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The purpose of this paper is to investigate how China's rural public pension affects farmers' formal borrowing, which has always been rationed.

This paper uses a difference-in-difference (DID) estimation to evaluate the effect of the implementation of the New Rural Pension Scheme (NRPS) at the end of 2009 on farmers' formal borrowing.

The results show that the NRPS significantly reduces farmers' formal borrowing from rural credit cooperatives (RCCs). The effect is significant among the elderly, eastern China and high-income groups.

This study contributes to the literature by identifying another potential reason for rural formal credit shortage. Policymakers and rural formal financial institutions should consider the demand side problem of lending.

China is the world's largest consumer of pesticides. To increase the use efficiency and achieve more sustainable and environmentally friendly use of pesticides in China, it is crucial to understand why Chinese farmers use such a large amount of pesticides.

The relationship between farm size and pesticide use was investigated by using national household-level panel data from 1995 to 2016.

Farms that are small and fragmented lead to the use of large amounts of pesticides in China. For a given crop type, three factors contribute to a negative relationship between farm size and pesticide use: the spillover effect from the use of pesticides by other farmers in the same village, the level of mechanization and the management ability of farmers. The first two factors play important roles in the cultivation of grain crops, while the last factor is the main reason why farmers with larger plots of land use fewer pesticides in the cultivation of vegetables. In addition, the effect of agricultural machinery services on reducing the use of pesticides is currently limited, and the service system in China is still insufficient, which has been pointed out that it is also due to the prevalence of small and fragmented farms.

The authors investigate and compare the farm size–pesticide use relationship in both grain and cash crop production. Moreover, the authors systematically explore and explain how farm size is related to a reduction in pesticide use in the cultivation of grain crops and cash crops. These results can help to better understand the role of land scale in pesticide use, lay a foundation for the formulation of policies to reduce pesticide use and provide valuable knowledge about pesticide use for other developing countries around the world.

The purpose of this paper is to examine the causal relationship between Chinese housing and stock markets. The authors discuss the three transmission mechanisms between the two markets: wealth effect, modern portfolio theory and credit-price effect. Moreover, the authors focus on the effects of inflation on the relationship between the two markets.

This paper uses wavelet analysis to test the housing and stock markets relationship both in the frequency domain and time domain.

The empirical results indicate that housing prices have a positive effect on stock prices, and these have the same effect on housing prices. Moreover, this positive effect means that stock prices have a wealth effect on housing prices and these have a credit-price effect on stock prices.

These results provide information to financial institutions and individual investors in China to assist them in constructing investment portfolios within these two asset markets.

The authors first use wavelet analysis to analyze Chinese housing and stock markets and to provide information both on the frequency domain and time domain. Moreover, the authors take the inflation factor as a control variable in the causal relationship between the housing and stock markets.

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.

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.

Two corrosion inhibitors for closed cooling water systems, nitrite-based and mixture of nitrite and molybdate corrosion inhibitor, are often compared to each other. This study aims to optimize these two inhibitors in terms of concentration and pH for carbon steel protection, with insights into the double layer structure on surface and its impact on corrosion inhibition.

Electrochemical analysis including electrochemical impedance spectroscopy and potentiodynamic test are carried out for quick assessment of corrosion inhibition efficiency and optimization, which is confirmed by immersion test and microscopic analysis. The electronic properties of the surface film are analyzed through Mott–Schottky method which provides new insights into the inhibition mechanism and the role of each component in mixture inhibitor.

Mixture of nitrite and molybdate is shown to present higher inhibition efficiency, owning to the double layer structure. Nitrite alone can form a protective surface film, whereas molybdate leads to an n-type semiconductive film with lower donor density, hence giving rise to a better inhibition effect.

Surface after inhibitor treatment has been carefully characterized to the microscopic scale, implying the effect of micro-structure, chemical composition and electronic properties on the corrosion resistance. Inorganic corrosion inhibitors can be tuned to provide higher efficiency by careful design of surface film structure and composition.

Almost every study on corrosion inhibitor applies such method for quick assessment of corrosion inhibition effect. Mott–Schottky test is one of electrochemical methods that reveals the electronic properties of the surface film. Previous works have studied the surface layer mainly through X-ray photoelectron spectroscopy. This study provides another insight into the surface film treated by nitrite and molybdate through Mott–Schottky analysis, and relates this structure to the corrosion inhibition effect based on multiple analysis including electrochemistry, microscopic characterization, thermodynamics and interface chemistry.

The purpose of the paper is to propose a new optimization algorithm to realize a synchronous optimization of sensor array and classifier, to improve the performance of E-nose in the detection of wound infection. When an electronic nose (E-nose) is used to detect the wound infection, sensor array’s optimization and parameters’ setting of classifier have a strong impact on the classification accuracy.

An enhanced quantum-behaved particle swarm optimization based on genetic algorithm, genetic quantum-behaved particle swarm optimization (G-QPSO), is proposed to realize a synchronous optimization of sensor array and classifier. The importance-factor (I-F) method is used to weight the sensors of E-nose by its degree of importance in classification. Both radical basis function network and support vector machine are used for classification.

The classification accuracy of E-nose is the highest when the weighting coefficients of the I-F method and classifier’s parameters are optimized by G-QPSO. All results make it clear that the proposed method is an ideal optimization method of E-nose in the detection of wound infection.

To make the proposed optimization method more effective, the key point of further research is to enhance the classifier of E-nose.

In this paper, E-nose is used to distinguish the class of wound infection; meanwhile, G-QPSO is used to realize a synchronous optimization of sensor array and classifier of E-nose. These are all important for E-nose to realize its clinical application in wound monitoring.

The innovative concept improves the performance of E-nose in wound monitoring and paves the way for the clinical detection of E-nose.

Green supply chain management (GSCM) and the circular economy (CE) overlap but also differ. The purpose of this paper is to clarify linkages between these two concepts. It identifies mutual theory applications used to study GSCM and CE.

A systematic literature review is conducted to identify theories from GSCM and CE studies. A critical analysis explores the theories that can provide mutual applications between GSCM and CE fields. Propositions are developed.

In all, 12 theories are applied in both GSCM and CE studies. Several theories are only applied in GSCM studies, but can help to advance CE study. These theories include complexity, transaction cost economics, agency, and information theories. Each of the eight theories only applied to CE can potentially advance GSCM study.

The findings contribute to further theory development for both GSCM and CE study. A methodological review can advance theoretical development and cross-pollination in both fields.

This work is the first study to explicitly explore linkages of GSCM and CE from a theoretical perspective.

The Chinese civilization is an important part of the history of mankind. The purpose of this paper is to show that there are project management lessons to be learned from Chinese history, including that relating to the management of the building process in ancient China.

Through a review of the literature, this paper discusses the key management and economic practices in the building process of ancient China and highlights these practices from an important document, the Yingzao Fashi or (“Treatise on Architectural Methods”), that was compared with the modern‐day project management framework.

This paper explains the official systems instituted for public projects; the management of labour, design and planning of construction works; quantity surveying practices; the use, control and recycling of building materials; and inspection of building elements in ancient China.

The study suggests that lessons in the principles of construction project management in ancient China bear many similarities with the nine areas of modern‐day project management body of knowledge relating to integration, scope, time, cost, quality, human resource, communications, risk, and procurement management. An area for future research would be to compare the Yingzao Fashi with modern‐day codes of practice for building works to determine which of its “ancient” provisions relating to quality management are still relevant today.

It was found that much emphasis was placed by the ancient Chinese on the quality aspects of prominent building projects. This is one facet from which modern‐day project managers and clients can draw lessons.

The purpose of this study was to research how the reassembly (remanufacturing assembly) achieves a quality that is not lower than original production with different precision remanufactured parts based on the integration of mechanics, mathematics (measurement uncertainty) and management (optional classification). Remanufactured product quality is the soul of the remanufacturing project.

First, this paper studies the recycled parts features and reassembly features. Then, we build the mathematical sub-model with remanufactured parts and dimensional precision, which is proven that optional classification can effectively improve the reassembly accuracy mathematically. The optimization model of optional classification for reassembly is proposed under the constraint of a dimensional chain, and the solutions are studied based on particle swarm optimization. Finally, this method is applied in a remanufacturing enterprise and achieves good results.

The method can reduce the cost of quality loss and improve the quality of remanufactured products.

It provides a new solution and idea for reassembly with different precision remanufactured parts and promotes the healthy development of reverse logistics with a high level of customer satisfaction. This method can maximize the use of different levels of quality remanufactured parts and improve reassembly accuracy by mathematical proofs and examples.