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It is imperative to achieve sustainable growth in farmers' earnings to sustain poverty alleviation efforts and achieve rural revitalization goals. The authors investigated the nature of the non-linear relationship between farmers' e-commerce participation and income growth, analyzed the rationale behind this correlation and examined the moderating effect of digital finance on this relationship.

The authors conducted an empirical investigation using rural household data from the China Household Finance Survey and the regional digital finance index compiled by Peking University. The authors employed a fixed-effect model and a moderating effect model to identify the non-linear influences of e-commerce participation on farmers' income and to analyze the positive synergies of digital finance. The authors used identification and estimation techniques to mitigate the endogeneity problem, specifically employing heteroscedasticity-based instruments.

There is an inverted U-shaped relationship between e-commerce participation and farmers' income. Digital finance reduces the declining trend in the marginal effects of e-commerce and increases marginal values. Furthermore, the synergistic effect can promote the quality and efficiency of business activities by easing credit constraints, reducing risk aversion and stimulating innovative activities, which in turn can lead to sustained revenue growth.

Few studies have focused on the non-linear relationship between e-commerce and farmers' income. This implies that achieving sustained income growth using e-commerce alone is difficult. The synergy between e-commerce and digital finance is a feasible path for achieving this goal.

It has been noted that the spin-valve sensor exhibits lower sensitivity with higher temperature because of the variation of GMR ratio, which could lead to the measurement error in applications where working temperature changes largely over seasons or times. This paper aims to investigate and compensate the temperature effect of the spin-valve sensor.

A spin-valve sensor is fabricated based on microelectronic process, and its temperature relevant properties are investigated, in which the transfer curves are acquired within a temperature range of −50°C to 125°C with a Helmholtz coil and temperature chamber.

It is found that the sensitivity of spin-valve sensor decreases with temperature linearly, where the temperature coefficient is calculated at −0.25 %/°C. The relationship between sensitivity of spin-valve sensor and temperature is well-modeled.

The temperature drift model of the spin-valve sensor’s sensitivity is highly correlated with tested results, which could be used to compensate the temperature influence on the sensor output. A self-compensation sensor system is proposed and built based on the expression modeled for the temperature dependence of the sensor, which exhibits a great improvement on temperature stability.

In the process of continuous casting and rolling of steel plate, due to the influence of rolling equipment and process, there are scratches, inclusions, patches, scabs and pitted surfaces on the surface of steel plate, which will not only affect the corrosion resistance, wear resistance and fatigue strength of steel plate but also may cause production accidents. Therefore, the detection of steel plate surface defect must be strengthened to ensure the production quality of steel plate and the smooth development of industrial construction.

(1) A steel plate surface defect detection technology based on small datasets is proposed, which can detect multiple surface defects and fill in the blank of scab defect detection. (2) A detection system based on intelligent recognition technology is built. The steel plate images are collected by the front-end monitoring device, then transmitted to the back-end monitoring center and processed by the embedded intelligent algorithms. (3) In order to reduce the impact of external light on the image, an improved Multi-Scale Retinex (MSR) enhancement algorithm based on adaptive weight calculation is proposed, which lays the foundation for subsequent object segmentation and feature extraction. (4) According to the different factors such as the cause and shape, the texture and shape features are combined to classify different defects on the steel plate surface. The defect classification model is constructed and the classification results are recorded and stored, which has certain application value in the field of steel plate surface defect detection. (5) The practicability and effectiveness of the proposed method are verified by comparison with other methods, and the field running tests are conducted based on the equipment commissioning field of China Heavy Machinery Institute.

When applied to small dataset, the precision of the proposed method is 94.5% and the time is 23.7 ms. In order to compare with deep learning technology, after expanding the image dataset, the precision and detection time of this paper are 0.948 and 24.2 ms, respectively. The proposed method is superior to other traditional image processing and deep learning methods. And the field recognition precision is 91.7%.

In brief, the steel plate surface defect detection technology based on computer vision is effective, but the previous attempts and methods are not comprehensive and the accuracy and detection speed need to be improved. Therefore, a more practical and comprehensive technology is developed in this paper. The main contributions are as follows: (1) A steel plate surface defect detection technology based on small datasets is proposed, which can detect multiple surface defects and fill in the blank of scab defect detection. (2) A detection system based on intelligent recognition technology is built. The steel plate images are collected by the front-end monitoring device, then transmitted to the back-end monitoring center and processed by the embedded intelligent algorithms. (3) In order to reduce the impact of external light on the image, an improved MSR enhancement algorithm based on adaptive weight calculation is proposed, which lays the foundation for subsequent object segmentation and feature extraction. (4) According to the different factors such as the cause and shape, the texture and shape features are combined to classify different defects on the steel plate surface. The defect classification model is constructed and the classification results are recorded and stored, which has certain application value in the field of steel plate surface defect detection. (5) The practicability and effectiveness of the proposed method are verified by comparison with other methods, and the field running tests are conducted based on the equipment commissioning field of China Heavy Machinery Institute.

Despite recent organizational behavior studies have witnessed considerable progress in abusive supervision research; some demerits for both theory and methodology still remain in the past years. To clarify the current state of knowledge in the field, this study aims to analyze the current state of theories and methods on abusive supervision and provides a detailed future research agenda.

This paper conducted a literature review for both theory and methodology of the abusive supervision research using a content analysis of 134 publications.

For the theory part, this paper summarized the theories that had been applied to explain the relationship between abusive supervision and its consequences as well as antecedents. For the methodology part, this paper outlined some critical issues regarding country of origin, research design, measurement, analysis strategy and also summarized with a discussion of the relationship between methodological issues and article impact. Finally, this paper concluded by presenting an agenda for future abusive supervision research regarding both theory and methodology.

First, this paper summarizes the main theories, antecedents and consequences often used in abusive supervision research to allow scholars to carry out theoretically driven research investigating abusive supervision in the future. Second, through a content analysis of the methods sections of abusive supervision research in the samples (i.e. country of origin, research design, measurement and analytical procedures), this paper identified the potential reasons underlying the inconsistency in the conclusions of abusive supervision research and provide some guidance for future empirical studies. Third, based on the qualitative review, this paper provides an agenda for future research investigating abusive supervision by developing a content-specific theoretical framework to benchmark abusive supervision research against other research related to leadership and offers an accurate response to scholars’ criticisms of abusive supervision research.

The purpose of this paper is to systematically study the dynamic contact stress, frictional heat and temperature field of femoral head-on-acetabular cup contact pairs in a gait cycle.

In this paper, four common femoral head-on-acetabular cup contact pairs are used as the research objects, mathematical calculations and finite element simulations are adopted. The contact model of hip joint head and acetabular cup was established by finite element simulation to analyze the stress and temperature distribution of the contact interface.

The results show that the contact stress of the head-on-cup interface is inversely proportional to the contact area; high contact stress directly leads to greater frictional heat. However, hip joints with metal-on-polyethylene or ceramic-on-polyethylene paired interfaces have lower frictional heat and show a significant temperature rise in one gait cycle, which may be related to the material properties of the acetabular cup.

Previous studies about calculating the interface frictional heat always ignore the dynamic change process in the contact load and the contact area. This study considered the dynamic changes of the contact stress and area of the femoral head-on-acetabular cup interface, and four common contact pairs were systematically analyzed.

A new method of hollowing rapid prototype models based on STL models and their cross‐sectional contours is presented to meet the demands of hollowed prototypes in casting and rapid prototype manufacturing. Offsetting along the Z‐axis and cross‐sectional contour offsetting are employed to perform the hollowing operation. The process performs two‐dimensional Boolean operations on the polygons made by the offset contours of cross‐sectional contours instead of three‐dimensional offsetting of the STL models. This hollowing operation is especially suitable for hollowing STL models with free‐form surfaces. Detailed algorithms are described to generate the correct offset contours of an STL model. Adopting this method, the hollowing process is dramatically simplified and becomes more efficient. This method has been verified by practical case studies, and it is proved that this simplified hollowing operation can reduce the prototype build time and cost.

This study is conducted to determine the factors that affect profitability in Chinese listed companies (by using financial ratios). Four independent variables liquidity, intangible assets, working capital and company leverage were empirically tested for their relationships with profitability besides two control variables which are firm size and company efficiency.

This study used secondary data extracted manually from the annual reports of non-financial Chinese listed companies on the Shanghai stock exchange (http://www.szse.cn/); the data set covers 100 companies during the period of 2017–2019, and a random selection method was used in order to achieve credibility and fairness as much as possible.

The findings show firm size, working capital and intangible assets have positive and significant relationships with profitability [return on assets (ROA) and earnings per share (EPS)]. Positive working capital is important to lower the cost of capital and improve companies' profitability. Intangible assets are also an essential source to improve profitability due to their low costs. In addition, the findings display a negative and strong relationship between liquidity and profitability, meaning that companies suffer low profit due to inefficient use of liquid items. Interestingly, leverage, which is measured by debt ratio and leverage ratio, shows mixed results; debt ratio shows a positive and strong association with ROA but not with EPS; while leverage ratio displays a strong but negative association with ROA but not with EPS. These results confirm the inverted U-shape relationship between leverage and profitability, which depends on the balance between benefit and cost of debt.

Profitability is also important for employees and society where business organization provides sustainability and stability for both of them. Employees can then significantly contribute to achieve higher firm's profitability by efficiently using firm's resources.

This study differs than previous studies in number of aspects: First, this study focuses on financial ratios to explain profitability in Chinese companies. This study provides empirical results about the factors connected to profitability and help stakeholders to make their right decisions. Second, it examines the impact of four independent factors and two control variables that some of them are new in Chinese context such as intangible assets. Third previous studies focus on financial industry such as banks; however, this study focuses on non-financial industry.

With a fast-growing Muslim population and consumer income, the demand for halal products by Chinese Muslims has expanded strongly. However, literature addressing Chinese Muslims’ consumption is limited, and their demand for halal products is little understood. This study aims to investigate what affects Chinese Muslims’ demand for halal products, with a focus on halal personal care products.

A survey of 500 respondents was conducted to collect cross-sectional data in northwest China. Data were processed and analysed with a logit model.

Apart from faithfulness, reliability of recommendations, product price, product availability and halal authenticity are most important determinants influencing the purchase of halal products by Chinese Muslims.

In this study, the focus is only on Muslims from China’s Northwest. Due to various constraints, the cluster and convenience sampling methods are used.

The findings are invaluable for governments and industry bodies to form policies to better meet the burgeoning demand for halal products by Chinese Muslims. They are also very invaluable for producers and exporters who intend to penetrate the halal market in non-Muslim-dominant countries like China.

Studies on understanding the needs of Muslims in non-Muslim countries are limited. Given the sheer size of the Muslim population in China, understanding their demand for halal products and influential determinants concerning such demand adds to the literature and helps the industry to better serve and capitalise on the growing market.

The purpose of this paper is to investigate the impact of strategic collaboration (SC) on sustainable supply chain management (SSCM), considering the mediating role of internal knowledge sharing (IKS) and external knowledge sharing (EKS).

The study population consisted of experts associated with the supply chain in the automotive, food, clothing, pharmaceuticals and chemicals industries. After reviewing the literature, a conceptual framework was developed and applied using a structural equation modeling approach. In this study, samples with 271 observations were collected from manufacturing and servicing companies in Iran.

The results showed that SC in the supply chain has a positive impact on the IKS and EKS and SSCM. IKS and EKS have a positive impact on SSCM. Also, the results showed that IKS and EKS fully mediate in the relationship between SC and SSCM.

This study has been done in the context of Iran, so caution should be taken to generalize the results.

The findings of the study contribute to the knowledge of the managers and policy makers in achieving SSCM. The results provide the important environmental and social concepts regarding the sustainability of supply chain using SC and IKS and EKS.

Recent empirical findings on the relationship between internationalization and firm performance (I–P) suggest a significant role of firm's context. Extending this line of argument, the authors study the effect of internationalization on firm's performance for emerging market firms from knowledge-intensive industries, taking into account the firm's motive of internationalization and host country’s location-based advantages.

The authors link host country-specific advantages (CSAs) with firm-specific advantages (FSAs) to identify three distinct settings of internationalization for emerging economy firms – (1) asset-exploitative internationalization in developing or least developed countries, (2) asset-exploitative internationalization in developed countries and (3) strategic asset-seeking internationalization. The authors test this study’s hypotheses on a sample of 415 Indian firms from knowledge-intensive industries.

The authors find that firm's performance upon internationalization is non-linear in each of the three different settings. The nature of the non-linear relationship depends upon location-based advantages of the host country and the motive of internationalization.

The motive of internationalization and the location-based advantages sought during internationalization are unique for emerging economy firms. Hence, the study extends understanding of the I–P linkage in an emerging economy context.