مرور نظام‌مند مدیریت منابع انسانی هوشمند داده محور
محورهای موضوعی : بهره وری و توانمندسازی نیروی انسانیمصطفی طغیانی پزوه 1 , محمدرضا دلوی 2 , رسول آقا داوود 3
1 - دانشجوی دکتری، رشته مدیریت دولتی -مدیریت تطبیقی و توسعه ، دانشگاه آزاد اسلامی واحد دهاقان ، دهاقان، ایران.
2 - محمدرضا دلوی دانشیار، گروه مدیریت، واحد دهاقان، دانشگاه آزاد اسلامی، دهاقان، ایران.
3 - استادیار، گروه مدیریت، دانشگاه آزاد اسلامی دهاقان، دهاقان، ایران.
کلید واژه: مدیریت منابع انسانی, مدیریت هوشمند, داده محور,
چکیده مقاله :
زمینه و هدف: مدیریت منابع انسانی هوشمند، رویکردی نوین است از ترکیب دو عنصر کلیدی یعنی مدیریت منابع انسانی و تحلیل داده‌ها برای بهبود فرآیندها و تصمیم‌گیری‌ها، که به سازمان‌ها کمک می کند تا داده‌های خود را به شکلی هوشمندانه تبدیل کند. هدف پژوهش، مرور نظامند مدیریت منابع انسانی هوشمند داده محور در دانشگاه های آزاد و دولتی می باشد. روش بررسی: این پژوهش ازنظر هدف بنیادی و از روش فرا تحلیل استفاده شد. جامعه مورد بررسی شامل تحقیقات انجام‌شده در مورد موضوع در پایگاه‌های معتبر علمی بود که در مجموع 33 منبع مرتبط با ویژگی های مورد نظرشناسایی شدند. از روش کدگذاری باز، محوری و انتخابی برای طراحی الگو استفاده شد. یافته ها: مولفه‌های الگوی نهایی شامل 15 مضمون بود از جمله: رهبری هوشمند، تامین منابع استراتژیک و سرمایه گذاری هدفمند، معماری سازمانی مناسب برای نظام های آموزش و جذب و نگهداشت. نتیجه گیری: به منظور تحقق مدیریت منابع انسانی هوشمند داده محور، تمرکز بر مولفه های شناسایی شده و عملیاتی کردن آنها در دانشگاه ها از اهمیت بالایی برخوردار است.
Background and purpose: Intelligent human resource management is a new approach of combining two key elements namely human resource management and data analysis to improve processes and decisions, which helps organizations to transform their data in an intelligent way. The purpose of this research is to review the intelligent data-oriented human resources management system in open and public universities. Research method: This research was based on the fundamental goal and the meta-analysis method was used. The investigated community included the research conducted on the subject in reliable scientific databases, which identified a total of 33 sources related to the desired characteristics. Open, central and selective coding methods were used to design the model. Findings: The components of the final model included 15 themes, including: intelligent leadership, provision of strategic resources and targeted investment, suitable organizational architecture for training and recruitment and retention systems. Conclusion: In order to realize intelligent data-driven human resource management, focusing on the identified components and operationalizing them in universities is of great importance.
References
Ahmad, K., Maabreh, M., Ghaly, M., Khan, K., Qadir, J., & Al-Fuqaha, A. (2022). Developing future human-centered smart cities: Critical analysis of smart city security, Data management, and Ethical challenges. Computer Science Revie. 43(4), 100452. DOI:10.1016/j.cosrev.2021.100452
Alavi, M., Qalavandi, H., Abbas por Fard Tahrani, M., & Khani Kamran, M. (2019). Presenting a model for pplying green management in public universities in Tehran. Research and planning in higher education, 97(26), 77-9 [In Persian]. https://journal.irphe.ac.ir/article_703007.html
Amiri, H., Mirspasi, N., & Rahnamae Roudpashti, F. (2016). Designing the accounting model of human resources in the Islamic Azad University. Scientific Research Quarterly Journal of Management Accounting and Auditing, 6(21): 19-32 [In Persian]. https://journals.srbiau.ac.ir/article_10288.html
Barkheh, A., & Jamali, G.R. (2017). Investigating the impact of strategic human resources on improving financial performance in Yasouj State University. Economic studies, financial management and accounting, 4(4), 318-332 [In Persian]. https://civilica.com/doc/1500020/
Armstrong, M., & Taylor, S. (2014). Armstrong's Handbook of Human Resource Management Practice (13th ed.). Kogan Page.
Bazarafshan, A. A., Amiryanzadeh, M., Zarei, R., & Ahmadi, A. (2018). The effect of organizational culture in preventing malpractices in the organizational behavior of Khatam al-Anbia air defense base staff. Quarterly Journal of Military Sciences and Techniques, 15(48), 116-143 [In Persian]. https://ensani.ir/fa/article/422445
Bibri, S. E. (2020). Compact urbanism and the synergic potential of its integration with data-driven smart urbanism: An extensive interdisciplinary literature review. Land Use Policy, 97: 104703. https://doi.org/10.1016/j.landusepol.2020.104703
Bibri, S. E., & Krogstie, J. (2020). The emerging data–driven Smart City and its innovative applied solutions for sustainability: The cases of London and Barcelona. Energy Informations, 3(1), 5. DOI:10.1186/s42162-020-00108-6
Boxall, P., & Purcell, J. (2016). Strategy and Human Resource Management (4th ed.). Palgrave Macmillan.
Cai, Q., Wang, H., Li, Z., & Liu, X. (2019). A survey on multimodal data-driven smart healthcare systems: approaches and applications. IEEE Access. https://doi.org/10.1109/ACCESS.2019.2941419
Dessler, G. (2019). Human Resource Management (16th ed.). Pearson. https://doi.org/10.3390/biomedinformatics4010004
Eskandar, F., Radfar, R., & Toloui Ashlaghi, A. (2019). A factor-based simulation model will be presented to predict work team performance in order to improve human resource management strategies (case study: Department of Industrial Management, Faculty of Management and Economics, Islamic Azad University, Science and Research Unit, Tehran). Strategic Management Research, 25(74), 49-73 [In Persian]. https://journals.iau.ir/article_673155.html?lang=en
Fang, Y., Shan, Z., & Wang, W. (2021). Modeling and key technologies of a data-driven smart city system. IEEE Access. https://doi.org/10.1109/ACCESS.2021.3091716
Fazl’lahi Qomshi, S., & Nowrozi, A.A. (2011). Knowledge management infrastructures in the Islamic Azad University of Qom from the point of view of faculty members. Scientific Journal of Education and Evaluation Quarterly, 4(15), 129-149 [In Persian]. https://www.sid.ir/paper/183589/fa
Foruzandeh Junqani, R., Seyyed Naqvi, M. A., Ghorbanzadeh, V., & Taghavifard, T. (2021). Human resource management intelligence model based on data science and machine learning. Intelligent Business Management Studies, 40(10), 267-310 [In Persian]. https://doi.org/10.22054/ims.2022.66412.2169
Ghaffari Zenozi, M., Mohebi, S., & Daneshfar, K. (2021). Designing the effectiveness model of human resources in the university with the innovative approach of foundation data (case study: Islamic Azad University). Innovation and creativity in human sciences, 10(4), 143-178 [In Persian]. https://www.sid.ir/paper/402877/fa
Ghobadi Alwar, A., Mousavi, N., & Shariatnejad, A. (2017). Analysis and evaluation of human resource risks in the higher education system; Case: Lorestan Islamic Azad University. Research and planning in higher education, 24(3), 107-129 [In Persian]. https://journal.irphe.ac.ir/article_702959.html
Heydarzadeh, M. (2015). Meta-analysis of research related to factors affecting the use of information technology (IT) in Iranian organizations. Master thesis, Tehran: Allameh Tabatabai University [In Persian]. https://doi.org/10.22054/qpss.2023.73621.3237
Kabipour, Ashraf Ganjavi, Zarei. (2021). Improving the information management system of human and physical resources of Islamic Azad University sports. Sports Management Journal, 15(4), 19-36 [In Persian]. https://doi.org/10.22059/jsm.2021.326806.2761
Kambur, E., & Yildirim, T. (2023). From traditional to smart human resources management. International Journal of Manpower, 44(1). DOI:10.1108/IJM-10-2021-0622
Khanleri, A., & Kafai, O. (2014). Investigating the effect of structural dimensions on the success of the organizational resource planning system in Iranian companies The owner of this system, 6(1), 47-70 [In Persian]. doi: 10.22059/jitm.2014.50050
Kostepen, Z. N., Akkol, E., Dogan, O., Bitim, S., & Hiziroglu, A. (2020). A Framework for Sustainable and Data-driven Smart Campus. Conference: 22nd International Conference on Enterprise Information Systems. 2: 746-753. DOI:10.5220/0009406807460753
Mahdizadeh, R., Soltani, I. & Davadzeh Emami, H. (2019). Factors affecting the architecture of human resources in the Islamic Azad University of Fars province. A new approach in educational management, 3(43), 373-398 [In Persian]. https://ensani.ir/fa/article/437549/
Majam, T., & Jarbandhan, D. B. (2022). Data driven human resource management in the Fourth Industrial Revolution. Africa’s Public Service Delivery & Performance Review, 10(1), 12. DOI:10.4102/apsdpr.v10i1.588
Malhotra, K., Kalra, A., Kumar, A., Majmundar, M., Wander, G. S., & Bawa, A. (2022). Understanding the digital impact of World Hypertension Day: key takeaways. European Heart Journal-Digital Health, 3(3), 489-492. https://doi.org/10.1093/ehjdh/ztac039
Marr, B. (2018). Data-driven HR: How to use analytics and metrics to drive performance. Kogan Page Publishers.
Medeiros, M. M. D., & Maçada, A. C. G. (2022). Competitive advantage of data-driven analytical capabilities: the role of big data visualization and of organizational agility. Management Decision, 60(4), 953-975. https://doi.org/10.1108/MD-12-2020-1681
Naqhvi, M. A., Junqani, F., Ghorbanzadeh, V., & Taghavifard, M. T. (2012). Human resource management intelligence model based on data science and machine learning. Intelligent Business Management Studies, 40(10), 267-310 [In Persian]. https://sid.ir/paper/1031251/fa
Noe, R. A., Hollenbeck, J. R., Gerhart, B., & Wright, P. M. (2019). Human Resource Management: Gaining a Competitive Advantage (11th ed.). McGraw-Hill Education.
Pakdel, S., & Lavasani, S. (2021). Systematic analysis of human resource data is a new approach in pathology, trend forecasting and data-based decision making. Administrative change, 65(14), 32-43 [In Persian]. https://www.noormags.ir/view/ar/articlepage/1810095
Panahi, M., Guderzi, M., Jalali Farahani, A., & Dost Ghafarakhi, A. (1401). Identifying the dimensions of acceleration of physical education faculties of state universities towards fourth-generation universities. Sports Management and Development, 11(2), 75-97 [In Persian]. https://civilica.com/doc/1997154/
Polzer, J. T. (2022). The rise of people analytics and the future of organizational research. Research in Organizational Behavior, 42: 100181. https://doi.org/10.1016/j.riob.2023.100181
Rashidi, I., Amirnejad, Q., & Daneshfard, K. (2019). Designing a model of green human resources with an emphasis on health and wellness in Islamic Azad University. Journal of the Faculty of Medicine of Mashhad University of Medical Sciences, 63(5), 2924-2936 [In Persian]. 10.22038/MJMS.2021.19056
Rejaei, Z., & Banai, F. (2017). The effect of policies related to working environment conditions on academic staff productivity (case study: Birjand State University). Public policy in management (Government Management Mission), 9(31), 19-38 [In Persian]. https://civilica.com/doc/1794621/
Salymian, M.A, Azizi, F., Boshroeh, N., & Zahedkar, P. (2019). Investigating the impact of human resource management measures on organizational performance (case study: Islamic Azad University, Astara Branch). Educational Management Innovations, 2(15), 21-35 [In Persian]. https://sanad.iau.ir/Journal/jmte/Article/1109712/FullText
Sarker, I. H. (2021). Data science and analytics: an overview from data-driven smart computing, decision-making and applications perspective. SN Computer Science, 2(5), 377. https://doi.org/10.1007/s42979-021-00765-8
Schwab, K. (2017). The fourth industrial revolution. Crown Currency, New York. https://www.weforum.org/about/the-fourth-industrial-revolution-by-klaus-schwab/
Simbeck, K. (2019). HR analytics and ethics. IBM Journal of Research and Development, 9(1), 1-12. DOI: 10.1147/JRD.2019.2915067
Storm, M. & Borgman, H. (2020). Understanding challenges and success factors in creating a data-driven culture. Conference: Hawaii International Conference on System Sciences. DOI:10.24251/HICSS.2020.663
Tao, F., Qi, Q., Liu, A., & Kusiak, A. (2018). Data-driven smart manufacturing. Journal of Manufacturing Systems, 48: 157-169. https://doi.org/10.1016/j.jmsy.2018.01.006
Ulrich, D., & Brockbank, W. (2005). The HR value proposition. Harvard Business Press.
Zaker salehi, G. & Kikha, A. (2021). A comparative study of the perspective and goals of higher education in selected countries. Public Policy, 7(4), 285-307 [In Persian]. https://www.sid.ir/paper/1050254/fa