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The Chinese Government relies heavily on increasing farming scale to address the new challenges facing China’s agricultural development. A basket of polices targeted at increasing farming scale has been issued in recent years thereby resulting to debates over large-scale farming in China. The purpose of this paper is to summarize and highlight the debate over China’s on-going large-scale farming.

This paper contributes to the policy debates over large-scale farming in China by reviewing the existing literature on the positive and negative impacts of large-scale farming on agricultural development, land productivity, and national food security. This paper overviews the different ideas and findings of studies associated with the topic.

The mainstream literature supports the idea that large-scale farming will address the challenges facing China’s agricultural development, while others argue that it crowds out the benefits of small farmers, and raises concerns over inequalities of resources allocation and income distribution, and undermines social stability. While proponents argue that large-scale farming may lead to rise in land productivity, opponents argue that it may result into decrease in land productivity and national grain output.

This paper is a policy review based on existing works. It organizes the different debates over large-scale farming in China, and highlights the key arguments put forward.

The anti-friction and anti-wear properties of WS₂@GO composites on paraffin liquid were investigated with a four-ball tribometer.

A series of graphene oxide (GO) nano hybrid composites decorated with tungsten disulfide (WS₂) were prepared in-suit by hydrothermal strategy.

The results showed that compared to the virgin oil, friction coefficient and diameter of wear scare of lubricant oil containing W/G = 1:1 hybrid composite was reduced by 42.7% and 31.6%, respectively. At the microscopic, the excellent lubrication performance resulted from the tribo-chemical reaction on the sliding interface, which promotes the formation of tribo-film with a thickness of 8 nm. The carbonization compound, WO₃ and Fe₂O₃ in the tribo-film results from the tribo-chemical reactions at the sliding interface, which can improve the stability and strength of tribo-film. Thereby the metal surface was further protected from friction and wear.

A series of WS₂@GO composites were prepared in-suit by a hydrothermal strategy, and the tribo-film was analyzed by the transmission electron microscope and X-ray photoelectron spectrometer.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2024-0397

Livestream selling is becoming an increasingly popular practice adopted by online retailers to develop a consumer-centric supply chain (CCSC). It improves consumer experience by integrating chat, watch and purchase functions, while also altering consumer behaviors by increasing impulse purchases. Online retailers’ responses to this change potentially impact suppliers’ operational processes. This study aims to empirically examine how livestream selling affects suppliers’ operational performance in terms of lead time and how suppliers’ product variety and order fulfillment capabilities moderate such an impact.

Using data from a leading online retailer in China, the authors use a least squares model with fixed effects to test the relationships. Both the two-stage instrumental variable model and the two-stage Heckman model are used to address potential endogeneity in this study.

The findings show that retailers’ usage of livestream selling can increase suppliers’ lead time. Furthermore, the negative impact is enhanced when a supplier has a higher level of product variety or a weaker order fulfillment capability.

This study explores how livestream selling alters consumer behavior, adversely affecting upstream suppliers’ operational performance. It underscores the need for a CCSC approach across all tiers, not just those closest to consumers. To achieve this, the research suggests that suppliers must align their capabilities with retailers’ consumer-centric practices to develop a CCSC, particularly by improving order fulfillment capability and cautiously expanding their product variety in livestream selling. The research further highlights the importance for retailers to consider changes in lead time to enhance the application of traditional inventory theory in the context of livestream selling.

As social networks have developed to be a ubiquitous platform of public opinion spreading, it becomes more and more crucial for maintaining social security and stability by accurately predicting various trends of public opinion dissemination in social networks. Considering the fact that the dissemination of online public opinion is a dynamic process full of uncertainty and complexity, this study establishes a novel conformable fractional discrete grey model with linear time-varying parameters, namely the CFTDGM(1,1) model, for more accurate prediction of online public opinion trends.

First, the conformable fractional accumulation and difference operators are employed to build the CFTDGM(1,1) model for enhancing the traditional integer-order discrete grey model with linear time-varying parameters. Then, to improve forecasting accuracy, a base value correction term is introduced to optimize the iterative base value of the CFTDGM(1,1) model. Next, the differential evolution algorithm is selected to determine the optimal order of the proposed model through a comparison with the whale optimization algorithm and the particle swarm optimization algorithm. The least squares method is utilized to estimate the parameter values of the CFTDGM(1,1) model. In addition, the effectiveness of the CFTDGM(1,1) model is tested through a public opinion event about “IG team winning the championship”. Finally, we conduct empirical analysis on two hot online public opinion events regarding “Chengdu toddler mauled by Rottweiler” and “Mayday band suspected of lip-syncing,” to further assess the prediction ability and applicability of the CFTDGM(1,1) model by comparison with seven other existing grey models.

The test case and empirical analysis on two recent hot events reveal that the CFTDGM(1,1) model outperforms most of the existing grey models in terms of prediction performance. Therefore, the CFTDGM(1,1) model is chosen to forecast the development trends of these two hot events. The prediction results indicate that public attention to both events will decline slowly over the next three days.

A conformable fractional discrete grey model is proposed with the help of conformable fractional operators and a base value correction term to improve the traditional discrete grey model. The test case and empirical analysis on two recent hot events indicate that this novel model has higher accuracy and feasibility in online public opinion trend prediction.