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Currently, China’s economy is in the critical phase of transforming economic development patterns and replacing old growth drivers with new ones. Whether it can successfully overcome the “middle-income trap” has become a significant issue attracting wide attention.

Driven by underlying digital technologies such as artificial intelligence, blockchain, cloud computing and big data, the fourth industrial revolution featuring the booming digital economy has provided significant opportunities for China’s economy to “overtake” and overcome the “middle-income trap”. The transformation of economic development pattern, the optimization of industrial structure, and the change of growth drivers, brought by the deep integration of digital and real economies are the keys to leaping over the “middle-income trap”.

From the supply side, the digital economy can improve the quality and efficiency of the supply side and promote the supply-side structural reform and economic growth from the following three aspects: First, promote the quality, efficiency and diversification of the supply system; second, promote networking, opening-up and synergy in the innovation system and third, promote the socialization, modularization and flexibility of production pattern. From the demand side, the digital economy can boost the new drivers of the “troika” of economic growth consisting of consumption, exports and investment by changing the market investment direction, promoting consumption upgrade and fostering export strengths. However, once these two attributes interact with each other, especially when data is combined with capital, the most adhesive factor in the market economy, a series of new social relations will then be produced based on the technical attribute, resulting in significant adjustments in social relations, involving both positive and negative externalities.

To overcome the “middle-income trap”, it is necessary to adapt to the laws of economic evolution and promote a fundamental change in economic growth drivers; boost the high-quality development of the digital economy by strengthening the support role of data in the digital economy; and accelerate digital industrialization and industrial digitalization to realize the integration of digital and real economies.

Forest as a vital natural resource in China plays an irreplaceable important role in safeguarding ecological security and human survival and development. Due to the vast territory, huge population and widespread forest landscape of China, forest management is a complex system involving massive data and various management activities. To effectively implement sustainable forest management, the big data technology has been utilized to analyze China’s forestry resources. Thus, the purpose of this paper is to clarify the role of big data technology in China’s forest management.

In this paper, the authors revisited the roles of big data in forest ecosystem monitoring, forestry management system development, and forest policy implementation.

It demonstrates that big data technology has a great potential in forest ecosystem protection and management, as well as the government’s determination for forest ecosystem protection. However, to deepen the application of big data in forest management, several challenges still need to be tackled.

Thus, enhancing modern science and technology to improve big data, cloud computing, and information technologies and their combinations will contribute to tackle the challenges and achieve wisdom of forest management.

The purpose of this paper is to explore whether an in-service life teacher training program can improve boarding students’ health, behavior, and academic performance.

The authors conducted a cluster-randomized controlled trial to measure the effect of life teacher training on student health, behavior, and academic performance among 839 boarding students in ten central primary boarding schools in Shaanxi. And the authors also tried to identify why or why not life teacher training works. Both descriptive and multivariate analysis are used in this paper.

The authors find significant improvements in health and behavior. Specifically, compared to boarding students in control schools, 15 percent fewer students in treatment schools reported feeling cold while sleeping at night. The results also showed that student tardiness and misbehaviors after class declined significantly by 18 and 78 percent, respectively. However, the in-service life teacher training program had no measurable impact on boarding students’ BMI-for-age Z-score, number of misbehaviors in class, and academic performance. The analysis suggests that improved communication between life teachers and students might be one mechanism behind these results.

This is the first empirical work which explored how to improve the welfare of boarding students via their life teachers. Because of the sudden increase in boarding students in rural China, it is almost certain that school personnel lack experience in managing boarding students. As such, one promising approach to improving student outcomes might be in-service training for life teachers.

States that, although it differs from that practised in the West, moral consideration is a key factor in making strategic moves for business people in Chinese society. Substantiates this claim based on evidence from business history in China, overseas Chinese business practice and Chinese experiences today. Then, deliberates on the management implications of this phenomenon for people who want to do business with Chinese and in China.

This study aims to examine Chinese college students' perceptions of police.

Using survey data collected from over 400 college students in two cities, the study empirically analyzes the global and specific perceptions of police among Chinese college students and factors that accounted for the variation in Chinese college students' evaluations of police. The study incorporates a broader range of explanatory variables to explain Chinese college students' attitudes toward the police, including demographic characteristics, crime and criminal justice experience, perceptions of quality of life, and locality. The study reviews research on public perceptions of police published in Chinese academic journals.

College students' global satisfaction with police as well as their specific evaluations of police fairness, effectiveness, and integrity were significantly related to their crime and criminal justice experience, perceived quality of life, and locality. Students' background characteristics only had a weak effect on attitudes toward police.

More empirical research is warranted to gauge the extent of Chinese satisfaction with police and police performance. Future research should continue incorporating crime and criminal justice factors into analysis.

Findings of the study provide Chinese police administrators with useful references and directions to improve police‐community relations..

This study represents one of the few attempts to empirically assess Chinese citizens' perceptions of police. It examines not just Chinese college students' global satisfaction with the police, but also their more specific views of various areas of police performance including fairness, effectiveness, and integrity.

The proposed method is to generate the 3 D model of frame assemblies based on their topological model automatedly. It was a very demanding task and there was no appropriate automated method to facilitate this work.

The proposed method includes two stages. The first stage is decisive. In this stage, a deep learning network and the Chu–Liu–Edmonds algorithm are used to recognize contact relations among parts. Based on this recognition, the authors perform a geometrical computation in the second stage to finalize the 3 D model.

The authors verify the feasibility of the proposed method using a case study and find that the classification rate of the deep learning network for part contact relations is higher than 75 per cent. Furthermore, more accurate results could be achieved with modification by the Chu–Liu–Edmonds algorithm. The proposed method has lower computational complexity compared with traditional heuristic methods, and its results are more consistent with existing designs.

The paper introduces machine learning method into assembly modelling issue. The proposed method divides the assembly modelling into two steps and solves the assemble relation creatively.

Frame assemblies are fundamental to many areas. The proposed method could automate frame assembly modelling in a viable way. It could benefit design and manufacture process significantly.

The proposed method expands the application of machine learning into a new field. It would be more useful than simple machine learning in industry. The proposed method is better than general heuristic algorithms. It outputs identical results when the inputs are the same. Meanwhile, the algorithmic complexity in worst situation is better than general heuristic algorithms.

Although manufacturer-initiated rewards are widely used to secure distributors’ compliance, the spillover effect on unrewarded distributors (i.e. observers) in the same distribution channel is under-researched. Using insights from social learning theory, this paper aims to investigate how manufacturer-initiated rewards affect observers’ expectation of reward and shape observers’ compliance toward the manufacturer. Furthermore, this paper explores how such effects are contingent upon distributor relationship features.

To test the hypotheses, hierarchical multiple regression and bootstrapping analyses were performed using survey data from 280 Chinese distributors.

The magnitude of a manufacturer-initiated reward to a distributor stimulates expectation of reward among observers, which enhances compliance; observers’ expectation of reward mediates the impact of reward magnitude on compliance. Moreover, network centrality (of the rewarded peer) negatively moderates the positive impact of reward magnitude on observers’ expectation of reward, whereas observers’ dependence (on the manufacturer) positively moderates this dynamic.

Manufacturers should pay attention to the spillover effects of rewards. Overall, they should use rewards of appropriate magnitude to show willingness to recognize outstanding distributors. This will inspire unrewarded distributors, which will then be more compliant. Furthermore, manufacturers should know that specific types of distributor relationship features may significantly vary the spillover effects.

This study illuminates the spillover effects of manufacturer-initiated reward by opening the “black box” of the link between reward magnitude and observers’ compliance and by specifying the effects’ boundary conditions.

In situations where the crew is reduced, the optimization of crew task allocation and sequencing (CTAS) can significantly enhance the operational efficiency of the man-machine system by rationally distributing workload and minimizing task completion time. Existing related studies exhibit a limited consideration of workload distribution and involve the violation of precedence constraints in the solution process. This study proposes a CTAS method to address these issues.

The method defines visual, auditory, cognitive and psychomotor (VACP) load balancing objectives and integrates them with workload balancing and minimum task completion time to ensure equitable workload distribution and task execution efficiency, and then a multi-objective optimization model for CTAS is constructed. Subsequently, it designs a population initialization strategy and a repair mechanism to maintain sequence feasibility, and utilizes them to improve the non-dominated sorting genetic algorithm III (NSGA-III) for solving the CTAS model.

The CTAS method is validated through a numerical example involving a mission with a specific type of armored vehicle. The results demonstrate that the method achieves equitable workload distribution by integrating VACP load balancing and workload balancing. Moreover, the improved NSGA-III maintains sequence feasibility and thus reduces computation time.

The study can achieve equitable workload distribution and enhance the search efficiency of the optimal CTAS scheme. It provides a novel perspective for task planners in objective determination and solution methodologies for CTAS.