish the complex structural relationships of risks involved.

In total, 76 published articles from the previous literature are reviewed using the content analysis method. Three risk networks in different phases of power plant projects are depicted based on literature review and case studies. The possible methods of solving these risk networks are also discussed.

The study finds critical cost overrun risks and develops risk networks for the procurement, civil and mechanical works of power plant projects. It identifies potential models to assess cost overrun risks based on the developed risk networks. The literature review also revealed some research gaps in the cost overrun risk management of power plants and similar infrastructure projects.

This study will assist project risk managers to understand the potential risks and their relationships to prevent and mitigate cost overruns for future power plant projects. It will also facilitate decision-makers developing a risk management framework and controlling projects’ cost overruns.

The study presents conceptual risk networks in different phases of power plant projects for comprehending the root causes of cost overruns. A comparative discussion of the relevant models available in the literature is presented, where their potential applications, limitations and further improvement areas are discussed to solve the developed risk networks for modeling cost overrun risks.

This paper aims to explore the pathways of carbon transfer in 200 US corporations along with the motivations that drive such transfers. The particular focus is on each firm’s embeddedness in the global value chain (GVC) and the influence of environmental law, operational costs and corporate social responsibility (CSR). The insights gleaned bridge a gap in the literature surrounding GVCs and corporate carbon transfer.

The methodology comprised a two-step research approach. First, the authors used a two-sided fixed regression to analyse the relationship between each firm’s embeddedness in the GVC and its carbon transfers. The sample consisted of 217 US firms. Next, the authors examined the influence of environmental law, operational costs and CSR on carbon transfers using a quantitative comparison analysis. These results were interpreted through the theoretical frameworks of the GVC and legitimacy theory.

The empirical results indicate positive relationships between carbon transfers and GVC embeddedness in terms of both a firm’s position and its degree. From the quantitative comparison, the authors find that the pressure of environmental law and operational costs motivate these transfers through the value chain. Furthermore, CSR does not help to mitigate transfers.

The findings offer insights for policymakers, industry and academia to understand that, with globalised production and greater value creation, transferring carbon to different parts of the GVC – largely to developing countries – will only become more common. The underdeveloped nature of environmental technology in these countries means that global emissions will likely rise instead of fall, further exacerbating global warming. Transferring carbon is not conducive to a sustainable global economy. Hence, firms should be closely regulated and given economic incentives to reduce emissions, not simply shunt them off to the developing world.

Carbon transfer is a major obstacle to effectively reducing carbon emissions. The responsibilities of carbon transfer via GVCs are difficult to define despite firms being a major consideration in such transfers. Understanding how and why corporations engage in carbon transfers can facilitate global cooperation among communities. This knowledge could pave the way to establishing a global carbon transfer monitoring network aimed at preventing corporate carbon transfer and, instead, encouraging emissions reduction.

This study extends the literature by investigating carbon transfers and the GVC at the firm level. The authors used two-step research approach including panel data and quantitative comparison analysis to address this important question. The authors are the primary study to explore the motivation and pathways by which firms transfer carbon through the GVC.

High-quality labor supply is inevitable to maintain sustainable and steady economic growth. This study mainly explores the impact of the social pension system on the health of human capital, and further explores its impact mechanism.

On the basis of the data from China Family Panel Studies from 2012 to 2018, this article uses the fixed effect model and the mediation effect model to empirically study the influence of the social pension scheme on the health of human capital and further explore its influence mechanism.

This study shows that the social pension scheme can significantly improve the physical and mental health of laborers, especially for low-income and agricultural groups. The implementation of the social pension scheme contributes to increasing medical services and reducing the labor supply for the benefit of human health capital. Therefore, the government should continue to expand the coverage of the social pension scheme and comprehensively improve the importance of human health capital on economic growth.

Medical costs and labor supply play a mediating effect in the relationship between social pension and rural labors' health status, which indicates that medical costs and labor supply level are still important factors affecting the health status of rural labor. There are essential factors affecting the health status of the rural labor force, and their role should be given more consideration in the process of system design and improvement.

The existing studies have more frequently studied the effect of the implementation of social pension schemes from the perspective of economic performance, but this paper evaluates the policy effect of social pension schemes based on the perspective of health human capital, which enriches research on health performance in related fields.

In the continuous development of high-speed railways, ensuring the safety of the operation control system is crucial. Electromagnetic interference (EMI) faults in signaling equipment may cause transportation interruptions, delays and even threaten the safety of train operations. Exploring the impact of disturbances on signaling equipment and establishing evaluation methods for the correlation between EMI and safety is urgently needed.

This paper elaborates on the necessity and significance of studying the impact of EMI as an unavoidable and widespread risk factor in the external environment of high-speed railway operations and continuous development. The current status of research methods and achievements from the perspectives of standard systems, reliability analysis and safety assessment are examined layer by layer. Additionally, it provides prospects for innovative ideas for exploring the quantitative correlation between EMI and signaling safety.

Despite certain innovative achievements in both domestic and international standard systems and related research for ensuring and evaluating railway signaling safety, there’s a lack of quantitative and strategic research on the degradation of safety performance in signaling equipment due to EMI. A quantitative correlation between EMI and safety has yet to be established. On this basis, this paper proposes considerations for research methods pertaining to the correlation between EMI and safety.

This paper overviews a series of methods and outcomes derived from domestic and international studies regarding railway signaling safety, encompassing standard systems, reliability analysis and safety assessment. Recognizing the necessity for quantitatively describing and predicting the impact of EMI on high-speed railway signaling safety, an innovative approach using risk assessment techniques as a bridge to establish the correlation between EMI and signaling safety is proposed.

This paper elucidates the role of anger in error management (EM) and organizational learning behaviors. The study explores how anger can catalyze learning, emphasizing its strategic implications.

A double-layered moderated-mediated model was developed and tested using data from 744 Chinese CEOs. The psychometric properties of the survey instrument were rigorously examined through structural equation modeling, and hypotheses were tested using Hayes's PROCESS macros.

The findings reveal that anger is a precursor for recognizing the value of significant errors, leading to a positive association with learning behavior among top management team members. Additionally, the study uncovers a triple interaction effect of anger, EM culture and supply chain disruptions on the value of learning from errors. Extensive experience and positive grieving strengthen the relationship between recognizing value from errors and learning behavior.

This study uniquely integrates affect-cognitive theory and organizational learning theory, examining anger in EM and learning. The authors provide empirical evidence that anger can drive error value recognition and learning. The authors incorporate a more fine-grained approach to leadership when including executive anger as a trigger to learning behavior. Factors like experience and positive grieving are explored, deepening the understanding of emotions in learning. The authors consider both negative and positive emotions to contribute to the complexity of organizational learning.

The purpose of this study is to investigate the effect of nano ZrC particles on the mechanical and electrochemical corrosion properties of FeCrAl alloys, providing a beneficial reference basis for the development of high-performance carbide reinforced FeCrAl alloys with good mechanical and corrosion properties in the future.

Nano ZrC reinforced FeCrAl alloys were prepared by mechanical alloying and spark plasma sintering. Phases composition, tensile fractography, corrosion morphology and chemical composition of nano ZrC reinforced FeCrAl alloys were analyzed by X-ray diffraction, scanning electron microscopy and energy dispersive X-ray spectroscopy, respectively. Microhardness and tensile properties of nano ZrC reinforced FeCrAl alloys were investigated by mechanical testing machine and Vickers hardness tester. Electrochemical corrosion properties of nano ZrC reinforced FeCrAl alloys were investigated by electrochemical workstation in 3.5 wt.% NaCl solution.

The results showed that addition of nano ZrC can effectively improve the mechanical and corrosion properties. However, excessive nano ZrC could decrease the mechanical properties and reduce the corrosion resistance. In all the FeCrAl alloys, FeCrAl–0.6 wt.% ZrC alloy exhibits the optimum mechanical properties with an ultimate tensile strength, elongation and hardness of 990.7 MPa, 24.1% and 335.8 HV1, respectively, and FeCrAl–0.2 wt.% ZrC alloy has a lower corrosion potential (−0.179 V) and corrosion current density (2.099 µA/cm2) and larger pitting potential (0.497 V) than other FeCrAl–ZrC alloys, showing a better corrosion resistance.

Adding proper nano ZrC particles can effectively improve the mechanical and corrosion properties, while the excessive nano ZrC is harmful to the mechanical and corrosion properties of FeCrAl alloys, which provides an instruction to develop high-performance FeCrAl cladding materials.

This paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the I-Optimal design.

I-optimal design methodology is used to plan the experiments by means of Minitab-17.1 software. Samples are manufactured using Stratsys FDM 400mc and tested as per ISO standards. Additionally, an artificial neural network model was developed and compared to the regression model in order to select an appropriate model for optimisation. Finally, the genetic algorithm (GA) solver is executed for improvement of tensile strength of FDM built PC components.

This study demonstrates that the selected process parameters (raster angle, raster to raster air gap, build orientation about Y axis and the number of contours) had significant effect on tensile strength with raster angle being the most influential factor. Increasing the build orientation about Y axis produced specimens with compact structures that resulted in improved fracture resistance.

The fitted regression model has a p-value less than 0.05 which suggests that the model terms significantly represent the tensile strength of PC samples. Further, from the normal probability plot it was found that the residuals follow a straight line, thus the developed model provides adequate predictions. Furthermore, from the validation runs, a close agreement between the predicted and actual values was seen along the reference line which further supports satisfactory model predictions.

This study successfully investigated the effects of the selected process parameters - raster angle, raster to raster air gap, build orientation about Y axis and the number of contours - on tensile strength of PC samples utilising the I-optimal design and ANOVA. In addition, for prediction of the part strength, regression and ANN models were developed. The selected ANN model was optimised using the GA-solver for determination of optimal parameter settings.

The proposed ANN-GA approach is more appropriate to establish the non-linear relationship between the selected process parameters and tensile strength. Further, the proposed ANN-GA methodology can assist in manufacture of various industrial products with Nylon, polyethylene terephthalate glycol (PETG) and PET as new 3DP materials.