منابع
حاجی‌وند، امین؛ خوش‌منظر، علی و سیاری زهان، صابر (1402). تاریخچه مختصری از هوش مصنوعی: گذشته، حال و آینده هوش مصنوعی. فصلنامه تمدن حقوقی، 6(18)، 73-90.
حمزوی، حسین؛ صالحی صدقیانی، جمشید و نجفی، فاطمه (1404). بازشناسی و رتبه‌بندی پیشران‌های بهینه‌سازی و توسعه عملکرد زیست‌محیطی پالایشگاه‌های نفت و گاز ج.ا.ایران با رهیافت آینده‌نگاری راهبردی. فصلنامه علمی مدیریت محیط زیست شهری، 3(1)، 34-55.
داداشی حاجی، مهدی؛ اکبرزاده، علیرضا؛ میرزایی، مهدی و قنبری، وحید (1403). کاربردهای تاب‌آوری شناختی کارکنان نظامی در برابر استرس روانی ـ مطالعه مروری. مدیریت سرمایه انسانی دفاعی، 4(3)، 138- 169.
دوله، معصومه و شجاعی، مسلم (1401). تأثیر رهبری اخلاقی بر فرسودگی شغلی با تأکید بر نقش واسطه‌ای سرمایه اجتماعی و روان‌شناختی (مورد مطالعه: معلمان شهرستان بهبهان). برنامه‌ریزی رفاه و توسعه اجتماعی، 13(53)، 51- 85.
زارعی متین، حسن؛ ونکی فراهانی، محمد؛ اخوان علوی، سید حسین؛ ذاکری‌فر، مهدی و محمدیان، بهزاد (1404). بازشناسی سازوکارهای شناختی تاب‌آوری: رویکرد فلسفی. پژوهش‌های روان‌شناختی در مدیریت، 11(3)، 151-182.
عباسی، رسول و اسماعیلی، محدثه (1403). هوش مصنوعی و فرایندهای منابع انسانی دیجیتال: کاربردها و چالش‌ها. مطالعات منابع انسانی، 14(1)، 116-140.
محمدی، رضا و خرسندی یامچی، اکبر (1404). ارائه مدل ساختاری عوامل مؤثر بر فرسودگی شغلی معلمان ابتدایی. پژوهش‌های رهبری آموزشی، 9(35)، 157-185.
References
Abbasi, R. & Esmaili, M. (2024). Artificial intelligence and digital human resource processes: Applications and challenges. Journal of Human Resource Management, 14(1), 116–140. https://doi.org/10.22034/jhrs.2024.195965 (in Persian)
Al Mudhafar, W., Al Yaseri, A. & Jasim, N. (2023). Artificial intelligence enabled predictive maintenance in oil and gas operations. Journal of Petroleum Science and Engineering, 224, Article 111540. https://doi.org/10.1016/j.petrol.2023.111540
Alzubaidi, L., Zhang, J. & Duan, Y. (2021). Internet of things in the oil and gas industry: A comprehensive review. IEEE Access, 9, 22385–22400. https://doi.org/10.1109/ACCESS.2021.3054505
Annosi, M. C., Brunetta, F., Bimbo, F. & Kostoula, M. (2021). Digitalization within food supply chains to prevent food waste: Drivers, barriers and collaboration practices. Industrial Marketing Management, 93, 208–220. https://doi.org/10.1016/j.indmarman.2020.12.013
Asadi Aghajari, M., Fazlizade, S., Hashemzadeh, E., Ojaghloo, M., Ghanbari‑Afra, L., Ghahremani, Z. & Abdi, M. (2024). The relationship between occupational stress and depression in emergency medical technicians: Post‑corona consideration. Evidence Based Care, 13(4), 18–27. https://doi.org/10.22038/ebcj.2023.72752.2765
Bai, C., Dallasega, P., Orzes, G. & Sarkis, J. (2020). Industry 4.0 technologies assessment: A sustainability perspective. International Journal of Production Economics, 229, Article 107776. https://doi.org/10.1016/j.ijpe.2020.107776
Brady, M. & Jayawickreme, E. (2025). A philosophical approach to improving empirical research on posttraumatic growth. Philosophical Psychology, 38(2), 796–819. https://doi.org/10.1080/09515089.2024.2331424
Campbell‑Sills, L. & Stein, M. B. (2007). Psychometric analysis and refinement of the Connor–Davidson resilience scale (CD‑RISC). Journal of Traumatic Stress, 20(6), 1019–1028. https://doi.org/10.1002/jts.20271
Carvalho, T. P., Soares, F. A. A. M. N., Vita, R., Francisco, R. P., Basto, J. P. & Alcalá, S. G. S. (2019). A systematic literature review of machine learning methods applied to predictive maintenance. Computers & Industrial Engineering, 137, Article 106024. https://doi.org/10.1016/j.cie.2019.106024
Chakraborty, A. & Singh, P. (2022). Correlates of burnout among Indian primary school teachers. International Journal of Organizational Analysis, 30(2), 589–605. https://doi.org/10.1108/IJOA-08-2020-2379
Connor, K. M. & Davidson, J. R. T. (2003). Development of a new resilience scale: The Connor–Davidson resilience scale (CD‑RISC). Depression and Anxiety, 18(2), 76–82. https://doi.org/10.1002/da.10113
Dadashi Haji, M., Akbarzade, A., Mirzaei, M. & Ghanbari, V. (2024). The applications of cognitive resilience of military personnel on psychological stress: A narrative review. Defense-Human Capital Management, 4(3), 138–169. https://doi.org/10.22034/jdhcm.2024.2045484.1125 (in Persian)
Dowleh, M. & Shojae, M. (2022). Investigating the effect of ethical leadership on occupational burnout with emphasis on the mediating role of social and psychological capital. Social Development & Welfare Planning, 13(53), 51–85. https://doi.org/10.22054/qjsd.2022.64446.2267 (in Persian)
Duraku, Z., Jahiu, G. & Geci, D. (2025). The interplay of individual and organizational factors with early childhood teachers’ work motivation, job satisfaction, and burnout. International Journal of Educational Reform, 34(1), 106–121. https://doi.org/10.1177/10567879231187948
Garcia, M. & Steins, R. (2022). Remote monitoring and predictive maintenance in oil and gas operations using IoT and machine learning. Journal of Petroleum Science and Engineering, 210, Article 109883. https://doi.org/10.1016/j.petrol.2021.109883
Haghnegahdar, L., Joshi, S. S. & Dahotre, N. B. (2022). From IoT‑based cloud manufacturing approach to intelligent additive manufacturing: Industrial Internet of Things—An overview. The International Journal of Advanced Manufacturing Technology, 119(3–4), 1461–1478. https://doi.org/10.1007/s00170-021-08396-7
Hajivand, A., Khosh Manzar, A. & Sayari Zuhan, S. (2024). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. Fares Law Research, 6(18), 73–90. https://doi.org/10.22034/lc.2024.409037.1379 (in Persian)
Hamzavi, H., Salehi Sadaghyani, J. & Najafi, F. (2025). Identifying and ranking the drivers of environmental performance optimization and development of oil and gas refineries in the Republic of Iran using a strategic foresight approach. Journal of Urban Environmental Management, 3(1), 34–55. https://doi.org/10.48306/juem.2025.523414.1073 (in Persian)
Hsiao, C. H. & Lee, W. P. (2021). OPIIoT: Design and implementation of an open communication protocol platform for industrial Internet of Things. Internet of Things, 16, Article 100441. https://doi.org/10.1016/j.iot.2021.100441
Jafari, M. & Boughzala, I. (2023). Artificial intelligence applications for reducing operational workload in high‑risk industries. Safety Science, 160, Article 106023. https://doi.org/10.1016/j.ssci.2023.106023
Kawadler, J. M., Hemmings, N. R., Ponzo, S., Morelli, D., Bird, G. & Plans, D. (2020). Effectiveness of a smartphone app (BioBase) for reducing anxiety and increasing mental well‑being. JMIR Formative Research, 4(11), Article e18067. https://doi.org/10.2196/18067
Khan, S., Javaid, M., Haleem, A. & Suman, R. (2024). Industrial digital monitoring systems and safety management in smart industries. Safety Science, 171, Article 106508. https://doi.org/10.1016/j.ssci.2024.106508
Kim, H. & Marcouiller, D. W. (2021). Rural prospects for resilience: Planning sustainable livelihoods and coping with flood hazards along the US Mississippi River. Society & Natural Resources, 34(2), 168–187. https://doi.org/10.1080/08941920.2020.1819342
Küçükali, H., Türkoğlu, S. N., Hasanli, S., Çok, F. N. D., Culpan, H. C. & Hayran, O. (2023). Comparison of burnout among medical residents before and during the pandemic. Journal of Psychosomatic Research, 165, Article 111118. https://doi.org/10.1016/j.jpsychores.2022.111118
Leiter, M. P. & Maslach, C. (2022). Areas of worklife: A structured approach to organizational predictors of job burnout. Burnout Research, 25, Article 100494. https://doi.org/10.1016/j.burn.2022.100494
Markov, K. & Vitliemov, P. (2020). Logistics 4.0 and supply chain 4.0 in the automotive industry. IOP Conference Series: Materials Science and Engineering, 878, Article 012047. https://doi.org/10.1088/1757-899X/878/1/012047
Maslach, C., Jackson, S. E. & Leiter, M. P. (2018). Maslach burnout inventory manual (4th ed.). Mind Garden. https://doi.org/10.1037/t03589-000
Mohamadi, R. & Khorsandi Yamchi, A. (2025). A structural equation model of factors influencing on the elementary teachers’ job burnout. Educational Leadership Research, 9(35), 157–185. https://doi.org/10.22054/jrlat.2025.82725.1801 (in Persian)
Rad, F. F., Oghazi, P., Palmié, M., Chirumalla, K., Pashkevich, N., Patel, P. C. & Sattari, S. (2022). Industry 4.0 and supply chain performance: A systematic literature review. Industrial Marketing Management, 105, 268–293. https://doi.org/10.1016/j.indmarman.2022.06.016
Raza, M., Ahmad, W. & Patel, P. (2023). Remote monitoring and predictive analytics in Industry 4.0 environments. IEEE Access, 11, 88964–88977. https://doi.org/10.1109/ACCESS.2023.3302146
Robertson, I., Cooper, C., Sarkar, M. & Curran, T. (2023). Resilience training in the workplace and its impact on stress and burnout. Journal of Organizational Behavior. https://doi.org/10.1002/job.2667
Santos, R., Ferreira, P. & Costa, A. (2024). Digital transformation and worker well‑being in industrial environments. Computers & Industrial Engineering, 187, Article 109998. https://doi.org/10.1016/j.cie.2023.109998
Tarafdar, M., Pullins, E. B. & Ragu‑Nathan, T. S. (2022). Technostress: Negative effect on performance and possible mitigations. Journal of Service Research, 25(1), 7–22. https://doi.org/10.1177/10946705211018835
Tsang, K. K., Wang, G. & Bai, H. (2022). Enabling school bureaucracy, psychological empowerment, and teacher burnout. Sustainability, 14(4), Article 2047. https://doi.org/10.3390/su14042047
Yang, C., Chan, M. K., Lin, X. & Chen, C. (2022). Teacher victimization and teacher burnout. Journal of School Violence, 21(2), 206–221. https://doi.org/10.1080/15388220.2021.2016138
Yigitcanlar, T. & Cugurullo, F. (2020). The sustainability of artificial intelligence: An urbanistic viewpoint from the lens of smart and sustainable cities. Sustainability, 12(20), Article 8548. https://doi.org/10.3390/su12208548
Zareei Matin, H., Vanaki Farahani, M., Akhavan Alavi, H., Zakerifar, M. & Mohammadian, B. (2025). Recognizing cognitive mechanisms of resilience: Philosophical approach. Psychological Research in Management, 11(3), 151–182. https://doi.org/10.22034/jom.2025.2066559.1373 (in Persian)
Zhang, L., Wang, S. & Chen, Y. (2023). Industrial digitalization for operational efficiency and risk reduction. Journal of Industrial Information Integration, 35, Article 100423. https://doi.org/10.1016/j.jii.2023.100423
Zhao, X., Li, Y. & Wang, J. (2023). Remote monitoring technologies for industrial equipment maintenance: A review. Journal of Manufacturing Systems, 68, 412–425. https://doi.org/10.1016/j.jmsy.2023.05.012
