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The Association between Artificial Intelligence Awareness and Employee Depression: The Mediating Role of Emotional Exhaustion and the Moderating Role of Perceived Organizational Support

Author

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  • Guanglu Xu

    (School of Business, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Ming Xue

    (School of Business Administration, Shanghai Lixin University of Accounting and Finance, Shanghai 201620, China)

  • Jidi Zhao

    (School of Public Administration, College of Economics and Management, East China Normal University, Shanghai 200062, China)

Abstract

The combination of artificial intelligence (AI) technology with the real economy has dramatically improved the efficiency of enterprises. However, the replacement of AI for employment also significantly impacts employees’ cognition and psychological state. Based on the Conservation of Resources Theory, the relationship between AI awareness and employee depression is explored in this article while examining the mediating role of emotional exhaustion, as well as the moderating role of perceived organizational support. Based on a sample of 321 respondents, the empirical results show that (1) AI awareness is significantly positively correlated with depression; (2) emotional exhaustion plays a mediating role between AI awareness and depression; (3) perceived organizational support negatively moderates the relationship between emotional exhaustion and depression; (4) perceived organizational support negatively moderates the mediating role of emotional exhaustion between AI awareness and depression. The research conclusions provide a theoretical basis for organizations to take measures to intervene in the negative impact of changes in AI technology on employees’ mental health.

Suggested Citation

  • Guanglu Xu & Ming Xue & Jidi Zhao, 2023. "The Association between Artificial Intelligence Awareness and Employee Depression: The Mediating Role of Emotional Exhaustion and the Moderating Role of Perceived Organizational Support," IJERPH, MDPI, vol. 20(6), pages 1-16, March.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:6:p:5147-:d:1097493
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    References listed on IDEAS

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    1. Brougham, David & Haar, Jarrod, 2018. "Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA): Employees’ perceptions of our future workplace," Journal of Management & Organization, Cambridge University Press, vol. 24(2), pages 239-257, March.
    2. Lingmont, Derek N.J. & Alexiou, Andreas, 2020. "The contingent effect of job automating technology awareness on perceived job insecurity: Exploring the moderating role of organizational culture," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    3. Brougham, David & Haar, Jarrod, 2020. "Technological disruption and employment: The influence on job insecurity and turnover intentions: A multi-country study," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    4. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
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    Cited by:

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    2. Hazem Ahmed Khairy & Mohamed Ahmed & Arwa Asiri & Foziah Gazzawe & Mohamed A. Abdel Fatah & Naim Ahmad & Ayman Qahmash & Mohamed Fathy Agina, 2024. "Catalyzing Green Work Engagement in Hotel Businesses: Leveraging Artificial Intelligence," Sustainability, MDPI, vol. 16(16), pages 1-17, August.
    3. Naseer Abbas Khan & Robin Maialeh & Maria Akhtar & Muhammad Ramzan, 2024. "The Role of AI Self-Efficacy in Religious Contexts in Public Sector: The Social Cognitive Theory Perspective," Public Organization Review, Springer, vol. 24(3), pages 1015-1036, September.

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