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Understanding the customers’ habits of getting cosmetic products information is of great importance to enhance the effectiveness of advertising and marketing strategy of cosmetics. In China, as females are the major target customers of cosmetics, this paper aims to analyze the information behaviors of obtaining cosmetics information of different women groups, including the preferences of information channels and the corresponding means of getting information.

This research is based on a questionnaire survey. A total of 419 effective questionnaires were collected from females who had bought cosmetics in China. Descriptive statistics and chi-square analysis were used to analyze the data.

According to the result of the questionnaire survey, women preferred to get information through social platforms and physical stores. And the primary reason of the choice was that they believed the information from the channel they chose was reliable. The survey also revealed that age, educational level and occupation would significantly affect their preferences of information channels.

There was no previous research which analyzed Chinese women consumers’ information-seeking behaviors about cosmetic products information as well as the influence factors of the behaviors.

The purpose of this paper is to focus on the galvanic corrosion behaviors of the low-carbon ferritic stainless steel electrical resistance welding (ERW) joint in the simulated seawater.

The electrochemical methods such as electrochemical noise, galvanic current and TOEFL polarization curve tests were used to study the galvanic corrosion behaviors of ERW joints of low-carbon ferritic stainless steel in simulated seawater. On this basis, a reliable accelerated corrosion method was developed.

The corrosion type of the base metal and joint is the typical local corrosion. The order of corrosion resistance from strong to weak is: weld zone > base metal > low-temperature heat-affected zone (HAZ) > high-temperature HAZ. The results of constant current-constant potential accelerated corrosion test show that after constant current-constant potential accelerated corrosion, the joints present a typical groove corrosion pattern. The groove initiating area is located in the HAZ, and the corrosion degree in the weld zone is relatively light, which is consistent with the electrochemical test results.

This paper has clarified the galvanic corrosion behaviors of low-carbon ferritic stainless steel ERW joints. Moreover, a reliable accelerated corrosion method for the low-carbon ferritic stainless steel ERW joint has been developed.

Two friction models of Fe-Fe and Diamond-like carbon (DLC)-Fe were established by molecular dynamics (MD) method to simulate the friction behavior of traditional fracturing pump plunger and new DLC plunger from atomic scale. This paper aims to investigate the effects of temperature and load on the friction behavior between sealed nitrile butadiene rubber (NBR) and DLC films.

In this study, MD method is used to investigate the friction behavior and mechanism of DLC film on plungers and sealing NBR based on Fe-Fe system and DLC-Fe system.

The results show that the friction coefficient of DLC-Fe system exhibits a downward trend with increasing load and temperature. And even achieve a superlubricity state of 0.005 when the load is 1 GPa. Further research revealed that the low interaction energy between DLC and NBR promoted the proportion of atoms with larger shear strain in NBR matrix and the lower Fe layer in DLC-Fe system to be much lower than that in Fe-Fe system. In addition, the application of DLC film can effectively inhibit the temperature rise of friction interface, but will occur relatively large peak velocity.

In this paper, two MD models were established to simulate the friction behavior between fracturing pump plunger and sealing rubber. Through the analysis of mean square displacement, atomic temperature, velocity and Interaction energy, it can be seen that the application of DLC film has a positive effect on reducing the friction of NBR.

Drawing on engagement theory, this study aims to examine how leader–member relationships, including on-work relationship (leader–member exchange [LMX]) and off-work relationship (leader–member guanxi [LMG]), influence employees’ promotive and prohibitive voice. Furthermore, the study uses procedural justice as the moderator to distinguish the effects of LMG and LMX on employees’ psychological states and voice through a mediated moderation model.

The authors use a sample from a private and local company in Southern China to test their theoretical model.

The study finds that both LMG and LMX have positive effects on employees’ voice behavior through employees’ psychological states (psychological meaningfulness and psychological safety).

In a Chinese context, leaders have a more direct and powerful influence on employees than their counterparts in the Western society. Thus, the findings of LMX and LMG may not be generalizable to a Western context. A possible extension is to examine and compare the effects of social context (e.g., off-work leader–member relationship) on voice between the East and the West.

One important implication is that off-work relationship should be used by managers to encourage employee voice.

This study enriches the antecedents of voice with a new dimension of leader–member relationship, namely, LMG.

Due to the complicated nature of houses, the driving factors of the residential construction output can be investigated from different perspectives of interests. However, little research has provided an insight of the trend of the residential construction output from a cross-disciplinary perspective. The purpose of this paper is to identify the long-run equilibrium types of residential construction output, including external equilibrium, solo-market equilibrium and dual-market equilibrium.

A vector error correction model is applied into longitudinal data in the eight Australian states and territories to overview the regional variations of the residential construction output.

The empirical results show that the equilibrium of regional residential construction outputs in New South Wales and Victoria are determined by the external factors; the equilibrium in Western Australia is dominated by the construction market; and the equilibriums in the other five states and territories are influenced by both construction and house markets.

The simplified approach may overlook the detailed explanation of the external factors, such as regional population, economy, policy and so forth. Given this limitation, future studies can introduce the correspondingly variables as per research interests.

Implementing the existing research into residential construction output and house supply, this research provides a simplified approach that demonstrates the linkage between construction and real estate sectors to identify the long-run equilibriums across regions. The underlying research sheds light in delivering inter-disciplinary research into the residential construction output.

The purpose of this paper is to empirically study the impact of the coronavirus disease 2019 (COVID-19) on food prices in China and provides policy implications for crisis management for other countries who are still under the crisis of COVID-19 and for the future in China and beyond as well.

This paper first designed a theoretical model of market equilibrium, which shows that the impact of COVID-19 on food prices is linked to the impact difference on demand and supply in response to the COVID-19 crisis. Then we collected the representative prices data for four major food products (rice, wheat flour, pork and Chinese cabbages) from three provinces (Shandong as a producing base, Beijing as a consumption base and Hubei as the epicenter), and set up an iGARCH model.

(1) No significant impact on rice and wheat flour prices, (2) significantly positive impact on cabbages prices and (3) various impact on pork prices. Note that the outbreak and the severity of COVID-19 have different impacts. The outbreak itself may have a relatively large impact on pork and cabbage prices, which may result from social panic, while the magnitude of the impact of severity is relatively small, and some are negative, perhaps due to more reduced demand during the quarantine.

China always puts food security in its prior position of policy agenda and has been preparing for the worst scenario of the food security crisis. In the anti-COVID-19 campaign, China's local governments developed many measures to ensure food provision for each consumer. Hence, the impact of COVID-19 on food prices is minor. However, the outbreak of COVID-19 crisis could cause social panic in some scenarios where consumers may hoard food. Eventually, it may form a vicious cycle to push up food prices. This will be a challenging policy issue in crisis management for almost all governments.

This paper provides empirical evidence on the impact of COVID-19 on food prices in China. China has basically contained the COVID-19 in the whole country, and no major food crisis occurred during this process. The results will provide information on crisis management for other countries that are still under the COVID-19 crisis, and for future China and beyond.

Modelling methods can be helpful for understanding vibrations of beam structures including cracks, as well as for early detection of crack. This study aims to provide an analytical modelling approach for a cantilever beam considering a slant vertical crack along its height. However, previous uniform crack methods cannot be used for describing this case. The results from the analytical, finite element (FE) and experimental methods are compared to verify the vibration problem.

A massless rotational spring model is adopted to describe the crack. An extended method based on the calculation method for a uniform vertical edge crack is proposed to obtain the stiffness of the slant case. The beam is divided into a series of independent thin slices along the beam height. An Euler–Bernoulli beam model is applied to formulate each slice. The crack in each slice is considered as a uniform one. The transfer matrix method in the literature is used to obtain the beam vibration frequencies and mode shapes. Influences of crack location and sizes on the natural frequencies for the cantilever beam, as well as the mode shapes, are analysed. An established FE model and test results in the listed references are used to validate the developed method.

The numerical results show that the rotational stiffness at the cracked section and the natural frequencies of the beam decrease by increasing the crack sizes; the natural frequencies for the beam are greatly influenced by the crack sizes and location; the first natural frequency decreases with the distance from the beam fixed end to the crack location; the value of the first natural frequency reaches a minimum value when the crack is at the beam fixed end; the value of the second natural frequency is a minimum value when the crack is at the beam middle; and the value of the third natural frequency is a minimum value when the crack is at the beam free end. Saltation is observed in some mode shapes at the crack location, especially for larger crack depths; but, the mode shapes of the beam are slightly influenced by the vertical crack.

This study gives a useful analytical modelling method for free vibration analysis for the cantilever beam with a vertical crack, which can overcome the disadvantages of the previous uniform crack methods.

Carbon emissions trading is an effective instrument in reducing greenhouse gas emissions. There is a notable scarcity of comprehensive reviews on the modelling techniques within carbon trading research in construction.

This paper reviews 68 relevant articles published in 19 peer-reviewed journals using systematic search. Scientometric analysis and content analysis are undertaken.

Generally, China was the largest contributor to carbon trading research using quantitative models (representing 36% of the total articles). From the results, the modelling techniques identified were multi-objective grasshopper optimisation algorithm; system dynamics; interpretive structural modelling; multi-agent-based model; decision-support model; multi-objective chaotic sine cosine algorithm; optimised backpropagation neural network; sequential panel selection method; Granger causality test; and impulse response analysis. Moreover, the advantages and disadvantages of these techniques were identified. System dynamics was recommended as the most suitable modelling technique for carbon trading in construction.

This study is significant, and through this review paper, practitioners can easily be more familiar with the significant modelling techniques, and this will motivate them to better understand their uses.

Public-private partnership (PPP) projects for construction waste recycling have become the main approach to construction waste treatment in China. Risk sharing and income distribution of PPP projects play a vital role in achieving project success. This paper is aimed at building a practical and effective risk sharing and income distribution model to achieve win–win situation among different stakeholders, thereby providing a systematic framework for governments to promote construction waste recycling.

Stakeholders of construction waste recycling PPP projects were reclassified according to the stakeholder theory. Best-worst multi–criteria decision-making method and comprehensive fuzzy evaluation method (BWM–FCE) risk assessment model was constructed to optimize the risk assessment of core stakeholders in construction waste recycling PPP projects. Based on the proposed risk evaluation model for construction waste recycling PPP projects, the Shapley value income distribution model was modified in combination with capital investment, contribution and project participation to obtain a more equitable and reasonable income distribution system.

The income distribution model showed that PPP Project Companies gained more transaction benefits, which proved that PPP Project Companies played an important role in the actual operation of PPP projects. The policy change risk, investment and financing risk and income risk were the most important risks and key factors for project success. Therefore, it is of great significance to strengthen the management of PPP Project Companies, and in the process of PPP implementation, the government should focus on preventing the risk of policy changes, investment and financing risks and income risks.

The findings from this study have advanced the application methods of risk sharing and income distribution for PPP projects and further improved PPP project-related theories. It helps to promote and rationalize fairness in construction waste recycling PPP projects and to achieve mutual benefits and win–win situation in risk sharing. It has also provided a reference for resource management of construction waste and laid a solid foundation for long-term development of construction waste resources.

PPP mode is an effective tool for construction waste recycling. How to allocate risks and distribute benefits has become the most important issue of waste recycling PPP projects, and also the key to project success. The originality of this study resides in its provision of a holistic approach of risk allocation and benefit distribution on construction waste PPP projects in China as a developing country. Accordingly, this study adds its value by promoting resource development of construction waste, extending an innovative risk allocation and benefit distribution method in PPP projects, and providing a valuable reference for policymakers and private investors who are planning to invest in PPP projects in China.

The study uses machine learning techniques to cluster regional retail egg prices after 2000 in China. Furthermore, it combines machine learning results with econometric models to study determinants of cluster affiliation. Eggs are an inexpensiv, nutritious and sustainable animal food. Contextually, China is the largest country in the world in terms of both egg production and consumption. Regional clustering can help governments to imporve the precision of price policies and help producers make better investment decisions. The results are purely driven by data.

The study introduces dynamic time warping (DTW) algorithm which takes into account time series properties to analyze provincial egg prices in China. The results are compared with several other algorithms, such as TADPole. DTW is superior, though it is computationally expensive. After the clustering, a multinomial logit model is run to study the determinants of cluster affiliation.

The study identified three clusters. The first cluster including 12 provinces and the second cluster including 2 provinces are the main egg production provinces and their neighboring provinces in China. The third cluster is mainly egg importing regions. Clusters 1 and 2 have higher price volatility. The authors confirm that due to transaction costs, the importing areas may have less price volatility.

The machine learning techniques could help governments make more precise policies and help producers make better investment decisions.

This is the first paper to use machine learning techniques to cluster food prices. It also combines machine learning and econometric models to better study price dynamics.