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Journals / JOEEP: Journal of Emerging Economies and Policy / 2026 / Cilt: 11 Sayı: 1

The Impact of Inclusive Leadership on AI Use Intent: The Mediating Role of Psychological Safety, Emotional Regulation, and Trust

Kapsayıcı Liderliğin Yapay Zekâ Kullanım Niyeti Üzerindeki Etkisi: Psikolojik Güvenlik, Duygusal Düzenleme ve Güvenin Aracı Rolü

Haldun Turan(İSTANBUL RUMELİ ÜNİVERSİTESİ)0000-0002-0701-7679
Kenan Aydın(İSTANBUL GELİŞİM ÜNİVERSİTESİ)0000-0002-0496-5665
Pages
355–366
Publication Date
2026-06-25
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In conclusion, the study revealed the central role of individual emotional self-regulation capacity and trust mechanisms in the AI adoption process, and demonstrated that AI acceptance is shaped not only by cognitive but also by emotional and organizational dynamics.

📌 3 Key Takeaways

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Objective & Hypothesis:The present study aimed to examine the impact of inclusive leadership on employees' intention to use artificial intelligence (AI) and to test the mediating roles of psychological safety, emotional regulation, and trust in AI in this relationship.
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Key Findings & Data:The study determined that the model met the reliability and validity criteria (CR > 0.70; AVE > 0.50; HTMT < 0.90), the structural model showed acceptable fit (SRMR = 0.079), and the explanatory power was at a moderate-high level (R² mean = 0.443; AI use intention R² = 0.619).
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Conclusion & Impact:In conclusion, the study revealed the central role of individual emotional self-regulation capacity and trust mechanisms in the AI adoption process, and demonstrated that AI acceptance is shaped not only by cognitive but also by emotional and organizational dynamics.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Yapay Zeka Benimsenmesi · Kurumsal İklim · İnsan-Yapay Zeka Etkileşimi

Abstract

The present study aimed to examine the impact of inclusive leadership on employees' intention to use artificial intelligence (AI) and to test the mediating roles of psychological safety, emotional regulation, and trust in AI in this relationship. According to the model, inclusive leadership was identified as the independent variable, intention to use AI as the dependent variable, psychological safety and emotional regulation as mediating variables, and trust in AI as both a mediating and direct influencing variable. The study determined that the model met the reliability and validity criteria (CR > 0.70; AVE > 0.50; HTMT < 0.90), the structural model showed acceptable fit (SRMR = 0.079), and the explanatory power was at a moderate-high level (R² mean = 0.443; AI use intention R² = 0.619). In conclusion, the study revealed the central role of individual emotional self-regulation capacity and trust mechanisms in the AI adoption process, and demonstrated that AI acceptance is shaped not only by cognitive but also by emotional and organizational dynamics.

Özet

Bu çalışma, kapsayıcı liderliğin çalışanların yapay zekâ (YZ) kullanma niyetine etkisini incelemeyi ve bu ilişkide psikolojik güvenlik, duygusal düzenleme ve YZ'ye duyulan güvenin aracı rollerini test etmeyi amaçlamıştır. Modele göre, kapsayıcı liderlik bağımsız değişken, YZ kullanma niyeti bağımlı değişken, psikolojik güvenlik ve duygusal düzenleme aracı değişkenler ve YZ'ye duyulan güven hem aracı hem de doğrudan etkileyen değişken olarak belirlenmiştir. Çalışma, modelin güvenilirlik ve geçerlilik kriterlerini karşıladığını (CR > 0,70; AVE> 0,50; HTMT <0,90), yapısal modelin kabul edilebilir bir uyum gösterdiğini (SRMR = 0,079) ve açıklayıcı gücünün orta-yüksek düzeyde olduğunu (R² ortalama = 0,443; YZ kullanım niyeti R² = 0,619) belirlemiştir. Sonuç olarak, çalışma, YZ benimseme sürecinde bireysel duygusal öz düzenleme kapasitesinin ve güven mekanizmalarının merkezi rolünü ortaya koymuş ve YZ kabulünün yalnızca bilişsel değil, aynı zamanda duygusal ve örgütsel dinamikler tarafından da şekillendirildiğini göstermiştir.

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Cite This Article

Turan, H., Aydın, K. (2026). The Impact of Inclusive Leadership on AI Use Intent: The Mediating Role of Psychological Safety, Emotional Regulation, and Trust. JOEEP: Journal of Emerging Economies and Policy, Cilt: 11 Sayı: 1, 355–366. https://ajindex.com/articles/1504079

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References (24)

  1. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.
  2. Bandura, A. (2001). Social Cognitive Theory: An AGENTIC PERSPECTIVE. Annual Review of Psychology, 52(1), 1–26. https://doi.org/10.1146/annurev.psych.52.1.1
  3. Batuk, B., Aktu, Y., & Türk, N. (2025). Yapay zeka kabul ölçeği kısa formu’nun psikometrik özelliklerinin incelenmesi. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 34 (Uygarlığın Dönüşümü: Yapay Zekâ), 438–451. https://doi.org/10.35379/cusosbil.1695975
  4. Blau, P. (1964). Exchange and power in social life. Wiley.
  5. Bjureberg, J., Ljótsson, B., Tull, M. T., Hedman, E., Sahlin, H., Lundh, L.-G., Bjärehed, J., DiLillo, D., Messman-Moore, T., Gumpert, C. H., & Gratz, K. L. (2016). Development and validation of a brief version of the Difficulties in Emotion Regulation Scale: The DERS-16. Journal of Psychopathology and Behavioral Assessment, 38(2), 284–296. https://doi.org/10.1007/s10862-015-9514-x
  6. Carmeli, A., Reiter-Palmon, R., & Ziv, E. (2010). Inclusive leadership and employee involvement in creative tasks in the workplace: The mediating role of psychological safety. Creativity Research Journal, 22(3), 250–260. https://doi.org/10.1080/10400419.2010.504654
  7. Çelik, Ç., & Polat, S. (2023). Kapsayıcı liderlik ölçeğinin türkçeye uyarlanması. Journal of Higher Education and Science, 13(2), 303–308. https://doi.org/10.5961/higheredusci.1085320
  8. Cutuli, D. (2014). Cognitive reappraisal and expressive suppression strategies role in the emotion regulation: an overview on their modulatory effects and neural correlates. Frontiers in Systems Neuroscience, 8. https://doi.org/10.3389/fnsys.2014.00175
  9. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
  10. Edmondson, A. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44(2), 350–383. https://doi.org/10.2307/2666999
  11. Flavián, C., Pérez-Rueda, A., Belanche, D., & Casaló, L. V. (2022). Intention to use analytical artificial intelligence (AI) in services – the effect of technology readiness and awareness. Journal of Service Management, 33(2), 293–320. https://doi.org/10.1108/JOSM-10-2020-0378
  12. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
  13. Glikson, E., & Woolley, A. W. (2020). Human trust in artificial intelligence: review of empirical research. Academy of Management Annals, 14(2), 627–660. https://doi.org/10.5465/annals.2018.0057
  14. Gratz, K. L., & Roemer, L. (2004). Multidimensional assessment of emotion regulation and dysregulation: development, factor structure, and initial validation of the difficulties in emotion regulation scale. Journal of Psychopathology and Behavioral Assessment, 26(1), 41–54. https://doi.org/10.1023/B:JOBA.0000007455.08539.94
  15. Gross, J. J. (1998). The emerging field of emotion regulation: an integrative review. Review of General Psychology, 2(3), 271–299. https://doi.org/10.1037/1089-2680.2.3.271
  16. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd Edition). Sage Publications Inc.
  17. Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems, 116(1), 2–20. https://doi.org/10.1108/IMDS-09-2015-0382
  18. Jian, J.-Y., Bisantz, A. M., & Drury, C. G. (2000). Foundations for an Empirically Determined Scale of Trust in Automated Systems. International Journal of Cognitive Ergonomics, 4(1), 53–71. https://doi.org/10.1207/S15327566IJCE0401_04
  19. Kanoğlu, M. F., & Durak, H. S. (2025). Yapay Zekâya Uyum Ölçeği (YZYÖ): Geçerlik ve güvenirlik çalışması. Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi, 242–259.
  20. Lee, J. D., & See, K. A. (2004). Trust in Automation: Designing for Appropriate Reliance. Human Factors: The Journal of the Human Factors and Ergonomics Society, 46(1), 50–80. https://doi.org/10.1518/hfes.46.1.50_30392
  21. Nembhard, I. M., & Edmondson, A. C. (2006). Making it safe: the effects of leader inclusiveness and professional status on psychological safety and improvement efforts in health care teams. Journal of Organizational Behavior, 27(7), 941–966. https://doi.org/10.1002/job.413
  22. Verburg, R. M., Nienaber, A.-M., Searle, R. H., Weibel, A., Den Hartog, D. N., & Rupp, D. E. (2018). The role of organizational control systems in employees’ organizational trust and performance outcomes. Group & Organization Management, 43(2), 179–206. https://doi.org/10.1177/1059601117725191
  23. Yener, S. (2015). Psikolojik Rahatlık Ölçeğinin Türkçe Formunun Geçerlik ve Güvenirlik Çalışması. Ordu Üniversitesi Sosyal Bilimler Enstitüsü Sosyal Bilimler Araştırmaları Dergisi, 5(13), 280–305.
  24. Yiğit, İ., & Guzey Yiğit, M. (2019). Psychometric properties of turkish version of Difficulties in Emotion Regulation Scale-Brief Form (DERS-16). Current Psychology, 38(6), 1503–1511. https://doi.org/10.1007/s12144-017-9712-7