حسینی، ر.، احمدی، ن.، و جعفری، ف. (۱۴۰۰). شناسایی چالشهای پیادهسازی سیستمهای هوشمند منابع انسانی در سازمانهای ایرانی. فصلنامه مدیریت توسعه انسانی، ۱۲(۴)، 77–98.
صادقی، م.، کریمی، ع.، و زارعی، ح. (۱۴۰۱). طراحی الگوی هوشمندسازی مدیریت منابع انسانی مبتنی بر تحلیل دادههای سازمانی. فصلنامه مدیریت منابع انسانی در صنعت نفت، ۱۴(۳)، 45–68.
موسوی، س.، و رحیمی، م. (۱۴۰۲). کاربرد یادگیری ماشین در پیشبینی عملکرد کارکنان سازمانهای دانشبنیان. فصلنامه پژوهشهای مدیریت منابع انسانی، ۱۵(۲)، 113–136.
Aeon, B., & Aguinis, H. (2017). It’s about time: New perspectives and insights on time management. Academy of Management Perspectives, 31(4), 309–330. https://doi.org/10.5465/amp.2016.0166
Al Akasheh, M., Malik, E. F., Hujran, O., & Zaki, N. (2024). A decade of research on machine learning techniques for predicting employee turnover: A systematic literature review. Expert Systems with Applications, 238, 121794. https://doi.org/10.1016/j.eswa.2023.121794
Al Dwaikat, M., Ayupp, K., & Alolabi, Y. A. (2022). Performance Monitoring and Knowledge Worker Productivity. International Journal of Academic Research in Business and Social Sciences, 12(7), 386–406. https://doi.org/10.6007/IJARBSS/v12-i7/14164
Alam, M. M., & Priya, P. (2025). Data mining techniques for employee empowerment: Insights and approaches. International Journal of Innovative Research in Science, Engineering and Technology, 14(2), 1274–1279. Retrieved from https://www.ijirset.com/upload/2025/february/33_Data.pdf
Anseel, F., Beatty, A. S., Shen, W., Lievens, F., & Sackett, P. R. (2015). How are we doing after 30 years? A meta-analytic review of the antecedents and outcomes of feedback-seeking behavior. Journal of Management, 41(1), 318–348. https://doi.org/10.1177/0149206313484521
Bailey, C., Madden, A., Alfes, K., & Fletcher, L. (2018). The meaning, antecedents and outcomes of employee engagement: A narrative synthesis. International Journal of Management Reviews, 20(1), 31–53. https://doi.org/10.1111/ijmr.12077
Bartram, T., Fan, D., & Gong, Y. (2025). The Future of AI in HR: Collaboration or Replacement? The International Journal of Human Resource Management, 36(5), 801–826. https://doi.org/10.1080/09585192.2025.xxxxxx
Becker, G. S. (1964). Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education. University of Chicago Press.
Berry, C. M., Ones, D. S., & Sackett, P. R. (2007). Interpersonal deviance, organizational deviance, and their common correlates: A review and meta-analysis. Journal of Applied Psychology, 92(2), 410–424. https://doi.org/10.1037/0021-9010.92.2.410
Bogers, M., Chesbrough, H., & Moedas, C. (2018). Open innovation: Research, practices, and policies. California Management Review, 60(2), 5–16. https://doi.org/10.1177/0008125617745086
Bositkhanova, N., & Dadaboyev, S. M. U. (2025). Revolutionizing workforce planning: The strategic role of AI in HR strategy. Discover Global Society, 3(1), Article 100. https://doi.org/10.1007/s44282-025-00252-y
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Carpenter, N. C., Berry, C. M., & Houston, L. (2014). A meta‐analytic comparison of self‐reported and other‐reported organizational citizenship behavior. Journal of Organizational Behavior, 35(4), 547–574. https://doi.org/10.1002/job.1909
Căvescu, A. M., & Popescu, N. (2025). Predictive Analytics in Human Resources Management: Evaluating AIHR’s Role in Talent Retention. AppliedMath, 5(3), 99. https://doi.org/10.3390/appliedmath5030099
Critical Appraisal Skills, P. (2018). CASP Qualitative Checklist.
De Jong, B. A., Dirks, K. T., & Gillespie, N. (2016). Trust and team performance: A meta-analysis of main effects, moderators, and covariates. Journal of Applied Psychology, 101(8), 1134–1150. https://doi.org/10.1037/apl0000110
Drucker, P. F. (1993). Post-Capitalist Society. HarperBusiness.
Fetters, M. D., Curry, L. A., & Creswell, J. W. (2013). Achieving integration in mixed methods designs — principles and practices. Health Services Research, 48(6 Pt 2), 2134–2156. https://doi.org/10.1111/1475-6773.12117
Frazier, M. L., Fainshmidt, S., Klinger, R. L., Pezeshkan, A., & Vracheva, V. (2017). Psychological safety: A meta-analytic review and extension. Personnel Psychology, 70(1), 113–165. https://doi.org/10.1111/peps.12183
Gerber, M., Krause, A., Probst, J., & Heimann, M. (2024). HR analytics between ambition and reality: Current state and recommendations for the contribution of work and organizational psychology. Gruppe. Interaktion. Organisation, 55(2), 225–236. https://doi.org/10.1007/s11612-024-00743-7
Giermindl, L. M., Strich, F., Christ, O. (2022). The dark sides of people analytics: reviewing the perils for organisations and employees. European Journal of Information Systems, 31(3), 410–435. https://doi.org/10.1080/0960085X.2021.1927213
Giermindl, L. M., Strich, F., Christ, O., Leicht-Deobald, U., & Redzepi, A. (2022). The dark sides of people analytics: Reviewing the perils for organisations and employees. European Journal of Information Systems, 31(3), 410–435. https://doi.org/10.1080/0960085X.2021.1927213
Gong, Q., Fan, D., & Bartram, T. (2024). Integrating artificial intelligence and human resource management: A review and future research agenda. International Journal of Human Resource Management, 36(1), 103–141. https://doi.org/10.1080/09585192.2024.2440065
Gonzalez-Mulé, E., Cockburn, B. S., McCormick, B. W., & Zhao, P. (2020). Team tenure and team performance: A meta-analysis and process model. Personnel Psychology, 73(1), 151–198. https://doi.org/10.1111/peps.12319
Han, S., Zhang, D., Zhang, H., & Lin, S. (2025). Artificial intelligence technology, organizational learning capability, and corporate innovation performance: Evidence from Chinese specialized, refined, unique, and innovative enterprises. Sustainability, 17(6), 2510. https://doi.org/10.3390/su17062510
He, Y., Donnellan, M. B., & Mendoza, A. M. (2019). Five‐factor personality domains and job performance: A second‐order meta‐analysis. Journal of Research in Personality, 82, 103848. https://doi.org/10.1016/j.jrp.2019.103848
Huang, M.-H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155–172. https://doi.org/10.1177/1094670517752459
Huffcutt, A. I., & Murphy, S. A. (2023). Structured interviews: moving beyond mean validity and addressing subgroup differences. Industrial and Organizational Psychology, 16(3), 344–348. https://doi.org/10.1017/iop.2023.42
Huffcutt, A. I., & Murphy, S. A. (2023). Structured interviews: Moving beyond mean validity and addressing subgroup differences. Industrial and Organizational Psychology, 16(3), 344–348. https://doi.org/10.1017/iop.2023.42
Lau, W.-M., Chan, K.-Y., Sun, R., & Cheng, G. H.-L. (2023). Predictive validity of integrity tests for workplace deviance... Australian Journal of Management, 48(4), 731–758. https://doi.org/10.1177/18344909231171729
Leblanc, P.-M., Harvey, J.-F., & Rousseau, V. (2024). A meta-analysis of team reflexivity... Human Resource Management Review, 34(3), 101042. https://doi.org/10.1016/j.hrmr.2024.101042
Li, N., Liang, J., & Crant, J. M. (2010). The role of proactive personality in job satisfaction and OCB... Journal of Applied Psychology, 95(2), 395–404. https://doi.org/10.1037/a0018079
Marlow, S. L., Lacerenza, C. N., & Salas, E. (2017). Communication in virtual teams... Human Resource Management Review, 27(4), 575–589. https://doi.org/10.1016/j.hrmr.2016.12.005
Miao, C., Humphrey, R. H., & Qian, S. (2017). A meta-analysis of emotional intelligence... Journal of Occupational and Organizational Psychology, 90(2), 177–202. https://doi.org/10.1111/joop.12167
Miao, Y., Wang, J., Shen, R., & Wang, D. (2023). Effects of Big Five, HEXACO, and Dark Triad on CWB... International Journal of Mental Health Promotion, 25(3), 357–374. https://doi.org/10.32604/ijmhp.2023.027950
Najjar, A., Amro, B., & Macedo, M. (2021). An intelligent decision support system for recruitment... Informatica, 45(4), 617–623. https://doi.org/10.31449/inf.v45i4.3356
Nonaka, I., & Takeuchi, H. (2021). The wise company: How companies create continuous innovation. Oxford University Press.
Okoli, C., & Pawlowski, S. D. (2004). The Delphi method as a research tool... Information & Management, 42(1), 15–29. https://doi.org/10.1016/j.im.2003.11.002
Ramachandran, R., Babu, V., & Murugesan, V. P. (2023). Human resource analytics revisited... Benchmarking: An International Journal. https://doi.org/10.1108/BIJ-04-2022-0272
Ramachandran, R., Babu, V., & Murugesan, V. P. (2023). Human resource analytics revisited: A systematic literature review and research agenda. Benchmarking: An International Journal. https://doi.org/10.1108/BIJ-04-2022-0272
Rockstuhl, T., Ang, S., Ng, K.-Y., Lievens, F., & Van Dyne, L. (2015). Putting judging situations into SJTs... Journal of Applied Psychology, 100(2), 464–480. https://doi.org/10.1037/a0038098
Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. New York, NY: Guilford Press.
Sackett, P. R., Zhang, C., Berry, C. M., & Lievens, F. (2022). Revisiting meta-analytic estimates of validity... Journal of Applied Psychology, 107(11), 2040–2068. https://doi.org/10.1037/apl0000994
Sackett, P. R., Zhang, C., Berry, C. M., & Lievens, F. (2022). Revisiting meta-analytic estimates of validity in personnel selection: Addressing systematic overcorrection for range restriction. Journal of Applied Psychology, 107(11), 2040–2068. https://doi.org/10.1037/apl0000994
Sandelowski, M., & Barroso, J. (2007). Handbook for synthesizing qualitative research. Springer Publishing Company.
Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods... Psychological Bulletin, 124(2), 262–274. https://doi.org/10.1037/0033-2909.124.2.262
Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124(2), 262–274. https://doi.org/10.1037/0033-2909.124.2.262
Selvamohana, K., Sahu, S. R., Singh, S., Mohanraj, S., & Sharma, A. (2025). From HR Analytics to AI-Driven HRM: Enhancing organizational efficiency through data-driven decision-making. Journal of Information Systems Engineering & Management, 10(21s). https://doi.org/10.52783/jisem.v10i21s.3395
Shalley, C. E., Hitt, M. A., & Zhou, J. (Eds.). (2015). The Oxford Handbook of Creativity, Innovation, and Entrepreneurship. Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199927678.001.0001
Stasielowicz, Ł. (2019). Goal orientation and performance adaptation: A meta-analysis. Journal of Research in Personality, 83, 103847. https://doi.org/10.1016/j.jrp.2019.103847
Stone, K. (2024, December 16). 7 trends redefining HR analytics for 2025. Diversio. Retrieved March 15, 2025, from https://diversio.com/hr-analytics-trends/
Tan, P.-N., Steinbach, M., & Kumar, V. (2019). Introduction to Data Mining. Pearson.
Tănăsescu, L. G., Vines, A., Bologa, A. R., & Vîrgolici, O. (2024). Data analytics for optimizing and predicting employee performance. Applied Sciences, 14(8), 3254. https://doi.org/10.3390/app1408325
Teece, D. J. (2016). Dynamic capabilities and entrepreneurial management in large organizations: Toward a theory of the (entrepreneurial) firm. European Economic Review, 86(C), 202–216. https://doi.org/10.1016/j.euroecorev.2015.11.006
Thakral, P., Srivastava, P. R., Dash, S., Jasimuddin, S. M., & Zhang, Z. (2023). Trends in the thematic landscape of HR analytics research... Management Decision, 61(12), 3665–3690. https://doi.org/10.1108/MD-01-2023-0080
Wandhe, P. (2025). HR Analytics and the Employee Lifecycle: From Onboarding to Exit. SSRN. https://doi.org/10.2139/ssrn.5096405
Wang, S., & Noe, R. A. (2010). Knowledge sharing: A review and directions for future research. Human Resource Management Review, 20(2), 115–131. https://doi.org/10.1016/j.hrmr.2009.10.001
Wilmot, M. P., & Ones, D. S. (2019). A century of research on conscientiousness at work. Proceedings of the National Academy of Sciences, 116(46), 23004–23010. https://doi.org/10.1073/pnas.1908430116
