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Because of increasing wealth inequality, China has been confronted with resentment against the rich (referred to hereafter as RAR or Choufu in Chinese), which is a growing concern owing to its potential to foment social conflict. Drawing on social comparison and deonance theories, this paper aims to provide theoretical insights into RAR within the Chinese context and to develop an RAR scale. Following spillover theory, the attitudinal and behavioral outcomes of RAR in organizational settings will be explored.

This research consists of two studies. Study 1 conceptualizes RAR and develops an RAR scale by using three separate samples. Exploratory and confirmatory factor analyses are conducted to establish scale reliability and validity. Study 2 uses hierarchical linear regression analysis to test whether employees’ RAR attitude spills over from the societal to the organizational setting.

Results suggest that RAR can be conceptualized as two distinct but related dimensions – emotional RAR and moral RAR. These two forms spill over to the workplace, influencing employees’ work attitudes and behaviors. Emotional RAR relates negatively to life satisfaction and prosocial organizational behaviors and positively to unethical organizational behaviors. Moral RAR relates negatively to pay satisfaction and positively to prosocial behaviors.

This research suggests that RAR has spillover effects from societal to organizational settings and demonstrates that a more robust understanding of employees’ workplace experience requires acknowledging social experiences, such as conflicts beyond the workplace.

This research contributes to the conflict management literature by exploring RAR as a negative attitude that serves to potentially ignite social conflict. It not only develops a theory-grounded, conceptual RAR model and a reliable RAR scale but also for the first time explores RAR attitudinal and behavioral outcomes beyond the social domain. This study serves as a meaningful touchstone for future research to incorporate social attitudes into organizational behavior research.

Hand, foot and mouth disease (HFMD) is a common infectious disease in infants and children. HFMD has caused millions of cases and a large epidemic worldwide. A number of studies have shown that the incidence of HFMD is closely related to various factors such as meteorological factors, environmental air pollution factors and socio-economic factors. However, there are few studies that systematically consider the impact of various factors on the incidence of HFMD. The paper aims to discuss these issues.

This study used grey correlation analysis and principal component analysis (PCA) method to systematically analyse the impact of meteorological factors, health resource factors, socio-economic factors and environmental air pollution factors on the incidence of HFMD in Shenzhen.

The incidence of HFMD in Shenzhen was affected by multiple factors. Grey correlation analysis found eight influencing factors which are as follows: volume of industrial waste gas emission; the days of air quality equal to or above grade; the volume of industrial nitrogen oxide emission; precipitation; the mean air temperature; the gross domestic product; the expenditure for medical and health care; and the gross domestic product per capita. PCA found that the gross domestic product, the volume of industrial soot emission, the relative humidity, and the days of air quality equal to or above grade have a higher load value.

This study is the one of the first studies that apply the grey correlation analysis to analyse the influencing factors of HFMD in the English literature, which to some extent fills up the blank in this field.

The purpose of this paper is to propose a subcontractor selection model to fully consider the impact of construction enterprise demands on subcontractor selection. The objectives are to understand the translating process of specific enterprise demands to the evaluating criteria and the weight calculation process.

A three-stage model of subcontractor selection was designed based on quality function deployment (QFD), analytic hierarchy process (AHP) and improved grey correlation analysis (IGCA). In the proposed model, specific enterprise demands are translated by the QFD method, and the weights of the criteria are determined by the IGCA. The AHP is used to quantify the exporters' experience and construct the judgment matrix, which is used as inputting of the grey correlation analysis.

The proposed model provides a feasible process for subcontractor selection by fully considering the actual requirements of the project. By combining the company requirements and project requirement to put forward the requirements of the target subcontractor, the selection process ensures that the selected subcontractor and the project have a higher “fit”

Few researches on construction subcontractor selection have taken into account the “voice” of the company's stakeholders. Therefore, this paper designs a three-stage construction subcontractor selection model by introducing QFD to achieve the transmission of “voice” in the subcontractor selection process, so as to take full consideration of the project objectives and the needs of the company's stakeholders. Meanwhile, in order to decrease the subjective of weight calculation, this paper designs an AHP-IGCA allocation method to determine the weight of relevant indicators. By integrating the proposed weight calculation method and QFD method, the subcontractor selection results become more reasonable and objective.

The purpose of this article is to prepare graphene/polyimide composite materials for use as bearing cage materials, improving the friction and wear performance of bearing cages.

The oil absorption and discharge tests were conducted to evaluate the oil content properties of the materials, while the mechanical properties were analyzed through cross-sectional morphology examination. Investigation into the tribological behavior and wear mechanisms encompassed characterization and analysis of wear trace morphology in PPI-based materials. Consequently, the influence of varied graphene nanoplatelets (GN) concentrations on the oil content, mechanical and tribological properties of PPI-based materials was elucidated.

The composites exhibit excellent oil-containing properties due to the increased porosity of PPI-GN composites. The robust formation of covalent bonds between GN and PPI amplifies the adhesive potency of the PPI-GN composites, thereby inducing a substantial enhancement in impact strength. Notably, the PPI-GN composites showed enhanced lubrication properties compared to PPI, which was particularly evident at a GN content of 0.5 Wt.%, as evidenced by the minimization of the average coefficient of friction and the width of the abrasion marks.

This paper includes implications for elucidating the wear mechanism of the polyimide composites under frictional wear conditions and then to guide the optimization of oil content and tribological properties of polyimide bearing cage materials.

In this paper, homogeneously dispersed PPI-GN composites were effectively synthesized by introducing GN into a polyimide matrix through in situ polymerization, and the lubrication mechanism of the PPI composites was compared with that of the PPI-GN composites to illustrate the composites’ superiority.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0415

Psychosocial factors have received increasing attention regarding significantly influencing safety in the construction industry. This research attempts to comprehensively summarize psychosocial factors related to safety performance of construction workers. In the context of coronavirus disease 2019, some typical psychosocial factors are selected to further analyze their influence mechanism of safety performance.

First, a literature review process was conducted to identify and summarize relevant psychosocial factors. Then, considering the impact of the epidemic, hypotheses on the relationship between six selected psychosocial factors (i.e. work stress, role ambiguity, work–family conflict, autonomy, social support and interpersonal conflict) and safety performance were proposed, and a hypothetical model was developed based on job demands-resources theory. Finally, a meta-analysis was used to examine these hypotheses and the model.

The results showed these psychosocial factors indirectly influenced workers’ safety performance by impacting on their occupational psychology condition (i.e. burnout and engagement). Work stress, role ambiguity, work–family conflict and interpersonal conflict were negatively related to safety performance by promoting burnout and affecting engagement. Autonomy and social support were positively related to safety performance by improving work engagement and reducing burnout.

This research is the pioneer systematically describing the overall picture of psychosocial factors related to the safety performance of construction workers. Through deeply discussed the mechanism of psychosocial factors and safety performance, it could provide a reference for the theory and application of psychosocial factors in the field of construction safety management.

The purpose of this study is to prepare ZnFe₂O₄ nanospheres, sheet MoS₂ and three ZnFe₂O₄@MoS₂ core-shell composites with various shell thicknesses, and add them to the base oil for friction and wear tests to simulate the wear conditions of hybrid bearings.

Through the characterization and analysis of the morphology of wear scars and the elemental composition of friction films, the tribological behavior and wear mechanism of sample materials as lubricant additives were investigated and the effects of shell thickness and sample concentration on the tribological properties of core–shell composite lubricant additives were discussed.

The findings demonstrate that each of the five sample materials can, to varying degrees, enhance the lubricating qualities of the base oil and that the core–shell nanocomposite sample lubricant additive has superior lubricating properties to those of ZnFe₂O₄ and MoS₂ alone, among them ZnFe₂O₄@MoS₂-2 core–shell composites with moderate shell thickness performed most ideally. In addition, the optimal concentration of the ZnFe₂O₄@MoS₂ lubricant additive was 0.5 Wt.%, and a concentration that was too high led to particle deposition and affected the friction effect.

In this work, ZnFe₂O₄@MoS₂ core–shell composites were synthesized for the first time using ZnFe₂O₄ as the carrier and the lubrication mechanism of core–shell composites and single materials were compared and studied, which illustrated the advantages of core–shell composite lubricant additives. At the same time, the influence of different shell thicknesses on the lubricant additives of core–shell composites was studied.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2022-0367/

Accurate prediction of seasonal power consumption trends with impact disturbances provides a scientific basis for the flexible balance of the long timescale power system. Consequently, it fosters reasonable scheduling plans, ensuring the safety of the system and improving the economic dispatching efficiency of the power system.

First, a new seasonal grey buffer operator in the longitudinal and transverse dimensional perspectives is designed. Then, a new seasonal grey modeling approach that integrates the new operator, full real domain fractional order accumulation generation technique, grey prediction modeling tool and fruit fly optimization algorithm is proposed. Moreover, the rationality, scientificity and superiority of the new approach are verified by designing 24 seasonal electricity consumption forecasting approaches, incorporating case study and amalgamating qualitative and quantitative research.

Compared with other comparative models, the new approach has superior mean absolute percentage error and mean absolute error. Furthermore, the research results show that the new method provides a scientific and effective mathematical method for solving the seasonal trend power consumption forecasting modeling with impact disturbance.

Considering the development trend of longitudinal and transverse dimensions of seasonal data with impact disturbance and the differences in each stage, a new grey buffer operator is constructed, and a new seasonal grey modeling approach with multi-method fusion is proposed to solve the seasonal power consumption forecasting problem.

The highlights of the paper are as follows:

1. A new seasonal grey buffer operator is constructed.

2. The impact of shock perturbations on seasonal data trends is effectively mitigated.

3. A novel seasonal grey forecasting approach with multi-method fusion is proposed.

4. Seasonal electricity consumption is successfully predicted by the novel approach.

5. The way to adjust China's power system flexibility in the future is analyzed.

A new seasonal grey buffer operator is constructed.

The impact of shock perturbations on seasonal data trends is effectively mitigated.

A novel seasonal grey forecasting approach with multi-method fusion is proposed.

Seasonal electricity consumption is successfully predicted by the novel approach.

The way to adjust China's power system flexibility in the future is analyzed.

This paper aims to obtain the evolution law of dynamic performance of CR400BF electric multiple unit (EMU).

Using the dynamic simulation based on field test, stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers were tested. Stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to research the evolution law with running mileage of dynamic index of CR400BF EMU.

The results showed that stiffness and damping coefficient subjected to normal distribution, the mean and variance were computed and the evolution law of stiffness and damping coefficient with running mileage was obtained.

Firstly, based on the field test we found that stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers subjected to normal distribution, and the evolution law of stiffness and damping coefficient with running mileage was proposed. Secondly stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to the research to the evolution law with running mileage of dynamic index of CR400BF EMU.

In order to systematically grasp the changes and matching characteristics of wheel and rail profiles of high speed railway (HSR) in China, 172 rail profile measurement points and 384 wheels of 6 high-speed electric motive unites (EMUs) were selected on 6 typical HSR lines, including Beijing–Shanghai, Wuhan–Guangzhou, Harbin–Dalian, Lanzhou–Xinjiang, Guiyang–Guangzhou and Dandong–Dalian for a two-year field test.

Based on the measured data, the characteristics of rail and wheel wear were analyzed by mathematical statistics method. The equivalent conicity of wheel and rail matching in a wheel reprofiling cycle was analyzed by using the measured rail profile.

Results showed that when the curve radius of HSR was larger than 2,495 m, the wear rate of straight line and curve rail was almost the same. For the line with annual traffic gross weight less than 11 Mt, the vertical wear of rail was less than 0.01 mm. The wear rate of the rail with the curve radius less than 800 m increased obviously. The wheel tread wear of EMUs on Harbin–Dalian line, Lanzhou–Xinjiang line and Dandong–Dalian line was relatively large, and the average wear rate of tread was about 0.05–0.06 mm·(10,000 km)⁻¹, while that of Beijing–Shanghai line, Wuhan–Guangzhou line and Guiyang–Guangzhou line was about 0.03–0.035 mm·(10,000 km)⁻¹. When the wear range was small, the equivalent conicity increased with the increase of wheel tread wear. When the wear range of wheel was wide, the wheel–rail contact points were evenly distributed, and the equivalent conicity did not increase obviously.

This research proposes the distribution range of the equivalent conicity in one reprofiling cycle of various EMU trains, which provides guidance for the condition-based wheel reprofiling.