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This study investigates the influence of market and hierarchy organizational cultures on international project performance and examines the mediating role of relational capital.

In-depth interviews and a cross-sectional questionnaire survey were conducted to collect primary data within international projects. Hierarchical regression analysis was used to test the hypotheses based on data collected from 62 respondents.

The results reveal that both market and hierarchy cultures affect international project performance positively. Additionally, communication, cooperation and trust help enhance project performance; however, commitment is not. This study also proves the mediating role of relational capital between organizational culture and project performance.

This study selected only two types of organizational culture represented by Chinese construction enterprises. Future studies can explore the mediating role of relational capital between other varieties of organizational culture and project performance.

Given the high complexity and risks faced by projects abroad, both organizational culture, the internal environmental factor and relational capital being the external resource, are crucial for project success. This study clarifies the relationship between organizational culture, relational capital and project performance overseas. Empirical evidence to enhance international project performance for construction enterprises is provided. This study also makes contributions to international contractors who want to implement projects in developing countries.

Consider the mutual coupling between loads, the purpose of this paper is to study the total transmission efficiency based on different load coil positions relative to the charging platform, to provide the theoretical basis for the design and parameter optimization of one-to-multiple wireless charging platform.

Based on the dual-load series-resonant wireless power transfer system, the expression of system efficiency and its calculation model is achieved using the equivalent circuit theory. Finally, a 96 kHz magnetic resonance wireless power transmission test platform is built up to verify the theoretical analysis given in this paper.

For the completely resonant circuit, the transmission efficiency can be improved by increasing the transmitter-receiver coupling and reducing the coupling between receivers. The total transmission efficiency achieves its lowest value when two loads are with equal competitive capability.

Through the simulation analysis of efficiency formula, the selection principle of impact factors can be applied to the optimization analysis of the transmission efficiency.

The purpose of this study was to solve the problem of most woven-fabric self-lubricating bearings that find it difficult to function at temperatures above 320°C, by designing a new type of new nuclear joint bearing. The results of this study will help designers to achieve accurate stress distribution, displacement deformation, fatigue life and damage of bearings. All of these can be a guide for designing self-lubricating joint bearings.

Finite element analysis is undertaken to simulate the new design bearings. To get the most appropriate and accurate results, the room temperature simulation (Simulation A), the modulus of elasticity that changes with temperature (Simulation B) and the thermal-structure-coupled simulation (Simulation C) are compared. The fatigue simulation is conducted to verify whether the self-lubricating method is reasonable and whether the bearing can function for over 60 years in an enclosed environment.

Stress distribution and displacement deformation of joint bearing can be accurately achieved via the thermal-structure coupled simulation. Work life and damage results have been achieved via the fatigue analysis, and the suggested working loads can be calculated via safety factors.

The newly designed joint bearing in which the graphite is laid on the outside of the inner ring functions and self-lubricates at temperatures above 320°C.

Integrating self-determination theory with work-family boundary theory, this study delves into the mechanism (i.e. workplace anxiety) and boundary (i.e. intrinsic motivation) by which family motivation can inadvertently escalate work interference with family.

We conducted two three-wave field survey studies of 468 employees and 298 employees in China to test the theoretical model.

When intrinsic motivation is weak, employees with high family motivation feel anxious at work and thus experience more work interference with family.

The motivation to support one’s family through work increases the possibility of workplace anxiety and work interference with family. To alleviate this impact, cultivating intrinsic motivation is important. Thus, we encourage employees to be compassionate toward their internal feelings and needs while performing their jobs. Moreover, organizations are encouraged to improve employees’ intrinsic motivation by implementing practices that support their basic psychological needs.

This study casts new light on the potential adverse effects that family motivation may have on the work-family interface, challenging the prevalent belief that working for the family invariably improves the work-family interface. Moreover, it provides a new lens to understand how valuing the family inadvertently increases work interference with family.

The purpose of this paper is to examine the effect of employees' self-efficacy on employees' organizational identification. Based on a self-verification perspective, this paper focuses on the mediating role of leader–member exchange social comparison (LMXSC) and the moderating role of perceived organizational justice.

The authors conducted a field survey (Study 1) of 207 employees recruited from multiple financial organizations and tested a moderated mediation model using Hayes's (2018) PROCESS macro. The authors conducted another scenario-based experiment (Study 2) using a sample of 151 employees recruited online to further establish causality in our model.

Results suggest that employees' self-efficacy is positively associated with their LMXSC, which, in turn, positively impacts employees' organizational identification. The positive relationship between LMXSC and organizational identification is stronger when employees' perceived organizational justice is higher. The indirect effect of self-efficacy on organizational identification through LMXSC is also strengthened by perceived organizational justice.

Managers are encouraged to develop employees' self-efficacy and to create a fair environment to promote employees' identification with the organization.

This research extends organizational identification literature by examining how and when employees' self-efficacy, a dispositional predictor, leads to employees' identification with the organization from a self-verification perspective.

Malicious web domain identification is of significant importance to the security protection of internet users. With online credibility and performance data, the purpose of this paper to investigate the use of machine learning techniques for malicious web domain identification by considering the class imbalance issue (i.e. there are more benign web domains than malicious ones).

The authors propose an integrated resampling approach to handle class imbalance by combining the synthetic minority oversampling technique (SMOTE) and particle swarm optimisation (PSO), a population-based meta-heuristic algorithm. The authors use the SMOTE for oversampling and PSO for undersampling.

By applying eight well-known machine learning classifiers, the proposed integrated resampling approach is comprehensively examined using several imbalanced web domain data sets with different imbalance ratios. Compared to five other well-known resampling approaches, experimental results confirm that the proposed approach is highly effective.

This study not only inspires the practical use of online credibility and performance data for identifying malicious web domains but also provides an effective resampling approach for handling the class imbalance issue in the area of malicious web domain identification.

Online credibility and performance data are applied to build malicious web domain identification models using machine learning techniques. An integrated resampling approach is proposed to address the class imbalance issue. The performance of the proposed approach is confirmed based on real-world data sets with different imbalance ratios.

This study aims to propose a set of institutional frameworks, as well as practical polices and steps, with a view to facilitating the establishment of a unified carbon trading market in China.

Based on existing empirical studies and reviews of the socioeconomic contexts, this study followed a qualitative approach consisting of secondary data collection and analysis, semi-structured interviews to collect primary data and comparative analysis.

The establishment of a national carbon trading market in China is a systemic and complex process which requires coordination among various concerned government agencies and supporting mechanisms. Currently, the development of a unified national carbon market has been impeded by the lack of coordination among local pilot programs, and there is no specific law passed by the People’s Congress or by its Standing Committee to regulate the emerging carbon trading market. It is of vital importance for China, in terms of both practical and strategic aspects, to take a gradualist approach in establishing laws and institutions to guide and support the development of its emerging carbon market.

This present study forms a part of a regional research project aiming to identify sound policy approaches for the establishment of a carbon trading market in China. Due to scope reasons, it focuses only on policy analysis and recommendations.

China’s emerging national carbon trading market has attracted much research attention. However, little has been done from the perspectives of legislations and policies.

The purpose of this paper is to synthesize a microemulsion and investigate its tribological properties as lubricant. Magnesium alloy warm rolling experiments were conducted. Surface morphology was observed and wear form was summarized. The composition of surface residues was analyzed, which sheds light on the lubrication mechanism of microemulsion.

A microemulsion was prepared with a proper amount of oil, surfactant, cosurfactant, water and other additives for magnesium alloy strip warm rolling. Tribological properties, such as maximum non-seizure load (P_B), friction coefficient (μ) and wear scar diameter (D) of the microemulsion were measured and compared with those of emulsion and rolling oil on an MR-10A four-ball tribotester. The extreme pressure anti-wear coefficients (O) were calculated and compared. Warm rolling experiments were carried out on a Ф 170/400 × 300 mm four-high rolling mill at 240°C to compare the finish rolling thickness and surface quality of rolled AZ31B magnesium alloy strip under four lubrication states, namely, no lubrication, rolling oil, microemulsion and emulsion. The surface morphology after warm rolling was observed with confocal laser scanning microscope and scanning electron microscope, respectively. The composition of surface residues was analyzed with energy dispersive spectrometry and X-Ray photoelectron spectroscopy.

Surface morphology indicated that pitting wear, adhesive wear and ploughing wear were three main forms of wear in magnesium alloy warm rolling. Microemulsion had excellent lubrication properties with less residual oil remaining. Two types of adsorption layers formed on magnesium alloy strip surface were responsible for lubrication properties. MgSO₄ and magnesium stearate in the reaction layer played a key role in anti-wear and friction-reduction in warm rolling.

The study is original and gives valuable information on lubrication mechanism of microemulsion in warm rolling of magnesium alloy strips.

Under the pressure of environment degradation and energy consumption rises, solar photovoltaic power generation (SPPG) has been seen as a strategic emerging industry in China. However, the SPPG projects have many uncertain factors in the process of the life cycle. The purpose of this paper is to evaluate the investment risk comprehensively.

Specifically, this paper firstly identified the risk factors and consequences of SPPG project investment and constructed the investment risk factor evaluation index system. Secondly, the factor analysis method was used to reveal the key investment risk factors and risk consequences. Then, the research hypotheses and conceptual model were proposed, and the empirical analysis was conducted based on the structural equation model (SEM).

The results showed that the six key risk factors (political, economic, technological, management, market and natural) have a significant impact on the risks during the whole period. The influence degree of risk factors in the operational period is such that market factor > political factor > economic factor > management factor > natural factor > technical factor. In addition, the risk of constructional period has a significant impact during the risk of operational period. Except for natural factors, all risk factors are correlated among the mutual influence relationship of risk factors. Finally, this paper puts forward management implications based on the above conclusions: effectively identify investment risk factors and comprehensively improve risk management ability; (refine the risk factors of SPPG project investment and develop targeted risk prevention and control strategies; define risk management objectives and make relevant strategic plans.

Because of the chosen research approach, the research results may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions further.

It can also help stakeholders propose risk prevention strategies throughout the entire process, to promote the sustainable development of SPPG projects.

This study focuses on the investment risk of SPPG projects, by building an evaluation index system to identify key risk factors, and then establishes a SEM covering constructional period risks and operational period risks to better explore SPPG project risks, in an effort to reveal the mutual influence relationship and influence path of investment risk factors of the projects.

To explore how the blockchain affects the pricing and financing decisions in a low-carbon platform supply chain.

Considering the dual roles of the e-commerce platform as a seller and an initiator, a typical game-theoretical method is applied to analyze the behavior of supply chain decision-makers and the impact of key variables on equilibriums.

When loan interest rates are symmetric, whether blockchain is used or not, the e-commerce platform financing mode will always produce higher wholesale price and unit carbon emission reduction, while the retail price is the opposite. Higher unit additional income brought by the blockchain can bring higher economic and environmental performances, and the e-commerce platform financing mode is superior to bank financing mode. The application of blockchain may cause the manufacturer to change his/her financing choice. For bank financing, with the increase of loan interest rates, the advantages brought by blockchain will gradually disappear, but this situation will not occur under e-commerce platform financing.

Blockchain is known for its information transparency properties and its ability to enhance user trust. However, the impacts of applying blockchain in a low-carbon platform supply chain with different financing options are not clear. The authors examine the manufacturer's strategic choices for platform financing and bank financing, whether to adopt blockchain, and the impact of these decisions on carbon emissions reduction, consumer surplus and social welfare. The research conclusion can provide reference for the operation and financing decisions of platform supply chain under the carbon reduction target in the digital economy era.