الگوی هوشمندی مدیریت منابع انسانی مبتنی بر علم داده و یادگیری ماشینی

معروفی، یحیی و یوسف زاده، محمد رضا (1388) . تحلیل محتوا درعلوم انسانی. همدان: سـپهر دانش.

Ajit, P. (2016) . Prediction of employee turnover in organizations using machine learning algorithms. algorithms, 4 (5) , C5.

Albert, E. T. (2019) . AI in talent acquisition: a review of AI-applications used in recruitment and selection. Strategic HR Review. https://doi.org/10.1108/SHR-04-2019-0024

Bach, M. P., Simic, N., & Merkac, M. (2013) . Forecasting employees' success at work in banking: could psychological testing be used as the crystal ball? Managing Global Transitions, 11 (3) , 283.

Bassi, L., & McMurrer, D. (2016) . Four lessons learned in how to use human resource analytics to improve the effectiveness of leadership development. Journal of leadership studies, 10 (2) , 39-43. https://doi.org/10.1002/jls.21471

Basu, A. T. A. N. U. (2013) . Five pillars of prescriptive analytics success, Analytics magazine, 8-12.

Benabderrahmane, S., Mellouli, N., & Lamolle, M. (2018) . On the predictive analysis of behavioral massive job data using embedded clustering and deep recurrent neural networks. Knowledge-Based Systems, 151, 95-113. https://doi.org/10.1016/j.knosys.2018.03.025

Ben-Gal, H. C. (2019) . An ROI-based review of HR analytics: practical implementation tools. Personnel Review. https://doi.org/10.1108/PR-11-2017-0362

Bohlouli, M., Mittas, N., Kakarontzas, G., Theodosiou, T., Angelis, L., & Fathi, M. (2017) . Competence assessment as an expert system for human resource management: A mathematical approach. Expert Systems with Applications, 70, 83-102. https://doi.org/10.1016/j.eswa.2016.10.046

Braun, V., & Clarke, V. (2006) . Using thematic analysis in psychology. Qualitative research in psychology, 3 (2) , 77-101. DOI: 10.1191/1478088706qp063oa

Brock, J. K. U., & Von Wangenheim, F. (2019) . Demystifying AI: What Digital Transformation Leaders Can Teach You about Realistic Artificial Intelligence. California Management Review, 61 (4) , 110-134. https://doi.org/10.1177/1536504219865226

Chen, J., Yun, C., & Wang, Z. (2009, December) . Multi-dimensional model method for the human resource allocation in multi-project. In 2009 International Conference on Information Management, Innovation Management and Industrial Engineering (Vol. 4, pp. 364-366) . IEEE. DOI: 10.1109/ICIII.2009.547

Chien, C. F., & Chen, L. F. (2008) . Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry. Expert Systems with applications, 34 (1) , 280-290. https://doi.org/10.1016/j.eswa.2006.09.003

Davenport, T. H., Harris, J., & Shapiro, J. (2010) . Competing on talent analytics. Harvard business review, 88 (10) , 52-58.

Dhar, V. (2013) . Data science and prediction. Communications of the ACM, 56 (12) , 64-73. https://doi.org/10.1145/2500499

Dong, K. (2021) . Optimization of enterprise human resource management model based on Fama–French model and intelligent algorithm. Journal of Ambient Intelligence and Humanized Computing, 1-13. https://doi.org/10.1007/s12652-021-03210-z

Faliagka, E., Iliadis, L., Karydis, I., Rigou, M., Sioutas, S., Tsakalidis, A., & Tzimas, G. (2014) . On-line consistent ranking on e-recruitment: seeking the truth behind a well-formed CV. Artificial Intelligence Review, 42 (3) , 515-528. https://doi.org/10.1007/s10462-013-9414-y

Fan, C. Y., Fan, P. S., Chan, T. Y., & Chang, S. H. (2012) . Using hybrid data mining and machine learning clustering analysis to predict the turnover rate for technology professionals. Expert Systems with Applications, 39 (10) , 8844-8851. https://doi.org/10.1016/j.eswa.2012.02.005

Feinzig S (2018) AI in HR: have you started your journey? https://www.ibm.com/smarter-workforce/ai-in-hr-have-you-started-yourjourney. Accessed 03 May 2019

Garg, S., Sinha, S., Kar, A. K., & Mani, M. (2021) . A review of machine learning applications in human resource management. International Journal of Productivity and Performance Management. https://doi.org/10.1108/IJPPM-08-2020-0427

Gartner (2012) . Big Data Strategy Components: IT Essentials. Published on 15th October 2012.

Gelbard, R., Ramon‐Gonen, R., Carmeli, A., Bittmann, R. M., & Talyansky, R. (2018) . Sentiment analysis in organizational work: Towards an ontology of people analytics. Expert Systems, 35 (5) , e12289.

Gromov, A. Y., Petrovskaia, T. A., Suslina, A. A., Khizriyeva, N. I., & Stepanov, M. A. (2018, June) . Human resources intelligent selection algorithm with improvement of data validity. In 2018 7th Mediterranean Conference on Embedded Computing (MECO) (pp. 1-4) . IEEE. DOI: 10.1109/MECO.2018.8406036

Gui, X., Hu, Z., Zhang, J., & Bao, Y. (2014, July) . Assessing personal performance with M-SVMs. In 2014 Seventh International Joint Conference on Computational Sciences and Optimization (pp. 598-601) . IEEE. DOI: 10.1109/CSO.2014.115

Hampornchai, N., Chakpitak, N., Chandarasupsang, T., Chaikijkosi, T. A., & Dahal, K. (2007, September) . Dynamic adjustment of age distribution in Human Resource Management by genetic algorithms. In 2007 IEEE Congress on Evolutionary Computation (pp. 1234-1239) . IEEE. DOI: 10.1109/CEC.2007.4424611

Harris, J. G., Craig, E., & Light, D. A. (2011) . Talent and analytics: new approaches, higher ROI. Journal of Business Strategy. https://doi.org/10.1108/02756661111180087

Hota, J., & Ghosh, D. (2013) . Workforce analytics approach: An emerging trend of workforce management. AIMS International Journal, 7 (3) , 167-179. Available at SSRN: https://ssrn.com/abstract=2194987. https://doi.org/10.1111/exsy.12289

Huang, M., & Mou, R. (2010, August) . Improvement on the genetic algorithm and its application in employee performance evaluation. In 2010 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE) (Vol. 4, pp. V4-253) . IEEE. DOI: 10.1109/ICACTE.2010.5579839

Huang, Y. (2009, July) . Study of college human resources data mining based on the SOM algorithm. In 2009 Asia-Pacific Conference on Information Processing (Vol. 1, pp. 324-327) . IEEE. DOI: 10.1109/APCIP.2009.89

Huselid, M. A. (2018) . The science and practice of workforce analytics: Introduction to the HRM special issue. Human Resource Management, 57 (3) , 679-684. https://doi.org/10.1002/hrm.21916

Jantan, H., Hamdan, A. R., & Othman, Z. A. (2009, October) . Classification for talent management using decision tree induction techniques. In 2009 2nd Conference on Data Mining and Optimization (pp. 15-20) . IEEE. DOI: 10.1109/DMO.2009.5341916

Jantan, H., Hamdan, A. R., & Othman, Z. A. (2011, June) . Talent knowledge acquisition using data mining classification techniques. In 2011 3rd Conference on Data Mining and Optimization (DMO) (pp. 32-37) . IEEE. DOI: 10.1109/DMO.2011.5976501

Janusz, A., Stawicki, S., Drewniak, M., Ciebiera, K., Ślęzak, D., & Stencel, K. (2018, June) . How to Match Jobs and Candidates-A Recruitment Support System Based on Feature Engineering and Advanced Analytics. In International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (pp. 503-514) . Springer, Cham. DOI: 10.1007/978-3-319-91476-3_42

Jin, F., & Wang, L. (2020, December) . Evaluation and analysis of strategic human resource management based on multi-mode fuzzy logic control algorithm. In 2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE) (pp. 1908-1911) . IEEE.

Jing, H. (2009, December) . Application of fuzzy data mining algorithm in performance evaluation of human resource. In 2009 International Forum on Computer Science-Technology and Applications (Vol. 1, pp. 343-346). IEEE. DOI: 10.1109/IFCSTA.2009.90

Kapoor, B., & Sherif, J. (2012) . Human resources in an enriched environment of business intelligence. Kybernetes: The International Journal of Systems & Cybernetics, 41 (10) , 1625-1637. https://doi.org/10.1108/03684921211276792

Kim, J., Dibrell, C., Kraft, E., & Marshall, D. (2021) . Data analytics and performance: The moderating role of intuition-based HR management in major league baseball. Journal of Business Research, 122, 204-216. https://doi.org/10.1016/j.jbusres.2020.08.057

Kirimi, J. M., & Moturi, C. A. (2016) . Application of data mining classification in employee performance prediction. International Journal of Computer Applications, 146 (7) , 28-35.

Kryscynski, D., Reeves, C., Stice‐Lusvardi, R., Ulrich, M., & Russell, G. (2018). Analytical abilities and the performance of HR professionals. Human Resource Management, 57 (3) , 715-738. https://doi.org/10.1002/hrm.21854

Lan, J., & Xu, S. (2012, October) . The design of algorithm about the system of college talents recruitment. In 2012 3rd International Conference on System Science, Engineering Design and Manufacturing Informatization (Vol. 2, pp. 265-268) . IEEE. DOI: 10.1109/ICSSEM.2012.6340860

Leek, J. (2013) . The key word in ‘data science’is not data, it is science. Simply statistics, 12.

Lepenioti, K., Bousdekis, A., Apostolou, D., & Mentzas, G. (2020) . Prescriptive analytics: Literature review and research challenges. International Journal of Information Management, 50, 57-70. https://doi.org/10.1016/j.ijinfomgt.2019.04.003

Lewicki, A., & Tadeusiewicz, R. (2010, May) . The recruitment and selection of staff problem with an ant colony system. In 3rd International Conference on Human System Interaction (pp. 770-774) . IEEE. DOI: 10.1109/HSI.2010.5514481

Li, C. (2020, November) . Optimization of Human Resources Allocation for Airport Security Check Business Based on Genetic Algorithm. In 2020 2nd International Conference on Economic Management and Model Engineering (ICEMME) (pp. 983-986) . IEEE. DOI: 10.1109/ICEMME51517.2020.00201

Li, T., Yang, Y., & Liu, Z. (2008, December) . An Improved Neural Network Algorithm and Its Application on Enterprise Strategic Management Performance Measurement Based on Kirkpatrick Model. In 2008 Second International Symposium on Intelligent Information Technology Application (Vol. 1, pp. 861-865) . IEEE. DOI: 10.1109/IITA.2008.168

Li, Y. M., Lai, C. Y., & Kao, C. P. (2008) . Incorporate personality trait with support vector machine to acquire quality matching of personnel recruitment. In 4th international conference on business and information (pp. 1-11) .

Liu, Y. (2020, September) . Analysis of Human Resource Management Mode and Its Selection Factors Based on Decision Tree Algorithm. In 2020 International Conference on Advance in Ambient Computing and Intelligence (ICAACI) (pp. 139-142) . IEEE. DOI: 10.1109/ICAACI50733.2020.00035

Maji, K., & Bera, A. B. (2020, February) . Developing a Suitability Index Algorithm for Recruitment. In 2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA) (pp. 1-5) . IEEE. DOI: 10.1109/NCETSTEA48365.2020.9119944

Margherita, A. (2021) . Human resources analytics: A systematization of research topics and directions for future research. Human Resource Management Review, 100795. https://doi.org/10.1016/j.hrmr.2020.100795

Markevich, A. V., & Sidorenko, V. G. (2019, September) . Automating of Human Resources Management using Genetic Algorithms. In 2019 IEEE East-West Design & Test Symposium (EWDTS) (pp. 1-9) . IEEE. DOI: 10.1109/EWDTS.2019.8884478

Marler, J. H., & Boudreau, J. W. (2017) . An evidence-based review of HR Analytics. The International Journal of Human Resource Management, 28 (1) , 3-26. https://doi.org/10.1080/09585192.2016.1244699

Marler, J. H., & Parry, E. (2016) . Human resource management, strategic involvement and e-HRM technology. The International Journal of Human Resource Management, 27 (19) , 2233-2253. https://doi.org/10.1080/09585192.2015.1091980

Marr, B. (2019) . Artificial intelligence in practice: how 50 successful companies used AI and machine learning to solve problems. John Wiley & Sons. ISBN:1119548217, 9781119548218

McIver, D., Lengnick-Hall, M. L., & Lengnick-Hall, C. A. (2018) . A strategic approach to workforce analytics: Integrating science and agility. Business Horizons, 61 (3), 397-407. https://doi.org/10.1016/j.bushor.2018.01.005

Mehta, S., Pimplikar, R., Singh, A., Varshney, L. R., & Visweswariah, K. (2013, March). Efficient multifaceted screening of job applicants. In Proceedings of the 16th International Conference on Extending Database Technology (pp. 661-671). https://doi.org/10.1145/2452376.2452453

Menon, V. M., & Rahulnath, H. A. (2016, September). A novel approach to evaluate and rank candidates in a recruitment process by estimating emotional intelligence through social media data. In 2016 International Conference on Next Generation Intelligent Systems (ICNGIS) (pp. 1-6) . IEEE. DOI: 10.1109/ICNGIS.2016.7854061

Min, H., & Emam, A. (2003) . Developing the profiles of truck drivers for their successful recruitment and retention: a data mining approach. International Journal of Physical Distribution & Logistics Management. https://doi.org/10.1108/09600030310469153

Minbaeva, D. (2017). Human capital analytics: why aren't we there? Introduction to the special issue. Journal of Organizational Effectiveness: People and Performance. https://doi.org/10.1108/JOEPP-04-2017-0035

Nasrabadi, N. M. (2007). Pattern recognition and machine learning. Journal of electronic imaging, 16 (4), 049901. https://doi.org/10.1117/1.2819119

Nicolaescu, S. S., Florea, A., Kifor, C. V., Fiore, U., Cocan, N., Receu, I., & Zanetti, P. (2020). Human capital evaluation in knowledge-based organizations based on big data analytics. Future Generation Computer Systems, 111, 654-667. https://doi.org/10.1016/j.future.2019.09.048

Pessach, D., Singer, G., Avrahami, D., Ben-Gal, H. C., Shmueli, E., & Ben-Gal, I. (2020). Employees recruitment: A prescriptive analytics approach via machine learning and mathematical programming. Decision Support Systems, 134, 113290. https://doi.org/10.1016/j.dss.2020.113290

Qu, X. L. (2015, August). A decision tree applied to the grass-roots staffs' turnover problem—take CR Group as an example. In 2015 IEEE International Conference on Grey Systems and Intelligent Services (GSIS) (pp. 378-382). IEEE. DOI: 10.1109/GSIS.2015.7301886

Ramachandran, K. K., Mary, A. A. S., Hawladar, S., Asokk, D., Bhaskar, B., & Pitroda, J. R. (2021). Machine learning and role of artificial intelligence in optimizing work performance and employee behavior. Materials Today: Proceedings. https://doi.org/10.1016/j.matpr.2021.11.544

Rasmussen, T., & Ulrich, D. (2015). Learning from practice: how HR analytics avoids being a management fad. Organizational Dynamics, 44 (3), 236-242. https://doi.org/10.1016/j.orgdyn.2015.05.008

Reddy, D. J. M., Regella, S., & Seelam, S. R. (2020, October) . Recruitment Prediction using Machine Learning. In 2020 5th International Conference on Computing, Communication and Security (ICCCS) (pp. 1-4) . IEEE.

Ribes, E., Touahri, K., & Perthame, B. (2017). Employee turnover prediction and retention policies design: a case study. arXiv preprint arXiv:1707.01377.
https://doi.org/10.48550/arXiv.1707.01377

Saling, K. C., & Do, M. D. (2020). Leveraging People Analytics for an Adaptive Complex Talent Management System. Procedia Computer Science, 168, 105-111. https://doi.org/10.1016/j.procs.2020.02.269

Saradhi, V. V., & Palshikar, G. K. (2011). Employee churn prediction. Expert Systems with Applications, 38 (3), 1999-2006. https://doi.org/10.1016/j.eswa.2010.07.134

Sharma, A., & Sharma, T. (2017) . HR analytics and performance appraisal system: A conceptual framework for employee performance improvement. Management Research Review. https://doi.org/10.1108/MRR-04-2016-0084

Shehu, M. A., & Saeed, F. (2016) . An adaptive personnel selection model for recruitment using domain-driven data mining. Journal of Theoretical and Applied Information Technology, 91 (1) , 117.

Sikaroudi, E., Mohammad, A., Ghousi, R., & Sikaroudi, A. (2015) . A data mining approach to employee turnover prediction (case study: Arak automotive parts manufacturing) . Journal of industrial and systems engineering, 8 (4) , 106-121. 20.1001.1.17358272.2015.8.4.7.2

Simón, C., & Ferreiro, E. (2018) . Workforce analytics: A case study of scholar–practitioner collaboration. Human Resource Management, 57 (3) , 781-793. https://doi.org/10.1002/hrm.21853

Sisodia, D. S., Vishwakarma, S., & Pujahari, A. (2017, November) . Evaluation of machine learning models for employee churn prediction. In 2017 International Conference on Inventive Computing and Informatics (ICICI) (pp. 1016-1020) . IEEE. DOI: 10.1109/ICICI.2017.8365293

Sivaram, N., & Ramar, K. (2010) . Applicability of clustering and classification algorithms for recruitment data mining. International Journal of Computer Applications, 4 (5) , 23-28. DOI: 10.5120/823-1165 

Sivaram, N., & Ramar, K. (2011) . Knowledge Engineering to aid the recruitment process of an Industry by identifying superior selection criteria. ICTACT Journal on soft computing. DOI: 10.21917/ijsc.2011.0022

Strohmeier, S., & Piazza, F. (2015) . Artificial intelligence techniques in human resource management—a conceptual exploration. In Intelligent techniques in engineering management (pp. 149-172) . Springer, Cham. DOI: 10.1007/978-3-319-17906-3_7

Talerico, C. (2021) HR Analytic Competencies: A Comparison of Developed Versus Developing Country HR Practitioner Skill Sets.

Tursunbayeva, A., Di Lauro, S., & Pagliari, C. (2018). People analytics—A scoping review of conceptual boundaries and value propositions. International Journal of Information Management, 43, 224-247. https://doi.org/10.1016/j.ijinfomgt.2018.08.002

Ulrich, D. (1997) . Human resource champions: The next agenda for adding value and delivering results. Harvard Business Press. ISBN:1422160696, 9781422160695

Valle, M. A., Varas, S., & Ruz, G. A. (2012) . Job performance prediction in a call center using a naive Bayes classifier. Expert Systems with Applications, 39 (11), 9939-9945. https://doi.org/10.1016/j.eswa.2011.11.126

Van den Heuvel, S., & Bondarouk, T. (2016, February) . The rise (and fall) of HR analytics: a study into the future applications, value, structure, and system support. In 2nd HR Division International Conference, HRIC 2016. https://doi.org/10.1108/JOEPP-03-2017-0022

Votto, A. M., Valecha, R., Najafirad, P., & Rao, H. R. (2021). Artificial Intelligence in Tactical Human Resource Management: A Systematic Literature Review. International Journal of Information Management Data Insights, 1 (2), 100047. https://doi.org/10.1016/j.jjimei.2021.100047

Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2021) . Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. The International Journal of Human Resource Management, 1-30. https://doi.org/10.1080/09585192.2020.1871398

Wang, H., Liang, G., & Zhang, X. (2018) . Feature regularization and deep learning for human resource recommendation. IEEE Access, 6, 39415-39421. DOI: 10.1109/ACCESS.2018.2854887

Wang, K. Y., & Shun, H. Y. (2016) . Applying back propagation neural networks in the prediction of management associate work retention for small and medium enterprises. J. Manag, 4, 223-227. DOI: 10.13189/ujm.2016.040501

Wang, S. Q., Gong, L. H., & Yan, S. L. (2009, July) . The allocation optimization of project human resource based on particle swarm optimization algorithm. In 2009 IITA International Conference on Services Science, Management and Engineering (pp. 169-172). IEEE. DOI: 10.1109/SSME.2009.113

Wang, Z., Tang, X., & Chen, D. (2015, August) . A resume recommendation model for online recruitment. In 2015 11th International Conference on Semantics, Knowledge and Grids (SKG) (pp. 256-259). IEEE. DOI: 10.1109/SKG.2015.31

Xiangpeng, G., Wang, J., & Liang, S. (2014, May). Clustering analysis based on adaptive genetic algorithm for performance assessment. In The 26th Chinese Control and Decision Conference (2014 CCDC) (pp. 1682-1686) . IEEE.

Yabanci, O. (2019) . From human resource management to intelligent human resource management: a conceptual perspective. Human-Intelligent Systems Integration, 1 (2) , 101-109. https://doi.org/10.1007/s42454-020-00007-x

Yang, S., Korayem, M., AlJadda, K., Grainger, T., & Natarajan, S. (2017) . Combining content-based and collaborative filtering for job recommendation system: A cost-sensitive Statistical Relational Learning approach. Knowledge-Based Systems, 136, 37-45. https://doi.org/10.1016/j.knosys.2017.08.017

Yao, S., Yi, Z., & Zhang, L. (2015, May) . Researches on the best-fitted talents recommendation algorithm. In The 27th Chinese Control and Decision Conference (2015 CCDC) (pp. 4247-4252) . IEEE. DOI: 10.1109/CCDC.2015.7162676

Yasodha, S., & Prakash, P. S. (2012, March) . Data mining classification technique for talent management using SVM. In 2012 International Conference on Computing, Electronics and Electrical Technologies (ICCEET) (pp. 959-963) . IEEE. DOI: 10.1109/ICCEET.2012.6203768

Ye, P. (2011, July) . The decision tree classification and its application research in personnel management. In Proceedings of 2011 International Conference on Electronics and Optoelectronics (Vol. 1, pp. V1-372) . IEEE.

Zhang, H. (2009, December) . Fuzzy evaluation on the performance of human resources management of commercial banks based on improved algorithm. In 2009 2nd international conference on power electronics and intelligent transportation system (PEITS) (Vol. 1, pp. 214-218) . IEEE. DOI: 10.1109/PEITS.2009.5407033

Zhang, L., & Wang, H. (2006). Intelligent information processing in human resource management: an implementation case in China. Expert Systems, 23 (5), 356-369. https://doi.org/10.1111/j.1468-0394.2006.00416.x

Maroufi, Yahya and Yousefzadeh, Mohammad Reza (2008). Content analysis in Humanity. Hamedan: Sephar Danesh. [In Persian]