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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.

The development and presentation of a framework that integrates modern methods for detecting, assessing and mitigating mental health issues in the context of dynamic and adverse changes in social networks.

This viewpoint is based on a literature review of current advancements in the field. The use of causal discovery and causal inference methods forms the foundation for applying all the techniques included in the framework (machine learning, deep learning, explainable AI as well as large language models and generative AI). Additionally, an analysis of network effects and their influence on users’ emotional states is conducted.

The synergy of all methods used in the framework, combined with causal analysis, opens new horizons in predicting and diagnosing mental health disorders. The proposed framework demonstrates its applicability in providing additional analytics for the studied subjects (individual traits and factors that worsen mental health). It also proves its ability to identify hidden factors and processes.

The proposed framework offers a novel perspective on addressing mental health issues in the context of rapidly evolving digital platforms. Its flexibility allows for the adaptation of tools and methods to various scenarios and user groups. Its application can contribute to the development of more accurate algorithms that account for the impact of negative (including hidden) external factors affecting users. Furthermore, it can assist in the diagnostic process.

This study examines the interdependent relationships between green supply chain management (GSCM), carbon neutrality capability (CNC), digital transformation (DT) and firm performance (FP) among enterprises listed on the Chinese stock market. The primary objective is to provide a scholarly examination that may help these organisations to enhance their GSCM practices significantly.

Drawing on data from mainland Chinese publicly listed firms over the period from 2014 to 2021, this study posits and methodically evaluates four hypotheses: (1) GSCM practices are positively associated with an increase in CNC; (2) GSCM practices have a beneficial impact on FP; (3) DT moderates the GSCM–FP relationship and (4) CNC mediates the effect of GSCM on FP.

Contrary to initial assumptions, the findings suggest that GSCM practices may initially have a negative impact on FP. However, a concerted focus on CNC has the potential to convert this negative trajectory into a positive influence on FP. The findings further identify that DT has a significant moderating effect on the GSCM–FP relationship.

The findings of this study enrich the academic discourse concerning the symbiotic effects of GSCM, CNC and DT on FP. By systematically analysing these dynamics, the study underscores the critical importance of CNC and DT in the successful application of GSCM practices, thus offering valuable contributions to the literature on sustainable corporate operations.

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.

This paper proposes a framework for director evaluation in the context of Chinese state-owned enterprises (SOEs), taking into account the influences of traditional and modern Chinese ideologies.

Following the Delphi method, a series of semi-structured interviews were conducted with Chinese SOE directors.

The framework used has been validated by examining seven dimensions of virtue and four dimensions of competence functions in Chinese SOEs. Effective and representative characteristics of each dimension are identified through interviews.

First, through this research, indicators of virtue have been materialized and those of competence have been specified in a broader range. Second, this research provides advice for training of candidate directors whose experience were in private firms before they step in as SOE directors.

Mega construction projects (megaprojects) require technological innovation cooperation (TIC) to address complex construction demands and the interests of multiple stakeholders. Although TIC has been extensively discussed at the firm level, a significant gap remains in understanding megaprojects at the project level. This paper aims to identify TIC’s influencing factors and transmission paths and discuss stakeholders’ TIC mechanisms at the project level.

Based on case analysis, expert interviews, literature analysis and the Delphi method, this paper identifies the influencing factors of TIC in megaprojects at the project level. A structural system of these influencing factors is constructed by interpretive structural modeling (ISM), developing various mechanisms for TIC from bottom to top. The Matriced’ Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) method validates the driving forces and dependencies of the influencing factors, clarifying their roles and positions within the system. Additionally, the TIC mechanism is constructed.

The research findings identify 26 influencing factors categorized into four hierarchical levels: cooperative relationships, cooperative behavior, cooperative performance and technological innovation risks. Regarding direct factors, resource sharing affects goal congruence and communication effectiveness in megaprojects, affecting TIC’s satisfaction and trust. Most factors exist in the middle layer, and bridging the upper and lower levels depends on stakeholder collaboration. The root factors in the independent group significantly impact TIC, including policy circumstances, high technical requirements and limited site conditions. Addressing these issues influences improvements in other factors. The development of a digital resource-sharing platform, the enhancement of innovation incentives, the optimization of benefit distribution mechanisms and the improvement of risk-sharing mechanisms are essential for the effective operation of the TIC mechanism.

This study contributes to identifying and classifying challenges and opportunities in TIC. It explores transmission paths for enhancing TIC and presents strategies for successfully implementing and delivering megaprojects.

With recent advances in artificial intelligence, the hospitality industry has introduced the concept of unmanned smart hotels staffed by service robots instead of human employees. Research is needed to understand consumers’ receptivity to such an innovation. This paper examines factors associated with consumers’ potential resistance to using automated service hotels via two sequential studies. Given that younger generations of consumers are typically early adopters of advanced technology and innovative services, our sampling approach focused on this consumer group.

Two studies were conducted. Study 1 proposed and empirically tested a theoretical model. Results revealed that attitude, subjective norms and perceived behavioral control each positively influenced individuals’ intentions to use unmanned smart hotels. In Study 2, we further investigated aspects informing perceived security, a key variable in the use of unmanned smart hotels.

Findings showed how people’s beliefs about unmanned smart hotels and security control assurances led to perceived security. These perceptions were shaped by perceived physical risks, privacy concerns, website design and hotel reputation. Overall, this research provides theoretical and practical implications for various stakeholders associated with unmanned smart hotels.

Findings of this study suggested that managers of unmanned smart hotels should design user-friendly, secure processes and offer comprehensive support resources to enhance customer experience and usage.

The findings provide a holistic understanding of consumers’ receptivity to unmanned smart hotels.

Achieving accurate trajectory tracking control of robot manipulators is challenging due to dynamic model errors and uncertain payloads. This paper aims to enhance trajectory tracking performance for robots with n degrees of freedom (DOF).

This study proposes a robust motion control framework that combines uncertainty and disturbance estimator with model-based compensation. The proposed framework ensures precise trajectory tracking in robot manipulators. In addition, uncertainties in the high-DOF robot dynamics are estimated through a simple model-based compensation for system error dynamics. The stability of the closed-loop system of the proposed framework is analyzed and proved.

The results indicate that the proposed framework can significantly reduce tracking errors and increase disturbance resistance. The simulation results of a two-link robotic arm verify the effectiveness of the proposed method. The results of the experiments conducted on a seven-DOF torque-controlled Flexiv4S manipulator demonstrate the superior trajectory tracking performance and robustness of the proposed algorithm.

This study introduces a highly efficient, robust motion control framework for high-DOF robots, which can improve the trajectory tracking performance in the presence of model uncertainties.

The purpose of this study is to provide insight into how innovation that outperforms peers (IOP) affects corporate financial misconduct. To this end, on the basis of fraud triangle theory, we develop a theoretical relationship between the two and argue that IOP has an inhibitory effect on corporate financial misconduct.

On the basis of empirical data from Chinese listed companies from 2007–2023, we conduct a series of tests to examine whether, how and under what circumstances IOP affects corporate financial misconduct.

IOP does inhibit corporate financial misconduct. This result is validated in a series of sensitivity tests. Further analysis shows that IOP inhibits corporate financial misconduct by reducing executives' incentives to engage in fraud, reducing the opportunity under which executives are involved in fraud, and inhibiting executives' tendency to rationalize fraud. In addition, the results of cross-sectional tests show that the negative impact of IOP on corporate financial misconduct is more significant when the firm is a high-tech enterprise, with a greater balance of power among shareholders, lower supplier concentration and greater consumer confidence.

First, by examining the impact of IOP and corporate financial misconduct, we enrich and extend the literature on the antecedents of corporate financial misconduct. Second, by theoretically and empirically validating the relationship between IOP and corporate financial misconduct, we extend the literature related to the economic consequences of IOP. Finally, we extend fraud triangle theory to a wider range of applications and provide new perspectives and strategies for further research and intervention in corporate financial misconduct.

Implementing a green strategy to enhance the competitiveness of enterprises is a hot topic in current research. Although most enterprises have formed a green strategy orientation (GSO), it has not been transformed into green competitiveness (GC). Prior studies have not thoroughly studied the effect and mechanism of GSO on GC. To fill this research gap, based on optimal distinctiveness theory, this paper discusses the mediating role of two kinds of green innovation (GI) in the GSO–GC relationship and the moderating role of big data capability (BDC).

This study adopts the quantitative research methods of multiple linear regression, Bootstrap and structural equation modeling (SEM). Data were collected through a questionnaire and a random sampling method was used to survey middle and senior managers and professionals in manufacturing enterprises. About 400 questionnaires were distributed, and 342 valid questionnaires were collected.

The conclusions show that GSO significantly positively affects GI and GC. Still, it turns out that only strategic green innovation (SGI) mediates the GSO–GC relationship. BDC can positively moderate the mediation effect of SGI between GSO and GC, thus supporting the moderated mediation model.

This study used a survey questionnaire from Chinese manufacturing enterprises to collect data, but the sample size was limited. Furthermore, the mediating mechanism by which GSO affects GC requires further exploration. This study directly establishes the GSO–GC relationship based on the optimal distinctiveness theory, making an essential contribution to the literature on GSO and GC. At the same time, this paper uses GI as a bridge to connect the relationship between GSO and GC, enriching the literature on GI. In addition, we consider BDC to be a moderator, expanding the boundaries of the GSO–GC relationship.

This study provides new knowledge and insights for manufacturing enterprises to construct and implement green strategies to achieve GC. More importantly, managers should attach great importance to the critical role of SGI and BDC.

This study understands the importance of GSO, SGI and BDC to GC in theory and practice.