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Because of the globalization of the knowledge economy, intellectual property (IP) rights have become an important tool for maintaining market leadership and controlling emerging market shares. This paper aims to identify the IP risks that China’s strategic emerging industries face in the process of knowledge management in the post-COVID-19 pandemic era seeking to minimize these risks and reduce unnecessary losses.

Based on an analysis of the current situation in China’s strategic emerging industries, this paper qualitatively organizes the various types of IP risks faced by China’s strategic emerging industries in their development with knowledge creation, knowledge transfer and knowledge application. This paper further analyzes the factors triggering the risks and proposes endogenous and exogenous IP risk-prevention strategies for China’s strategic emerging industries from the perspective of knowledge management.

Adopting a knowledge management perspective, this paper identifies three main intellectual property risks in the knowledge creation, transfer, application processes of knowledge management for China’s emerging industries, including infringement risks related to independent innovation, leakage risks related to international cooperation and ownership risks related to technology transfer.

Based on the entire technology–product–application process and from a knowledge management perspective, the IP risks in the development of China’s strategic emerging industries are comprehensively elaborated in this paper, providing a theoretical basis for avoiding IP risks that is also widely applicable to other knowledge-intensive industries.

This paper explicates the IP risk faced by China’s strategic emerging industries in each step of the knowledge management process and suggestions from knowledge management strategy, tools and implementation support mechanism holds promise for business, industry and government IP risk prevention are elaborated specially to promote the development of China’s strategic emerging industries. On the one hand, this paper expanded the research on knowledge management by exploring the relationship between knowledge management and intellectual property rights variables. On the other hand, the findings have practical significance for the stable, long term and efficient development of strategic emerging industries in China as well as other knowledge-intensive industries. Empirical analyses on this subject are suggested for future studies.

This study aims to uncover the extent to which cultural traits may explain the puzzling international divergence in COVID-19 outcomes, and how those traits interact with state action to produce compliance with pandemic health policy.

A theoretical framework illustrates the surprising possibility that culture and state action may not reinforce each other but rather act as substitutes in eliciting anti-pandemic behavior. This possibility is tested empirically in two specifications: a cross-sectional regression that includes several novel COVID-related measures, and a panel model that controls for contemporaneous disease burden. Across these models, we use the measures of national culture developed by Hofstede (1984) and a newer metric developed by Schwartz (1990).

Individualism and egalitarianism have a positive effect on disease prevalence, while cultural heterogeneity was associated with a more robust public health response. Consistent with our model, we find that culture and state action served as substitutes in motivating compliance with COVID-19 policy.

The results of this study imply that culture and state interact in determining the effectiveness of public health measures aimed at combating COVID-19; these results recommend culturally aware state intervention when combating pandemics.

This study offers several new contributions. First, it proposes a model to help contextualize the empirical analysis. Second, it examines a wider range of traits than previous studies, including cultural homogeneity and the Schwartz variables. Third, it employs a richer econometric specification that explores the interaction between state and culture in a panel context.

In recent years, online public opinion reversal incidents have been occurring frequently, which has increased the complexity of the evolution of online public opinion, and they have become a difficult issue for public opinion management and control. It is of great significance to explore the regularity of online public opinion reversal.

Combined with the grey characteristics of online public opinion information, a grey graphical evaluation review technique (G-GERT) network model is constructed based on kernel and grey degree, and the frequency, probability and time of online public opinion reversal nodes are calculated using C-marking method and Z-marking method.

Throughout the online public opinion reversal events, there are all repeated outbreak nodes occurring, so the authors regard the repeated occurrence of outbreak nodes as reversal. According to the average frequency, probability and time of repeated outbreak nodes in the G-GERT network model, the authors predict the corresponding key information of reversal. It can simulate the evolution process of public opinion events accurately.

The G-GERT network model based on kernel and grey degree reveals the regulation of public opinion reversal, predicts the frequency, probability and time of reversal nodes, which are the most concerned and difficult issues for decision-makers. The model provides the decision basis and reference for government decision-making departments.

To achieve stable gait planning and enhance the motion performance of quadruped robot, this paper aims to propose a motion control strategy based on central pattern generator (CPG) and back-propagation neural network (BPNN).

First, the Kuramoto phase oscillator is used to construct the CPG network model, and a piecewise continuous phase difference matrix is designed to optimize the duty cycle of walk gait, so as to realize the gait planning and smooth switching. Second, the mapper between CPG output and joint drive is established based on BP neural network, so that the quadruped robot based on CPG control has better foot trajectory to enhance the motion performance. Finally, to obtain better mapping effect, an evaluation function is resigned to evaluate the proximity between the actual foot trajectory and the ideal foot trajectory. Genetic algorithm and particle swarm optimization are used to optimize the initial weights and thresholds of BPNN to obtain more accurate foot trajectory.

The method provides a solution for the smooth gait switching and foot trajectory of the robot. The quintic polynomial trajectory is selected to testify the validity and practicability of the method through simulation and prototype experiment.

The paper solved the incorrect duty cycle under the walk gait of CPG network constructed by Kuramoto phase oscillator, and made the robot have a better foot trajectory by mapper to enhance its motion performance.

The objective of this study is to examine the effects of pictures (consumer pictures vs. product pictures vs. no pictures) in online consumer reviews on product evaluation and to determine the mechanism and boundary conditions behind such effects.

The research consisted of three laboratory experiments.

The results showed that consumer pictures led to the most favorable product evaluation. Study 1 showed that persuasive effect was the mechanism behind the main effect. Study 2 showed that for problem-solving products, consumer pictures increased product evaluation significantly; for enhancing products, there was no significant difference of product evaluation among consumer pictures, product pictures and no picture. The results of Study 3 showed that for the unfamiliar brand, consumer pictures significantly enhanced product evaluation; for the highly familiar brand, there was no significant difference among consumer pictures, product pictures and no picture. The present research used persuasive effects to examine the mechanism behind the interaction effects.

The study provides managerial implications for online store owners about how to manage pictures in online reviews.

This study supplements the literature on online consumer reviews and enriches the study of effects of pictures.

In light of the stimulus-organism-response (SOR) theoretical paradigm, this paper explores how information relevance and media richness affect social network exhaustion and, moreover, how social network exhaustion ultimately leads to health anxiety and COVID-19-related stress.

The conceptual model is explicitly analyzed and estimated by using data from 309 individuals of different ages in mainland China. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were utilized to validate the proposed hypotheses through the use of online data.

The findings suggest that information relevance is negatively associated with social network exhaustion. In addition, social network exhaustion is a significant predictor of health anxiety and stress. Furthermore, information relevance and media richness can indirectly influence health anxiety and stress through the mediating effect of social network exhaustion.

Theoretically, this paper verifies the causes and consequences of social network exhaustion during COVID-19, thus making a significant contribution to the theoretical construction and refinement of this emerging research area. Practically, the conceptual research model in this paper may provide inspiration for more investigators and scholars who are inclined to further explore the different dimensions of social network exhaustion by utilizing other variables.

Although social network exhaustion and its adverse consequences have become prevalent, relatively few empirical studies have addressed the deleterious effects of social network exhaustion on mobile social media users’ psychosocial well-being and mental health during the prolonged COVID-19. These findings have important theoretical and practical implications for the rational development and construction of mobile social technologies to cultivate proper health awareness and mindset during the ongoing worldwide COVID-19 epidemic.

The purpose of this paper is to propose a novel jump control method based on Two Mass Spring Damp Inverted Pendulum (TMS-DIP) model, which makes the third generation of hydraulic driven wheel-legged robot prototype (WLR-3P) achieve stable jumping.

First, according to the configuration of the WLR, a TMS-DIP model is proposed to simplify the dynamic model of the robot. Then the jumping process is divided into four stages: thrust, ascent, descent and compression, and each stage is modeled and solved independently based on TMS-DIP model. Through WLR-3P kinematics, the trajectory of the upper and lower centroids of the TMS-DIP model can be mapped to the joint space of the robot. The corresponding control strategies are proposed for jumping height, landing buffer, jumping attitude and robotic balance, so as to realize the stable jump control of the WLR.

The TMS-DIP model proposed in this paper can simplify the WLR dynamic model and provide a simple and effective tool for the jumping trajectory planning of the robot. The proposed approach is suitable for hydraulic WLR jumping control. The performance of the proposed wheel-legged jump method was verified by experiments on WLR-3P.

This work provides an effective model (TMS-DIP) for the jump control of WLR-3P. The results showed that the number of landing shock (twice) and the pitch angle fluctuation range (0.44 rad) of center of mass of the jump control method based on TMS-DIP model are smaller than those based on spring-loaded inverted pendulum model. Therefore, the TMS-DIP model makes the jumping process of WLR more stable and gentler.

The objective of this study was to analyse the influencing factors of citizens' dissatisfaction with government services during the COVID-19 pandemic to help government departments identify problems in the service process and possible countermeasures.

The authors first used cosine interesting pattern mining (CIPM) to analyse citizens' complaints in different periods of the pandemic. Second, the potential evaluation indices of customer satisfaction were extracted from the hotline business system through a hypothesis analysis and modelled using multiple regression analysis. During the index transformation and standardization process, a machine-learning algorithm of clustering and emotion analysis was adopted. Finally, the authors used the random forest algorithm to evaluate the importance of the indicators and obtain the indicators more important to citizen satisfaction.

The authors found that the complaint topic, appeal time, urgency of citizens' complaints, citizens' emotions, level of detail in the case record, and processing timeliness and efficiency significantly influenced citizens' satisfaction. When the government addresses complaints in a more standardized and efficient manner, citizens are more satisfied.

During the pandemic, government departments should be more patient with citizens, increase the speed of the case circulation and shorten the processing period of appeals. Staff should record appeals in a more standardized manner, highlighting themes and prioritizing urgent cases to appease citizens and relieve their anxiety.

Drawing on the work design growth model (WDGM), this paper aims to explore the relationship between job complexity and employee creativity through feedback-seeking and the moderating effect of team leaders with a growth creative mindset.

The authors used an online survey to test the hypotheses. Data was collected in three waves from 74 supervisors and 349 paired employees in China.

Job complexity had a positive association with employees’ feedback-seeking, which further linked to employee creativity. This indirect effect was stronger in work teams with leaders endorsing a growth creative mindset.

Job complexity has become prevalent in organizations today. Taking daily complexity as a resource for nurturing employee creativity may balance organizations’ costs on formal training and give them more initiatives in long-term development. In addition, as the growth creative mindset is relatively easy to assess and change, it may bring insights in terms of creativity development.

By empirically testing the behavioural mechanism of WDGM, the learning and development perspective of work design offers a new explanation of the relationship between job complexity and employee creativity. The authors further extend WDGM by identifying leaders’ growth creative mindset to be a boundary condition.

To reveal the effective ways for leaders to motivate employees' innovative behaviour in complex environmental situations, the leadership rapport orientation is subdivided into two types of values-based/instrumental rapport orientation. The mechanism of supervisor developmental feedback in mediating between leadership rapport orientation and employees' innovative behaviour and the moderating effect of ambidextrous environments is explored. This paper aims to discuss the aforementioned objective.

Leadership rapport orientation is divided into value-based and instrumental rapport orientation to reveal effective ways for leaders to motivate employees' innovative behaviour in complex environmental situations.

The results show that the values-based (instrumental) rapport orientation of leaders impacts employees' innovative behaviour positively (negatively).

Leaders' values-based/instrumental rapport orientation indirectly influences employees' innovative behaviour through supervisor developmental feedback, which positively moderates the relationship between the values-based or instrumental rapport orientation of leaders and employees' innovative behaviour and further moderates the partially mediating role of supervisor developmental feedback between leaders' values-based/instrumental rapport orientation and employees' innovative behaviour.