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The mounting health misinformation on social media triggers heated discussions about how to address it. Anchored by the influence of presumed influence (IPI) model, this study investigates the underlying process of intentions to combat health misinformation. Specifically, we analyzed how presumed exposure of others and presumed influence on others affect intentions to practice pre-emptive and reactive misinformation countering strategies.

Covariance-based structural equation modeling based on survey data from 690 Chinese participants was performed using the “lavaan” package in R to examine the proposed mechanism.

Personal attention to health information on social media is positively associated with presumed others’ attention to the same information, which, in turn, is related to an increased perception of health misinformation’s influence on others. The presumed influence is further positively tied to two pre-emptive countermeasures (i.e. support for media literacy interventions and institutional verification intention) and one reactive countermeasure (i.e. misinformation correction intention). However, the relationship between presumed influence and support for governmental restrictions, as another reactive countering method, is not significant.

This study supplements the misinformation countering literature by examining IPI’s tenability in explaining why individuals engage in combating misinformation. Both pre-emptive and reactive strategies were considered, enabling a panoramic view of the motivators of misinformation countering compared to previous studies. Our findings also inform the necessity of adopting a context-specific perspective and crafting other-oriented messages to motivate users’ initiative in implementing corrective actions.

This study aims to investigate the impact of environmental, social and governance (ESG) performance on financial capabilities and strategic decision-making within enterprises. It seeks to provide clarity on how fulfilling ESG responsibilities influences financial performance, while examining differential effects across firm types.

This study analyzes the relationship between ESG performance and financial metrics using data from Chinese listed companies (2013–2022) and DuPont’s analytical framework.

First, while ESG practices enhance financial stability and market appeal, they also incur additional operating costs. Second, companies tend to increase their investments in innovation and capital expenditure as a result of better ESG performance. While capital expenditure boosts financial performance significantly, innovation investment, though promising, yields uncertain outcomes and has less influence compared to capital expenditure. Furthermore, the financial performance of nonstate-owned and nonpolluting firms is more susceptible to fluctuations in ESG performance.

The findings are context-specific and may not universally apply to all industries and regions. Further research is needed to validate the study’s propositions in diverse economic environments.

Policymakers should consider incentivizing ESG compliance to bolster market competitiveness. Enterprises are advised to optimize internal processes to balance ESG practices with operational efficiency and innovation for sustainable growth.

This paper introduces an innovative use of DuPont analysis in economics to explore how ESG affects financial and operational performance, showing it can boost corporate results and prompt ESG responsibility. It also distinguishes innovation outcomes with “Innovation Investment” and “Capital Expenditure,” offering enhanced investment guidance.

This study aims to identify which types of information quality influence purchase intentions the most in live streaming commerce and to examine the role of network size in this context.

We propose a model to investigate the correlation among the quality of different information in live streaming commerce, consumer trust, network size and purchase intention. An empirical analysis of 505 questionnaires was conducted by constructing a structural equation model.

The empirical findings indicate that information quality can directly enhance purchase intention and exert an indirect influence through the mediating factors of trust in products and streamers. Perceived network size positively moderates the relationship between information quality and trust in products. Of the five types of information, the quality of bullet-screen comments information is most important to consumers.

This study represents the first systematic analysis of how the quality of multiple types of information in live streaming commerce influences consumer trust and purchase intention, integrated within a unified framework. It uniquely introduces network size as a moderating variable, offering both theoretical insights and practical guidance for balancing information quality with network size in live streaming commerce environments.

This paper aims to explore the underlying mechanisms and boundary conditions through which equipment manufacturing enterprises can capture market value from digital transformation, with a specific focus on the roles of knowledge search and knowledge recombination.

This study uses a double fixed-effects model to test the hypotheses, using a unique data set of “firm-year” observations from 739 publicly listed equipment manufacturing companies in China, spanning the period from 2018 to 2022.

Digital transformation drives market value creation in equipment manufacturing enterprises through both breakthrough knowledge recombination (BKR) and progressive knowledge recombination (PKR). In addition, the analysis of marginal conditions reveals that diversified knowledge search serves as a substitute for digital transformation in promoting BKR, while also positively moderating the relationship between digital transformation and PKR.

Grounded in the knowledge-based view theoretical framework, this study introduces the novel concepts of BKR and PKR and systematically examines how digital transformation impacts market value in equipment manufacturing enterprises.

In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

The purpose of this paper is to reveal the pattern between government innovation funding and enterprise value creation. Many factors, including government innovation funding, R&D ability, corporate governance and some company characteristics significantly affected the efficiency of firm value creation.

This paper proposed a novel methodology based on clustering-rough sets to explore the characteristics of enterprise value creation behavior, and map the relationship between government innovation funding and enterprise value creation. The agglomerative hierarchical clustering (AHC) algorithm were used to classify firm performance and get two types of value creation efficiencies and to discretize condition attributes because the rough set theory cannot deal with continuous attributes. This paper utilized the rough sets method to realize data mining and get rules of government innovation funding and enterprise value creation.

R&D ability, proportion of independent directors, remuneration of directors, operating revenue, number of employees, price-earnings ratio, quick ratio, capital intensity and ROA were important to identify firm value creation efficiency when government funded the firms. Firms of high level of government innovation funding, high lagged R&D ratio, high remuneration of directors, low price-earnings ratio, low quick ratio, moderate capital intensity and high ROA were more likely to have high efficiency of value creation.

Since China implemented the innovation-driven development strategy, facilitating enterprise innovation has become an important way to achieve high-quality economic growth. With constantly increasing of Chinese government innovation funding, studying on the effect of government innovation funding on firm’s value creation is significant to improve the efficiency of government resource allocation. It is valuable to reveal the pattern between government innovation funding and enterprise value creation based on the value added theory. The rules obtained could be used to provide decision-making support to improve the efficiency of government innovation funding and prevent waste of government resources effectively.

Harmonic gears always work under different operating conditions and may usually break down due to lubrication failures, while its lubrication mechanism is still not clearly understood. This paper aims to present a lubrication model comprehensively considering the influence of contact geometry, lubrication properties and three-dimensional (3D) real surface roughness to analyze the lubrication performance under different conditions.

Based on the discrete convolution-fast Fourier transformation with duplicated padding and quasi-system numerical methods, the lubrication model for harmonic gears is developed, which is verified by comparing results with available lubrication data.

The effects of meshing process, working conditions and 3D roughness on the lubrication characteristics are discussed. From the calculated cases, the increase in rotational speed and decrease of applied torque may increase the film thickness, enhancing the lubrication performance of harmonic gears. It is also observed that proper surface roughness can be used for lubrication design.

The research results can provide theoretical guidance for improving lubrication performance and reducing friction/wear of the harmonic gear interfaces. This study can be promoted to various engineering scenarios of harmonic gears, such as industrial robots, space-driven agencies and precision measuring instruments.

Robots, as the crystallization of new artificial intelligence, are being applied in various fields, especially the hotel industry. They are seizing the opportunities, using technology to improve the overall quality and comprehensive competitiveness. However, they also cause many problems due to practical limitations. The purpose of this paper is to study customers' recognition and acceptance of hotel service robots to guide the successful promotion of this technology.

This paper proposed a comprehensive model based on the theory of planned behavior, the technology acceptance model and then the perceived value-based acceptance model. Exploratory factor analysis, confirmatory factor analysis, grouped regression analysis and path analysis was adopted to validate the impacts of each variable to obtain the final reliable model using data collected from hotel guests using a self-designed questionnaire.

The empirical research based on the theoretical model shows that the constructed conceptual model can thoroughly explain the influencing factors of hotel robot acceptance, enrich the acceptance theory and provide academic support for the use and popularization of hotel service robots. Among all variables, attitude, usefulness and perceived value are the factors that have the greatest impact on acceptance. They have significant differences in the effects of adjustment variables such as gender, educational level, whether hotel robots have been used, and whether other robot services have been experienced on different paths in the model.

This paper explored the customer acceptance of service robots in hotels, helped to understand the process of decision-making on service robot selection and contributed to the theoretical extension of the hospitality industry. The work guides hotel management to promote better-personalized products and services of robot technology in the hospitality industries.

The acceptance study on hotel service robots provides insight into the hotel industry to understand customers' attitudes and acceptance of emerging technology.

This study aims to provide an exploratory analysis of a broad range of factors that may help to explain the rapid growth of Chinese private owned enterprises (POEs).

The analysis in this study takes advantage of an archival dataset constructed by the third author from proprietary data collected for a practitioner conference in China.

Consistent with research on entrepreneurs in Western economies, the individual characteristics of the Chinese founders showed weak correlations with sales growth, but measures of founder motivation did correlate with sales growth. While the results for company characteristics were also weak, most of the factors related to company governance, strategy, competitive advantage, and stakeholder trust all showed significant correlations with the POE's rates of sales growth.

The motivations of Chinese founders appear to matter more than their traits in explaining their ability to grow sales. Solid structure, strategy, and competitive advantages are important also. Building trust with stakeholders may facilitate growth by helping Chinese POEs bridge the institutional voids that they face.

The rapid growth of the Chinese economy and of Chinese POEs offers a unique content in which to study factors that may affect growth rates. However, obtaining reliable data on Chinese POEs is difficult; this study uses a proprietary dataset to offer a rare glimpse into the factors that may affect the sales growth rates of Chinese POEs.

Grounded in the structural and relational inertia literature, this paper aims to investigate how two types of founding conditions – prior state ownership and a founder’s state career history – may individually and interactively affect the resource acquisition and organizing capability of firms.

This study uses a unique, large-scale survey of 480 manufacturing firms in China.

The findings show that prior state ownership is positively related to a firm’s resource acquisition, and the founder’s state career history moderates the relationship between prior state ownership and a firm’s organizing capability such that a founder with a state career history can help a privatized firm overcome its structural inertia and achieve superior organizing capabilities. However, it is found that a founder’s state career history is not associated with a firm’s resource acquisition or organizing capability.

First, this study is cross-sectional. Second, this paper refocuses on Chinese manufacturing firms in two regions only. Third, the authors do not have information on how long founders had been in state sector. Fourth, the measure of resource acquisition and organizational capability is a self-reported perceptual measure.

First, this study suggests that founders’ state career history does not benefit firms in resource acquisitions. Once founders do not work for government organizations, they can lose the associated resource benefits. The founders may have to actively maintain their historical connections with the current government officials to continue to receive various information and resource benefits. Second, this study indicates that it is possible for privatized firms to have resource acquisition advantages resulting from their historical heritage and at the same time overcome the inferior organizing capabilities from their histories by having a founder with a prior state career history. Such founders tend to have the ability to overcome the unfavorable imprinting effect of previous histories and to help private firms develop better strategies and structures to fit the dynamic and competitive environment.

This study indicates that it is possible for state-owned enterprises to become efficient if they can employ capable managers with superior managerial skills.

Current literature on the effect of government affiliations on firm behavior and outcomes typically focuses on existing government affiliations and their benefits on a firm’s economic and information resources, legitimacy and new venture performance. This study is one of the first to examine how historical government affiliations may affect both the resource acquisition and organizing capability of a firm. In addition, existing studies have rarely studied simultaneously how a firm’s and a founder’s historical government affiliations may independently and interactively affect a firm’s ability to acquire resources and develop capabilities critical for a firm’s performance and survival. This study fills this gap.