IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i6p5147-d1097493.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/6/5147/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/20/6/5147/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    3. 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).
    4. 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).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhou, Shuai & Yi, Ni & Rasiah, Rajah & Zhao, Haipeng & Mo, Zile, 2024. "An empirical study on the dark side of service employees’ AI awareness: Behavioral responses, emotional mechanisms, and mitigating factors," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Caselli, Mauro & Fracasso, Andrea & Traverso, Silvio, 2021. "Robots and risk of COVID-19 workplace contagion: Evidence from Italy," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    2. Zhao, Jingyou & Hu, Enhua & Han, Mingyan & Jiang, Keshen & Shan, Hongmei, 2023. "That honey, my arsenic: The influence of advanced technologies on service employees’ organizational deviance," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    3. Zhou, Shuai & Yi, Ni & Rasiah, Rajah & Zhao, Haipeng & Mo, Zile, 2024. "An empirical study on the dark side of service employees’ AI awareness: Behavioral responses, emotional mechanisms, and mitigating factors," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    4. Mauro Caselli & Andrea Fracasso & Arianna Marcolin & Sergio Scicchitano, 2023. "The reassuring effect of firms' technological innovations on workers' job insecurity," International Journal of Manpower, Emerald Group Publishing Limited, vol. 45(4), pages 754-778, October.
    5. Guanglu Xu & Ming Xue & Jidi Zhao, 2023. "The Relationship of Artificial Intelligence Opportunity Perception and Employee Workplace Well-Being: A Moderated Mediation Model," IJERPH, MDPI, vol. 20(3), pages 1-16, January.
    6. Kang, David Yeonjun & Hur, Won-Moo & Shin, Yuhyung, 2023. "Smart technology and service employees’ job crafting: Relationship between STARA awareness, performance pressure, receiving and giving help, and job crafting," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    7. 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).
    8. Arias-Pérez, José & Vélez-Jaramillo, Juan, 2022. "Ignoring the three-way interaction of digital orientation, Not-invented-here syndrome and employee's artificial intelligence awareness in digital innovation performance: A recipe for failure," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    9. Samuel Ogbeibu & Charbel Jose Chiappetta Jabbour & James Gaskin & Abdelhak Senadjki & Mathew Hughes, 2021. "Leveraging STARA competencies and green creativity to boost green organisational innovative evidence: A praxis for sustainable development," Business Strategy and the Environment, Wiley Blackwell, vol. 30(5), pages 2421-2440, July.
    10. Hyun Jung Lee & Tahira M. Probst & Andrea Bazzoli & Sunhee Lee, 2022. "Technology Advancements and Employees’ Qualitative Job Insecurity in the Republic of Korea: Does Training Help? Employer-Provided vs. Self-Paid Training," IJERPH, MDPI, vol. 19(21), pages 1-13, November.
    11. Makarius, Erin E. & Mukherjee, Debmalya & Fox, Joseph D. & Fox, Alexa K., 2020. "Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization," Journal of Business Research, Elsevier, vol. 120(C), pages 262-273.
    12. Li, Chao & Zhang, Yuhan & Li, Xiang & Hao, Yanwei, 2024. "Artificial intelligence, household financial fragility and energy resources consumption: Impacts of digital disruption from a demand-based perspective," Resources Policy, Elsevier, vol. 88(C).
    13. Egana-delSol, Pablo & Bustelo, Monserrat & Ripani, Laura & Soler, Nicolas & Viollaz, Mariana, 2022. "Automation in Latin America: Are Women at Higher Risk of Losing Their Jobs?," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    14. David, Sofia & Zinica, Daniel & Bărbuță-Mișu, Nicoleta & Savga, Larisa & Virlanuta, Florina-Oana, 2024. "Public administration managers' and employees' perceptions of adaptability to change under “the future of work” paradigm," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    15. Chowdhury, Soumyadeb & Budhwar, Pawan & Dey, Prasanta Kumar & Joel-Edgar, Sian & Abadie, Amelie, 2022. "AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework," Journal of Business Research, Elsevier, vol. 144(C), pages 31-49.
    16. Khaliq, Abdul & Waqas, Ali & Nisar, Qasim Ali & Haider, Shahbaz & Asghar, Zunaina, 2022. "Application of AI and robotics in hospitality sector: A resource gain and resource loss perspective," Technology in Society, Elsevier, vol. 68(C).
    17. Thomas Bolli & Filippo Pusterla, 2022. "Decomposing the effects of digitalization on workers’ job satisfaction," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 69(2), pages 263-300, June.
    18. Lara C. Roll & Hans De Witte & Hai-Jiang Wang, 2023. "Conceptualization and Validation of the Occupation Insecurity Scale (OCIS): Measuring Employees’ Occupation Insecurity Due to Automation," IJERPH, MDPI, vol. 20(3), pages 1-26, January.
    19. Egana-delSol, Pablo & Cruz, Gabriel & Micco, Alejandro, 2022. "COVID-19 and automation in a developing economy: Evidence from Chile," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    20. Mahyar Kamali Saraji & Dalia Streimikiene & Grigorios L. Kyriakopoulos, 2021. "Fermatean Fuzzy CRITIC-COPRAS Method for Evaluating the Challenges to Industry 4.0 Adoption for a Sustainable Digital Transformation," Sustainability, MDPI, vol. 13(17), pages 1-20, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:20:y:2023:i:6:p:5147-:d:1097493. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.