Xianmiao Li

Dr. Xianmiao Li

Anhui University of Science and Technology, Huainan, Anhui, China

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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MCMengting Cheng
Mengting Cheng
XLXianmiao Li
Xianmiao Li
JXJicheng Xu
Jicheng Xu
Artificial intelligence (AI)-assisted diagnosis and treatment could expand the medical scenarios and augment work efficiency and accuracy. However, factors influencing healthcare workers’ adoption intention of AI-assisted diagnosis and treatment are not well-understood. This study conducted a cross-sectional study of 343 dental healthcare workers from tertiary hospitals and secondary hospitals in Anhui Province. The obtained data were analyzed using structural equation modeling. The results showed that performance expectancy and effort expectancy were both positively related to healthcare workers’ adoption intention of AI-assisted diagnosis and treatment. Social influence and human–computer trust, respectively, mediated the relationship between expectancy (performance expectancy and effort expectancy) and healthcare workers’ adoption intention of AI-assisted diagnosis and treatment. Furthermore, social influence and human–computer trust played a chain mediation role between expectancy and healthcare workers’ adoption intention of AI-assisted diagnosis and treatment. Our study provided novel insights into the path mechanism of healthcare workers’ adoption intention of AI-assisted diagnosis and treatment.

31 January 2020 in Sustainability
Verified
Journal Article
Open access
PDF file
WHWeiwei Huo
Weiwei Huo
XLXianmiao Li
Xianmiao Li
MZManyi Zheng
Manyi Zheng
YLYan Liu
Yan Liu
JYJinyi Yan
Jinyi Yan
Drawing on the upper echelons theory and targeted at Chinese coal enterprises, this research examines the interactions of commitment to human resource management on green creativity, and discusses the mediating mechanism of green human resource management (GHRM) between them. The results show that commitment to human resource management indirectly affects the enterprise of green creativity, while GHRM intermediates the process. Environmental regulation positively regulates the relationship between commitment to human resource management (COHRM) and GHRM, as well as the intermediary role of GHRM in the relationship between COHRM and green creativity. This study provides an important reference value for the research of GHRM in China and offers practical enlightenment for the manufacturing and coal industry enterprises to carry out environmental management and achieve sustainable development.

24 April 2023 in International Journal of Medical Informatics
Verified
Journal Article
Closed access
WHWeiwei Huo
Weiwei Huo
XYXinze Yuan
Xinze Yuan
XLXianmiao Li
Xianmiao Li
WLWenhao Luo
Wenhao Luo
JXJiaying Xie
Jiaying Xie
BSBowen Shi
Bowen Shi


28 March 2022 in Management Decision
Verified
Journal Article
Closed access
ZXZhenting Xu
Zhenting Xu
XLXianmiao Li
Xianmiao Li
XSXiuming Sun
Xiuming Sun
MCMengting Cheng
Mengting Cheng
JXJicheng Xu
Jicheng Xu
Purpose: Drawing on the social exchange theory, this study examines the impact of self-sacrificial leadership on employee creativity and explores the mediating role of employees' creative process engagement and shared vision, along with the multilevel moderating role of shared vision.Design/methodology/approach: The data were collected from 78 R&D teams, and hierarchical linear model and bootstrapping analysis outlined by Hayes were used to test the hypotheses.Findings: Self-sacrificial leadership exerted a significantly positive impact on employee creativity, employees' creative process engagement and shared vision, whereas employees' creative process engagement and shared vision mediated the relationship between self-sacrificial leadership and employee creativity, respectively. Moreover, shared vision significantly moderated the relationship between employees' creative process engagement and employee creativity, such that the higher the shared vision, the stronger the relationship between employees' creative process engagement and employee creativity.Practical implications: Organizations and managers should provide leadership development training programs, such as leadership skills and abilities, to exhibit their self-sacrificing behaviors. Besides, while team leaders set an example for employees, in turn, spurring employees' creative process engagement, they should also elucidate the team/organization mission, amplify the publicity and employees' understanding of the mission.Originality/value: This study advances the self-sacrificial leadership and creativity literature by establishing employees' creative process engagement and shared vision as crucial mediators and shared vision as boundary condition in the relationship between employees' creative process engagement and employee creativity, as well as stressing the theoretical research of leadership and creativity.

1 January 2024 in Journal of Nursing Management
Verified
Journal Article
Open access
XLXianmiao Li
Xianmiao Li
QZQilin Zong
Qilin Zong
MCMengting Cheng
Mengting Cheng
Aim:This study aims to investigate the influence of medical explainable artificial intelligence (XAI) on the innovation behaviour of nurses, as well as explore the dual‐pathway mediating effect of AI self‐efficacy and AI anxiety and organizational ethical climate as the moderating effect.Background:To address the practical application of medical AI technology, alleviate the scarcity of medical resources and fulfil the medical and health demands of the public, it is crucial to improve the innovation behaviour of nurses through the use of medical XAI.Methods:A cross‐sectional survey was conducted involving 368 Chinese nurses working at tertiary and secondary hospitals in Anhui Province, Jiangsu Province, Zhejiang Province and Shanghai.Results:Implementing medical XAI significantly enhanced the innovation behaviour of nurses. Anxiety and self‐efficacy regarding AI mediated the connection between medical XAI and the innovation behaviour of nurses. Furthermore, the organizational ethical climate positively moderated the relationship between medical XAI and AI self‐efficacy.Conclusion:Medical XAI helps to enhance nurses’ AI self‐efficacy and reduce AI anxiety, thereby enhancing nurses’ innovation behaviour. An organizational ethical climate enhances the positive relationship between medical XAI and AI self‐efficacy.Implications for Nursing Management:Organizations and technology developers must augment the study about XAI and the system design of human‐centred AI technology. The organizations aim to enhance the education and training of nurses in AI, specifically focussing on boosting nurses’ self‐efficacy in utilizing AI technology. Moreover, they want to alleviate nurses’ fear of new technological advancements. Hospital administrators and leaders develop strategies to address the ethical atmosphere inside their organization.