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The purpose of this paper is to explore the impact of multidimensional perceived value and perceived pressure on physicians’ continuous intention to use (CIU) online health communities (OHCs) based on perceived value (PV) theory and conservation of resources (COR) theory.

This study developed a research model to test the proposed hypotheses, and the proposed model was tested using partial least squares structural equation modelling (PLS-SEM) for which data were collected from 481 physicians with OHC experience using an online survey.

The empirical results show the following: (1) Physicians’ CIU is influenced by perceived value and perceived pressure, with attitude towards OHCs using (ATU) playing a crucial role in the pathways. (2) Additional value, work pressure, peer pressure and social pressure have a positive impact on CIU, with consultation value, relationship value, work pressure and peer pressure positively influencing CIU through ATU as a mediator. (3) Reputation value has a positive effect on CIU moderated by seniority (online seniority and offline seniority).

This study emphasises the importance of different dimensions of perceived value and perceived pressure in CIU. Meanwhile, we broaden the research scope of PV theory and COR theory and provide inspiration to OHC managers and healthcare institution managers.

In the teleoperating process, the kinematically dissimilar mechanisms of the slave robots and the teleoperation devices will provide unplanned and discontinuous trajectories to the slave robots, which causes jitter on the slave robots that seriously affects the flexibility and accuracy of the teleoperation task without the operator-sensing. This paper aims to solve the above problem.

This paper established the conventional mapping relationship between the teleoperation device and the robot, and found out the reasons of the impact of jitter on slave robots; the paper then implemented the bilateral force feedback of force/dimension at the mapping point, and iteratively solved the feedback force of each time according to its functional compensation relationship, thus forming the bilateral force feedback method of dynamic impact feedback and operator-sensing of the teleoperation system.

The experimental result shows that the feedback force obtained would clearly make a feedback of the jitter states of the slave robot and enhance the operator-sensing ability, which enables the operators to avoid the jittering state of slave robots in real-time.

We propose a compliant teleoperation control method based on dynamic impact force feedback and operator-sensing. The effectiveness of the method has been verified in experimental validation, ensuring the compliant motion of the slave robot in various scenarios, which makes the teleoperated robots capable to be used in more high accuracy required tasks with a stable status.

This study aims to investigate the evolution of cybersecurity in autonomous vehicles over the past decade, focusing on influential publications, leading authors, key themes and emerging research trends.

A systematic literature review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach, with data extracted from The Lens database and analyzed using VOSviewer and Bibliometrix. This study provides a quantitative overview of academic trends from 2014 to 2023. The analysis reveals significant growth in scientific production, predominantly driven by the USA, China and the UK. Central themes include network security, cyberattack prevention and regulatory frameworks.

The findings emphasize that cybersecurity, artificial intelligence (AI) and regulation are critical for developing secure and reliable vehicular systems.

Future research should focus on enhancing security in vehicle-to-everything, vehicle-to-vehicle and vehicle-to-infrastructure communications by improving protocols and integrating AI.

Key themes identified include trust in security, reliability and user experience.

The analysis highlights future research directions, particularly the integration of AI with sustainable development and autonomous transportation policies.

This study provides a quantitative overview of academic trends from 2014 to 2023 regarding the theme of cybersecurity and self-driving cars.

Green innovation in human-centric smart manufacturing (HSM-GI) has emerged as a new paradigm in innovation management for Industry 5.0. The evaluation analysis method is crucial for measuring the development progress and guiding continual improvements of HSM-GI. Since this process of HSM-GI can be regarded as complex and interactive, a holistic picture is often required to describe the interrelations of its antecedents and consequences. In this respect, this study aims to construct a causality network indicator system and proposes a synergy evaluation method for HSM-GI.

Firstly, based on the Driver force-State-Response (DSR) causal-effect framework, this study constructs a holistic indicator system to analyze the interactions between environmental and human concerns of HSM-GI. Secondly, owing to the imprecision of human cognition and synergy interaction in the evaluation process, a flexible hesitant fuzzy (HF) superiority-inferiority synergetic evaluation method is presented. This method quantifies the strengths of causal relationships and expresses the incentives and constraints attitudes of humans. Finally, the proposed framework is applied to six HSMs in the electronic technology industry.

The driving force and state of the HSM-GI system exhibit an upward trend, while the response continues to decline due to changing market demands. The order and synergy degree have shown an increasing trend during 2021–2023, particularly significant for BOE and Haier Smart Home. HSM-GI systems with higher scores mostly have functional coordination and a coherent synergy structure.

This study demonstrates the proposed approach’s applicability and assists policymakers in formulating targeted strategies for green innovation systems.