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The purpose of this study is to address the welding demands within large steel structures by presenting a global spatial motion planning algorithm for a mobile manipulator. This algorithm is based on an independently developed wall-climbing robot, which comprises a four-wheeled climbing mobile platform and a six-degree-of-freedom robotic manipulator, ensuring high mobility and operational flexibility.

A convex hull feasible domain constraint is developed for motion planning in the mobile manipulator. For extensive spatial movements, connected sequences of convex polyhedra are established between the composite robot’s initial and target states. The composite robot’s path and obstacle avoidance optimization problem are solved by constraining the control points on B-spline curves. A dynamic spatial constraint rapidlye-xploring random trees-connect (RRTC) motion planning algorithm is proposed for the manipulator, which quickly generates reference paths using spherical spatial constraints at the manipulator’s end, eliminating the need for complex nonconvex constraint modeling.

Experimental results show that the proposed motion planning algorithm achieves optimal paths that meet task constraints, significantly reducing computation times in task conditions and shortening operation times in non-task conditions.

The algorithm proposed in this paper holds certain application value for the realization of automated welding operations within large steel structures using mobile manipulator.

Based on the perspective of knowledge management, this study aims to discuss how to build cross-city emergency management collaboration mechanism in major emergencies and explore the important role of knowledge management in emergency management collaboration.

Based on the theoretical analysis of knowledge management and the typical case study of cross-city emergency management collaborative rescue, this study provides an in-depth analysis of how these cities achieve high emergency management performance through multidimensional and multilevel knowledge collaboration, thus revealing the mechanism of knowledge transfer, integration and sharing in achieving high emergency management performance.

Through analyzing typical cases, this study finds that building a smooth mechanism for multichannel emergency rescue information can promote the diversification of knowledge transfer methods, building a platform-based integration mechanism for emergency rescue information can enhance knowledge integration capabilities and building a linkage mechanism for emergency rescue materials between cities can promote knowledge-sharing level, thereby improving emergency management performance level.

This study has great significance for how to build cross-city emergency management collaboration mechanism in the digital era. In the future, the authors need to further discuss the following two aspects in depth: research on the impact of cross-city emergency management collaboration mechanism on improving the knowledge management capabilities of government emergency management departments; and research on the impact mechanism of knowledge management capabilities on city resilience.

Through case analysis of cross-city emergency management collaborative rescue for major emergencies in China in recent years, this study proposes three specific strategies for cross-city emergency management (smooth, integration and linkage mechanisms) and reveals that these three strategies are essentially aimed at improving the government’s knowledge management level.

This study aims to enhance the classification and processing of online appeals by employing a deep-learning-based method. This method is designed to meet the requirements for precise information categorization and decision support across various management departments.

This study leverages the ALBERT–TextCNN algorithm to determine the appropriate department for managing online appeals. ALBERT is selected for its advanced dynamic word representation capabilities, rooted in a multi-layer bidirectional transformer architecture and enriched text vector representation. TextCNN is integrated to facilitate the development of multi-label classification models.

Comparative experiments demonstrate the effectiveness of the proposed approach and its significant superiority over traditional classification methods in terms of accuracy.

The original contribution of this study lies in its utilization of the ALBERT–TextCNN algorithm for the classification of online appeals, resulting in a substantial improvement in accuracy. This research offers valuable insights for management departments, enabling enhanced understanding of public appeals and fostering more scientifically grounded and effective decision-making processes.

This paper aims to construct a new turnover theory to explain and predict employee voluntary turnover in a more in-depth and comprehensive way.

Based on the literature review and theoretical analysis, this paper constructs a new turnover theory called the psychological goal system driving theory of employee turnover.

The psychological goal system driving theory of employee turnover advocates that there are psychological goals in the individual psychological world that point to the future and seek self-realization, and that there is a synergistic or competitive relationship among different psychological goals, and thus forming a psychological goal system and the dominant goals (including single goal or goal group) that exist in it; the individual’s dominant goals are the source of motivation, which initiate and organize the individual’s cognition and behavior; when the dominant psychological goals are difficult to achieve or destroyed in the original organization, they will produce continuous negative emotions and drive the individual to choose new and suitable job opportunities to realize themselves. Therefore, the dominant psychological goal is the organizer and driver of the employee turnover behavior, and when they are threatened, they will drive individuals to actively terminate the employment relationship with the current organization to better promote or protect their own realization process and sustainable growth.

This paper constructs a new turnover theory based on the self-organization goal system theory of motivation and personality.

Well-constructed transportation infrastructure may effectively decrease barriers to the flow of innovative human resources and inventive elements, accelerating enterprise innovation activities. This study will explore how HSR helps enterprises achieve ambidextrous innovation, including the mediating mechanism of absorbed slack resources, innovative talents, and the heterogeneous effects of management shareholding ratio and financing constraints.

Based on resource dependence theory and social network theory, this study employs a quasi-natural experiment of China’s high-speed railway and builds a multi-time point DID model to investigate its influence on enterprise ambidextrous innovation.

Results suggest that the HSR positively influences both exploitative and exploratory innovation, and the influence is more substantial on exploitative innovation. Further analysis finds two influencing channels through which HSR influences enterprise ambidextrous innovation: providing redundant resources and attracting innovative talents. Heterogeneity analysis indicates that HSR has a more significant positive effect on exploratory innovation for enterprises with high management shareholding. In the low financing constraint group, the HSR opening has a more significant impact on ambidextrous innovation.

In ambidextrous innovation, enterprises should rationalize the allocation of resources, attach importance to the innovative talent introduction, and choose differentiated paths based on intrinsic characteristics. Meanwhile, the government should actively improve the HSR routes and continuously improve the innovative environment.

This study enriches the theoretical research framework of HSR and ambidextrous innovation by identifying the channel mechanisms and boundary conditions through which HSR affects ambidextrous innovation and expands the consequences of HSR and the antecedents of ambidextrous.

This study aims to present a comprehensive knowledge mapping and an in-depth analysis of plastic and sustainability research to understand better global trends and directions in this field that emerged between 1995 and 2022.

This study presents a visual analysis of 1933 research articles listed in the Web of Science (WoS) databases between the years 1995 and 2022 related to plastic and sustainability. The knowledge mapping based on CiteSpace and VOSviewer presents the current research status, which contains the analysis of the collaboration network, co-citation network, references with citation bursts and keyword analysis.

The results reveal that China and the USA are the most prominent countries in exploring the notion of sustainability and plastic. The Chinese Academy of Science is the most prominent institution. Chai Qiang, Friedrich Daniel, Sahajwalla Veena and Ok Yong Sik are the most prolific authors in this field. Furthermore, circular economy, bioplastic, sustainable development, polyester and bioplastics are the highly discussed issues in recent years. Not surprisingly, COVID-19 is the latest topic of discussion started in 2021 due to its negative impact on plastic pollution and the challenges it posed to sustainability.

This study is among the pioneers to shed light on the current research status of plastic and sustainability using the bibliometric method and the newest data. This study also suggests that collaborations between scholars and institutions require to be enhanced for better management of plastic pollution and to contribute to sustainable development.

This paper aims to investigate investors' willingness to use robo-advisors from customers' perspectives and analyzes the factors that drive them to use robo-advisors, including perceived usefulness and emotional response.

The authors extend the Cognition-Affect-Conation (CAC) framework to the behavioral domain of robo-advisor users on financial technology platforms and conduct an empirical study based on 248 valid questionnaires.

The authors find two types of factors driving the willingness to use robo-advisors: perceived usefulness, trust and perceived risk as external driving forces and investor sentiment as an internal driving force. Trust has a significant positive effect on willingness to use, and arousal in emotional response plays a mediating role between perceived usefulness and willingness to use.

This research provides valuable insights for financial institutions to engage in robo-advisor innovation from customers' perspectives.

According to relevant research, non-uniform speed has a significant impact on the vehicle-track systems. Up to now, research work on it is still very limited. In this paper, the PEM is adopted to further transform it into a deterministic process to solve the vehicle’s problem of running at a non-uniform speed.

The multi-body vehicle model has 10 degrees of freedom and the track is regarded as a finite long beam supported by lumped sleepers and ballast blocks. They are connected via linear Hertz springs. The vertical track irregularity is a Gaussian stationary process in the space domain. It is transformed into a uniformly modulated nonstationary random process in the time domain with respect to the non-uniform vehicle speed. By solving the equation of motion of the coupled vehicle-track system with the pseudo-excitation method, the pseudo-response and consequently the power spectral density and the standard deviation of the structural response can be obtained.

Two kinds of vehicle braking programs are taken in the numerical example and some beneficial conclusions are drawn.

The pseudo-excitation method (PEM) was used to perform the random vibration analysis of a coupled non-uniform speed vehicle-track system. Transforming the track irregularity into a uniformly modulated nonstationary random process in time domain with respect to the non-uniform vehicle speed was undertaken. The pseudo-response of the coupled system is solved by applying the Newmark algorithm with constant space integral steps. The random vibration transfer mechanism of the coupled system is fully discussed.

A main challenge in studying China is that different views clash. A more serious challenge is that studies that are critical of or dissent from the Chinese government policies are labeled “anti-China” by the Chinese authorities, affecting the free academic exchange of ideas on China. This article discusses this issue and proposes a long-term solution.

This is a perspective study and uses the qualitative approach to develop the authors’ arguments.

The authors argue that the contention in China-related studies is derived primarily from the different perspectives that scholars use. This study identifies two main perspectives: the China-centric view and the rest of the world’s view. The combination of the clash of perspectives and the interference of the Chinese state hinders the development of our knowledge regarding China. Using Rawls’ theory of justice and the veil of ignorance, the authors propose to build common ground for the China study community based on academic freedom, equality and the rule of law. This study further shows that building the common ground is feasible.

The authors’ proposed common ground will help create a free environment for meaningful exchange between different perspectives and reduce the risks in China studies.

The authors’ angle to examine the contentiousness and riskiness of China studies is new. It is the first time that different perspectives on China studies are delineated and compared, the costs of the contentiousness and riskiness are assessed, and the long-term consequences of different paths are examined.

The practical need for understanding and improving team resilience has increased, and more research is needed to provide an evidence-base for guiding organizational practices and policies. In this chapter, the authors highlight what we see as critical challenges and opportunities for advancing the science of team resilience. We focus on conceptual and methodological challenges involved in conducting field-based research on team resilience, as the authors believe field-based research is a particularly critical approach for advancing the science of team resilience. The authors first provide a brief review of recent theoretical work in defining team resilience. Then the authors describe key challenges that must be managed in field studies seeking to refine and capitalize on this critical area of research to provide solutions capable of supporting individual, team, and organizational outcomes. These challenges include defining trajectories of resilient team performance, understanding the consequences of repeated episodes of team resilience, formal specifications of events precipitating resilient team performance, measuring the event appraisal and communication process, and adopting measurement methods with high temporal resolution. Finally, the authors provide directions for future research to address these gaps.