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Analyzing the impact of artificial intelligence on employee productivity: the mediating effect of knowledge sharing and well-being

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28120%2F23%3A63562398" target="_blank" >RIV/70883521:28120/23:63562398 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1111/1744-7941.12385" target="_blank" >https://doi.org/10.1111/1744-7941.12385</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1111/1744-7941.12385" target="_blank" >10.1111/1744-7941.12385</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Analyzing the impact of artificial intelligence on employee productivity: the mediating effect of knowledge sharing and well-being

  • Original language description

    Following social cognitive theory, the current study investigated the impact of artificial intelligence (AI) on employees’ productivity in the healthcare sector. AI significantly facilitates the management of hospitals to vigilantly assess employees’ productivity and accurately analyze employees’ characteristics, such as attitude, emotion and behavior. With the underlying mechanism of employee mental health and well-being, and knowledge sharing, the study has considered beneficial and harmful perspectives of AI in the workplace. The study also hypothesizes the important moderating role of technological leadership. The data was collected from 184 doctors in Pakistan’s major hospitals. Partial least squares (PLS) results support a direct relationship between AI and employee productivity. The findings also supported the underlying mechanism of knowledge sharing and mental health and well-being in the relationship between AI and employee productivity. However, the technological leadership moderating effect was found to be insignificant. It opens an important avenue for this further research and future directions.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    50204 - Business and management

Result continuities

  • Project

  • Continuities

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Asia Pacific Journal of Human Resources

  • ISSN

    1038-4111

  • e-ISSN

    1744-7941

  • Volume of the periodical

    61

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    AU - AUSTRALIA

  • Number of pages

    27

  • Pages from-to

    794-820

  • UT code for WoS article

    001019959400001

  • EID of the result in the Scopus database

    2-s2.0-85163595159