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Previous studies have rarely integrated the financing modes of a capital-constrained manufacturer with the choices of online sales strategies. To address this gap, the authors study how a manufacturer selects optimal financing modes under different sales strategies in three dual-channel supply chains.

This paper considers three sales strategies, namely, combining a traditional retailer channel with one of the direct selling, reselling and agency selling channels, and two common financing modes, namely, bank financing and retailer financing. The authors obtain equilibrium outcomes of the manufacturer and traditional retailer and then provide the conditions for them to select optimal financing modes under three sales strategies.

The results indicate that the manufacturer’s financing decisions rely on the initial capital and interest rates, and the manufacturer selects retailer financing only if the initial capital is relatively larger. In terms of financing mode options, the retailer financing mode is more beneficial for the manufacturer under the three sales strategies. From the perspective of sales strategies, the direct selling model is more beneficial. In addition, the higher the consumer acceptance of the online channel, the more profits the manufacturer obtains.

This paper provides suggestions on how the capital-constrained manufacturer chooses financing modes and sales strategies.

This paper integrates the financing mode and different sales strategies to investigate the manufacturer’s optimal operational decisions. These sales strategies allow us to investigate the manufacturer’s optimal financing modes in the presence of both different financing modes and sales strategies.

Integrating artificial intelligence and quantitative investment has given birth to various agricultural futures price prediction models suitable for nonlinear and non-stationary data. However, traditional models have limitations in testing the spatial transmission relationship in time series, and the actual prediction effect is restricted by the inability to obtain the prices of other variable factors in the future.

To explore the impact of spatiotemporal factors on agricultural prices and achieve the best prediction effect, the authors innovatively propose a price prediction method for China's soybean and palm oil futures prices. First, an improved Granger Causality Test was adopted to explore the spatial transmission relationship in the data; second, the Seasonal and Trend decomposition using Loess model (STL) was employed to decompose the price; then, the Apriori algorithm was applied to test the time spillover effect between data, and CRITIC was used to extract essential features; finally, the N-Beats model was selected as the prediction model for futures prices.

Using the Apriori and STL algorithms, the authors found a spillover effect in agricultural prices, and past trends and seasonal data will impact future prices. Using the improved Granger causality test method to analyze the unidirectional causality relationship between the prices, the authors obtained a spatial effect among the agricultural product prices. By comparison, the N-Beats model based on the spatiotemporal factors shows excellent prediction effects on different prices.

This paper addressed the problem that traditional models can only predict the current prices of different agricultural products on the same date, and traditional spatial models cannot test the characteristics of time series. This result is beneficial to the sustainable development of agriculture and provides necessary numerical and technical support to ensure national agricultural security.

In today's complex and rapidly changing business environment, cross-boundary growth is increasingly critical to the survival or even success of organizations. The purpose of this study is to examine the forming mechanism of firm’s cross-boundary growth by integrating the two important antecedent factors of performance pressure and managerial discretion into a united framework and theoretically analyze the direct role of performance pressure on firm’s cross-boundary growth as well as reveal the moderating role of managerial discretion. Also, the authors select listed manufacturing companies in China as samples to empirically test the research hypotheses.

The authors design a multiple regression model to perform empirical analysis by using a panel of 4,002 year-observations in 1,334 listed manufacturing companies between 2013 and 2016. The sample data sources mainly come from the Wind Database, which is mainland China's leading financial database and software services provider. The hypotheses proposed are tested by adopting a panel data set of the listed manufacturing companies of China.

Empirical results show that performance pressure has a positive effect on the cross-industry growth and cross-domestic regional growth but a negative effect on the cross-international regional growth, and managerial discretion has a different moderating effect. Specifically, capital intensity strengthens the positive effect of performance pressure on cross-industry growth but weakens the negative effect of performance pressure on cross-international regional growth. State ownership enhances the positive effect of performance pressure on cross-domestic regional growth but decreases the negative effect of performance pressure on cross-international regional growth. CEO duality increases the negative impact of performance pressure on cross-international regional growth.

This study provides several implications for top executives, including how to dialectically consider the double-edged effect of performance pressure on cross-boundary growth of firms, create an appropriate environments of managerial discretion and design the types of cross-boundary growth strategies that top executives can follow in the volatility, uncertainty, complexity and ambiguity era.

Although the relevant literature highlights the importance of performance pressure, it has not been related to the cross-boundary growth of firms. This paper makes an incremental contribution to the literature on the forming mechanisms of firm’s cross-boundary growth by providing an important perspective of performance pressure to firm growth determinants and taking into account the moderating role of managerial discretion.

The purpose of the study is to investigate the financing channels and carbon emission abatement preferences of supply chain members, and further examine the optimal contract design of the retailer.

This paper develops a low-carbon supply chain composed of one retailer and one manufacturer, in which the retailer provides trade credit to the manufacturer. Considering the cap-and-trade regulation, the manufacturer with uncertain yield makes decision on whether to invest in emission abatement. There are bank loan and trade credit to finance production for the manufacturer and green credit to finance emission abatement investment. Meanwhile, the retailer may provide the manufacturer with three kinds of contracts to improve emission abatement efficiency, namely, revenue sharing, cost sharing or both sharing.

The results show that the retailer prefers to offer financing service at lower interest rate, but trade (and green) credit financing is always optimal for manufacturer and supply chain. The investment in emission abatement is value-added to all players. The sharing contracts offered by the retailer at lower sharing ratios can realize Pareto improvement of the system regardless of the financing scheme. However, comparing with the revenue or cost sharing contract, the existence of optimal sharing ratios makes the both sharing contract more favorable to the retailer.

The findings provide guidance for the emission-dependent manufacturer in financing and emission abatement decisions, as well as recommendations for the retailer to offer loan service and sharing contract.

This paper integrates green credit into bank loan or trade credit to analyze the financing decision of the manufacturer with uncertain yield and further considers the influence of three kinds of sharing contracts introduced by the retailer on improving operational performance.

This study examines the effect of local government debt (LGD) on corporate earnings management using 25,624 firm-year observations from 2007 to 2019.

Pooled ordinary least squares (OLS) regression is used to examine the impact of LGD on earnings management. A difference-in-differences (DID) method is also used to alleviate potential endogeneity.

Results show that LGD motivates firms to increase earnings management, especially income-decreasing earnings management. Findings are robust to DID method and robustness tests. Heterogeneity analyses show that the positive effect of LGD on earnings management is pronounced in firms with political dependence and moderated by external governance mechanisms. Further discussions indicate that tax enforcement is an underlying channel for LGD to affect earnings management. Firms engage in downward real earnings management by increasing their abnormal discretionary expenditures and higher LGD leads to a greater book-tax difference in those firms that manipulate income-decreasing earnings management.

This study contributes towards examining the political costs hypothesis, the microeconomic effects of LGD and the determinants of earnings management.

Numerical literature shows that agricultural insurance can affect pesticide investments, but few of them are devoted to explain how agricultural insurance affects farmers’ selection on green or traditional pesticides. This paper aims to develop a theoretical model about how agricultural insurance influences on green pesticides selections and tests our conclusions by using the data from China land economic survey (CLES) from 2020 to 2021.

We employ probit model to capture the effects of agricultural insurance on green pesticides adoption.

We indicate that green pesticides have a stronger effect on stabilizing yield and increasing income than traditional pesticides, but there are still risks disturbing farmers’ decisions on green pesticides usage. By providing premium subsidies after the farmers are affected by natural risk, agricultural insurance improves the farmers’ expected income and encourages farmers to use green pesticides. Further, we further confirm these conclusions by considering different scenarios such as climate risks, farmers’ entrepreneurship and credit constraints. We find that the effects are more salient if croplands are under higher natural risks and, farmers are equipped with entrepreneurship and formal credit. This paper implies that the agricultural insurance decoupled with green technologies also have salient positive effects on agricultural pollution control.

The potential contributions of this paper can be outlined in three aspects in detail. Firstly, this paper aims to revel the effects of agricultural insurance on pesticide selection by structuring a general theoretical model. By using the CLES data from 2020 to 2021, we confirm that agricultural insurance increases the probability for adopting green pesticides. Secondly, this paper discusses the effects of farmers’ characteristics on the results and finds that if farmers have entrepreneurship, the effects of agricultural insurance on green pesticide usage will be more salient. Thirdly, it uncovers some practices in China, which will supply experiences for other developing countries. For example, this paper further demonstrates that “insurance + credit” plan the present Chinese government carried out will be an important measure for strengthening effects of agricultural insurance on green pesticides usage. Moreover, it shows that decouple agricultural policies will also guide farmers to use green technologies eventually if the technologies are reliable and farmers can afford.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

Retail investors are prone to be affected by information dissemination in social media with the rapid development of Web 2.0. The purpose of this study is to recognize the factors that may impact users' retweet behavior, namely information dissemination in the online financial community, through machine learning techniques.

This paper crawled data from the Chinese online financial community (Xueqiu.com) and extracted author-related, content-related, situation-related, stock-related and stock market-related features from the dataset. The best information dissemination prediction model based on these features was determined by evaluating five classifiers with various performance metrics, and the predictability of different feature groups was tested.

Five prevalent classifiers were evaluated with various performance metrics and the random forest classifier was proven to be the best retweet prediction model in the authors’ experiments. Moreover, the predictability of author-related, content-related and market-related features was illustrated to be relatively better than that of the other two feature groups. Several particularly important features, such as the author's followers and the rise and fall of the stock index, were recognized in this paper at last.

This study contributes to in-depth research on information dissemination in the financial domain. The findings of this study have important practical implications for government regulators to supervise public opinion in the financial market.

This paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of information sharing on optimal decisions and propose a coordination mechanism to encourage supply chain members to share information.

The two-echelon dual-channel FAP supply chain includes a manufacturer and a retailer. By using the Stackelberg game theory and the backward induction method, the optimal decisions are obtained under information symmetry and asymmetry and the coordination contract is designed.

The results show that supply chain members should comprehensively evaluate the specific situation of product attributes, coefficient of freshness-keeping cost and network operating costs to make decisions. Asymmetric information can exacerbate the deviation of optimal decisions among supply chain members and information sharing is always beneficial to manufacturers but not to retailers. The improved revenue-sharing and cost-sharing contract is an effective coordination mechanism.

The conclusions can provide theoretical guidance for supply chain managers to deal with information asymmetry and improve the competitiveness of the supply chain.

This paper combines the three characteristics that are most closely related to the reality of supply chains, including horizontal and vertical competition of different channels, the perishable characteristics of FAPs and the uncertainty generated by asymmetric demand information.

The purpose of this study is to examine the relationship between the corporate social responsibility (CSR) performance of job-hopping executives at their former and subsequent firms.

We conduct regression analyses using a sample of firms listed on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2020 to examine whether CSR performance is similar from one firm to the next as executives switch jobs.

We find a positive relationship between the CSR performance of former and subsequent firms under job-hopping executives. This relationship is the strongest in the year of the job switch; it weakens in the second year and eventually disappears in the third year. In addition, we show that this relationship benefits different CSR stakeholder groups and is contingent on executive and subsequent firm attributes and job-hopping characteristics. Furthermore, we demonstrate that firms that hire a new chief executive officer from a firm with a strong track record in CSR, the new firm experiences a significant surge in CSR performance compared with firms that do not experience such a shock.

This study has implications for executive hiring decisions.

This study extends the understanding of CSR determinants through the lens of inter-organisational ties associated with job-hopping executives.