Analítica de recursos humanos: una revisión sistemática de literatura

Contenido principal del artículo

Carla Fernández-Solís
María Reyes González-Ramírez
José Gascó-Gascó

Resumen

La gestión de recursos humanos representa un aspecto clave para el desarrollo de los países emergentes en general, y en particular, para el desempeño organizacional. Dentro de estas funciones, la analítica de recursos humanos, un conjunto de actividades desarrolladas para apoyar la toma de decisiones basada en datos se convierte en un punto de agenda básico para empresarios y académicos. En este contexto, el objetivo de esta investigación es identificar los principales referentes en Analítica de Recursos Humanos, que sirvan de soporte para el diseño de un modelo que caracterice este constructo, y para fundamento de investigaciones futuras. Para este fin, se realiza una Revisión Sistemática de Literatura, donde se logran identificar los artículos más citados, los métodos de investigación aplicados, y en general, las tendencias de investigación en el periodo temporal 2010–2023. Se realizó una búsqueda en las bases de datos científicas Web Of Science, SciELO, ProQuest, Elsevier y Researchgate. Se seleccionaron 69 documentos de acceso abierto. Se evaluó la calidad de los artículos. Se destaca que, la mayoría de las investigaciones se enfocan en el paradigma cualitativo; sin embargo, dentro de los pocos trabajos cuantitativos, el uso de encuestas y su análisis basado en Modelos de Ecuaciones Estructurales, representa una corriente de investigación prometedora para el futuro.

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Fernández-Solís, C., González-Ramírez, M. R., & Gascó-Gascó, J. (2024). Analítica de recursos humanos: una revisión sistemática de literatura. INNOVA Research Journal, 9(3), 137–166. https://doi.org/10.33890/innova.v9.n3.2024.2538
Sección
Empresa e innovación
Biografía del autor/a

Carla Fernández-Solís, Universidad ECOTEC, Samborondón, Ecuador

Fernández Solís Carla Lorena, ecuatoriana, Magister en Talento Humano de la Escuela Superior Politécnica del Litoral (Ecuador), Doctoranda en Economía, Empresa y Sociedad en la Universidad de Alicante (España), Docente de la Facultad de Ciencias Económicas y Empresariales de la Universidad ECOTEC. Líneas de Investigación: Desarrollo Empresarial e Innovación/ Empresa, Economía, Territorio y Patrimonio. Google Scholar: https://scholar.google.es/citations?hl=es&authuser=1&user=uMhi6fsAAAAJ

María Reyes González-Ramírez, Universidad de Alicante, San Vicente del Raspeig, Alicante, España

Reyes González-Ramírez. Española, Doctora en Ciencias Económicas y Empresariales en la Universidad de Alicante (España). Catedrática de Organización de Empresas en dicha universidad. Líneas de Investigación:  Investigación en las áreas de Dirección de Sistemas de Información y de Recursos Humanos, Digitalización, procesos de Outsourcing empresarial y la Gestión de las Administraciones Públicas. Google Scholar:  https://scholar.google.es/citations?user=0ot-KGkAAAAJ&hl=es

 

José Gascó-Gascó, Universidad de Alicante, San Vicente del Raspeig, Alicante, España

José Gascó Gascó. Español, Doctor en Ciencias Económicas y Empresariales en la Universidad de Alicante (España). Catedrático de Organización de Empresas en dicha universidad. Líneas de Investigación: Gestión de Recursos Humanos y Sistemas de Información en la Empresa. Digitalización. Dirección en Administraciones Publicas. Google Scholar:  https://scholar.google.es/citations?user=NTtiqrAAAAAJ&hl=es

Citas

Álvarez-Gutiérrez, F.; Stone, D.; Castaño, A. & García-Izquierdo, A. (2022). Human Resources Analytics: a systematic review from a sustainable management approach. Journal of Work and Organizational Psychology, 38 (3), 129-147. https://doi.org/10.5093/jwop2022a18

Aral, S.; Brynjolfsson, E. & Wu, L. (2012). Three-Way Complementarities: Performance Pay, Human Resource Analytics, and Information Technology. Management Science, 58(5):913-931. http://dx.doi.org/10.1287/mnsc.1110.1460

Arora, M., Prakash, A., Mittal, A. & Singh, S. (2022). Examining the slow acceptance of HR analytics in the Indian engineering and construction industry: a SEM-ANN-based approach. Engineering, Construction and Architectural Management. https://doi.org/10.1108/ECAM-09-2021-0795

Bandi, G.; Rao, T. & Ali, S. (2021). Data Analytics Applications for Human Resource Management. 2021 International Conference on Computer Communication and Informatics (ICCCI). https://doi.org/10.1109/ICCCI50826.2021.9402300

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

Bechter, B.; Brand, B. & Lehr, A. (2022). The role of the capability, opportunity, and motivation of firms for using human resource analytics to monitor employee performance: A multilevel analysis of the organisational, market, and country context. New Technology, Work and Employment, 37 (3), 398-424. https://doi.org/10.1111/ntwe.12239

Belizón, M. & Kieran, S. (2022). Human resources analytics: A legitimacy process. Human Resource Management Journal, 32 (3), 603–630. https://doi.org/10.1111/1748-8583.12417

Ben-Gal, H. C. (2019). An ROI-based review of HR analytics: practical implementation tools. Personnel Review, 48 (6), 1429-1448. https://doi.org/10.1108/PR-11-2017-0362

Bryce, V.; McBride, N. & Cunden, M. (2022). Post-COVID-19 ethics of people analytics. Journal of Information, Communication and Ethics in Society, 20 (4), 480-494. https://doi.org/10.1108/JICES-09-2021-0096

Burdon, M. & Harpur, P. (2014). Re-conceptualising privacy and discrimination in an age of talent analytics. UNSW Law Journal, 37 (2), 679-712. https://www.unswlawjournal.unsw.edu.au/wp-content/uploads/2017/09/37-2-4.pdf

Castellano, S. (2014). Decision Science. TD Magazine

Chatterjee, S., Chaudhuri, R., Vrontis, D. & Siachou, E. (2022). Examining the dark side of human resource analytics: an empirical investigation using the privacy calculus approach. International Journal of Manpower, 43 (1), 52-74. https://doi.org/10.1108/IJM-02-2021-0087

Chau, K. Y., Huang, T., Moslehpour, M., Khan, W., Nisar, Q. A., & Haris, M. (2024). Opening a new horizon in green HRM practices with big data analytics and its analogy to circular economy performance: empirical evidence. Environment, Development and Sustainability, 26(5). 12133-12162.

Chiavenato, I. (2019). Administración de Recursos Humanos: El capital humano de las organizaciones. McGraw-Hill.

Cho, W., Choi, S., & Choi, H. (2023). Human resources analytics for public personnel management: Concepts, cases, and caveats. Administrative Sciences, 13(2), 41.

Chornous, G. & Gura, V. (2020). Integration of Information Systems for Predictive Workforce Analytics: Models, Synergy, Security of Entrepreneurship. European Journal of Sustainable Development, 9 (1), 83-98. https://doi.org/10.14207/ejsd.2020.v9n1p83

D’Armas Regnault, M.; Mejías Acosta, A.; et al. (2022). Autoeficacia e Intención emprendedora en estudiantes universitarios: una revisión Sistemática de Literatura. 20th LACCEI International Multi-Conference for Engineering, Education, and Technology: “Education, Research and Leadership in Post-pandemic Engineering: Resilient, Inclusive and Sustainable Actions”, Hybrid Event, Boca Raton, Florida- USA, July 18 - 22, 2022. http://dx.doi.org/10.18687/LACCEI2022.1.1.553

Dahlbom, P., Siikanen, N., Sajasalo, P. & Jarvenpää, M. (2020). Big data and HR analytics in the digital era. Baltic Journal of Management, 15 (1), 120-138. https://doi.org/10.1108/BJM-11-2018-0393

Davenport, T.; Harris, J. & Shapiro, J. (2010). Competing on Talent Analytics. Harvard Business Review, 10, 1-6. https://hbr.org/2010/10/competing-on-talent-analytics

Dhankhar, K. & Singh, A. (2022). Employees' adoption of HR analytics – a theoretical framework based on career construction theory. Evidence-based HRM, https://doi.org/10.1108/EBHRM-02-2022-0053

Edwards, M.; Charlwood, A.; Guenole, N. & Marler, J. (2022). HR analytics: An emerging field finding its place in the world alongside simmering ethical challenges. Human Resource Management Journal, https://doi.org/10.1111/1748-8583.12435

Ekka, S. & Singh, P. (2022). Predicting HR Professionals’ Adoption of HR Analytics: An Extension of UTAUT Model. Organizacija, 55 (1), 77-93. https://doi.org/10.2478/orga-2022-0006

Ekka, S. (2021). HR Analytics: why it matters. Journal of Contemporary Issues in Business and Government, 27 (2), 2283-2291. https://doi.org/10.47750/cibg.2021.27.02.238

Ellmer, M. & Reichel, A. (2021). Staying close to business: the role of epistemic alignment in rendering HR analytics outputs relevant to decision-makers. The International Journal of Human Resource Management, 32 (12), 2622-2642. https://doi.org/10.1080/09585192.2021.1886148

Fernández, V. & Gallardo-Gallardo, E. (2021). Tackling the HR digitalization challenge: key factors and barriers to HR analytics adoption. Competitiveness Review: An International Business Journal, 31(1), 162–187. https://doi.org/10.1108/cr-12-2019-0163

Gal, U.; Jensen, T. & Stein, M. (2020). Breaking the vicious cycle of algorithmic management: A virtue ethics approach to people analytics. Information and Organization, 30 (2), 100301. https://doi.org/10.1016/j.infoandorg.2020.100301

García-Peñalvo, F. (2022). Desarrollo de estados de la cuestión robustos: Revisiones Sistemáticas de Literatura. Education in the Knowledge Society (EKS), 23, e28600. https://doi.org/10.14201/eks.28600

Gelbard, R.; Ramon-Gonen, R.; Carmeli, A; Bittmann, R. & Talyansky, R. (2018). Sentiment analysis in organizational work: Towards an ontology of people analytics. Expert Systems, 35 (5), e12289. https://doi.org/10.1111/exsy.12289

Gohain, A. & Saikia, A. (2021). A study on “Human resource analytics for decision making in international business machine in India and United States.” Journal of Contemporary Issues in Business and Government, 27 (5), 1081-1094. https://doi.org/10.47750/cibg.2021.27.05.070

Greasley, K. & Thomas, P. (2020). HR analytics: The onto-epistemology and politics of metricized. HRM Human Resource Management Journal, 30 (4), 494-507. https://doi.org/10.1111/1748-8583.12283

Green, D. (2017). The best practices to excel at people analytics. Journal of Organizational Effectiveness-People and Performance, 4 (2), 137-144. https://doi.org/10.1108/JOEPP-03-2017-0027

Guo, F.; Gallagher, C.; Sun, T.; Tavoosi, S. & Min, H. (2021). Smarter people analytics with organizational text data: Demonstrations using classic and advanced NLP models. Human Resource Management Journal, https://doi.org/10.1111/1748-8583.12426

Gurusinghe, R. N., Arachchige, B. J. H., & Dayarathna, D. (2021). Predictive HR analytics and talent management: a conceptual framework. Journal of Management Analytics, 8 (2), 195–221. https://doi.org/10.1080/23270012.2021.1899857

Halawi, A., Rasheed, R., & Al Belushi, B. (2024). The Effect of Human Resource Analytics on Employee Performance. Revista De Gestão Social E Ambiental, 18(5), e05569-e05569.

Huselid, M. (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

Jana, B. & Kaushik, T. (2022) Application of technology-organization-environment model in HR analytics adoption. Journal of Information and Optimization Sciences, 43 (6), 1387-1395. https://doi.org/10.1080/02522667.2022.2117331

Jiang, Y., & Akdere, M. (2022). An operational conceptualization of human resource analytics: implications for inhuman resource development. Industrial and Commercial Training, 54(1), 183-200.

Kapoor, B. & Kabra, Y. (2014). Current and future trends in Human Resources Analytics adoption. Journal of Cases on Information Technology, 16(1), 1-10. https://doi.org/10.4018/jcit.2014010105

Karwehl, L. J., & Kauffeld, S. (2021). Traditional and new ways in competence management: Application of HR analytics in competence management. Gruppe. Interaktion. Organisation. Zeitschrift Für Angewandte Organisationspsychologie (GIO), 52 (1), 7–24. https://doi.org/10.1007/s11612-021-00548-y

Khan, S. & Tang, J. (2016). The paradox of human resource analytics: being mindful of employees. Journal of General Management, 42 (2), 57–66. https://doi.org/10.1177/030630701704200205

Kifor, C.; Nicolaescu, S.; Florea, A.; Savescu, R.; Receu, I.; Tirlea, A. & Danut, R. (2021). Workforce Analytics in Teleworking. IEEE Access, 9, 156451-156464. https://doi.org/10.1109/ACCESS.2021.3129248

King, K. (2016). Data Analytics in Human Resources. Human Resource Development Review, 15 (4), 487-495. https://doi.org/10.1177/1534484316675818

Konovalova, V.; Ruben V. Aghgashyan, R. & Galazova, S. (2021). Perspectives and Restraining Factors of HR Analytics in the Conditions of Digitization of Human Resources Management.

EnPopkova, E. G., Ostrovskaya, V. N., & Bogoviz, A. V. (Eds.). Socio-economic Systems: Paradigms for the Future. Studies in Systems, Decision and Control, 314, 1015-1024. https://doi.org/10.1007/978-3-030-56433-9

Lal, P. (2015). Transforming HR in the digital era: Workforce analytics can move people specialists to the center of decision-making. Human Resource Management International Digest, 23(3), 1-4. https://doi.org/10.1108/hrmid-03-2015-0051

Lame, G. (2019). Systematic Literature Reviews: An Introduction. Proceedings of the Design Society: International Conference on Engineering Design, 1 (1), 1633-1642. https://doi.org/10.1017/dsi.2019.169

Larsson, A. & Edwards, M. (2021). Insider econometrics meets people analytics and strategic human resource management. The International Journal of Human Resource Management, 1–47. https://doi.org/10.1080/09585192.2020.1847166

Leonardi, P. & Contractor, N. (2018). Better people analytics measure who they know, not just who they are. Harvard Business Review, 11,1-15. https://hbr.org/2018/11/better-people-analytics

Levenson, A. (2018). Using workforce analytics to improve strategy execution. Human Resource Management, 57 (3), 685-700. https://doi.org/10.1002/hrm.21850

Luo, Z., Liu, L., Yin, J., Li, Y., & Wu, Z. (2018). Latent ability model: A generative probabilistic learning framework for workforce analytics. IEEE transactions on knowledge and data engineering, 31(5), 923-937.

Madhani, P. (2022). Human Resources Analytics: Leveraging Human Resources for Enhancing Business Performance. Compensation & Benefits Review, 0(0). https://doi.org/10.1177/08863687221131730

Manokha, I. (2020). The Implications of Digital Employee Monitoring and People Analytics for Power Relations in the Workplace. Surveillance & Society, 18 (4), 540-554. https://ojs.library.queensu.ca/index.php/surveillance-and-society/index

Margherita, A. (2022). Human resources analytics: A systematization of research topics and directions for future research. Human Resource Management Review, 32 (2), 1-13. https://doi.org/10.1016/j.hrmr.2020.100795

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. http://dx.doi.org/10.1080/09585192.2016.1244699

Martin-Rios, C.; Pougnet, S. & Nogareda, A. (2017). Teaching HRM in contemporary hospitality management: a case study drawing on HR analytics and big data analysis. Journal of Teaching in Travel & Tourism, 17 (1), 34-54 https://doi.org/10.1080/15313220.2016.1276874

McCartney, S. & Fu, N. (2022). Bridging the gap: why, how, and when HR analytics can impact organizational performance. Management Decision, 60 (13), 25-47. https://doi.org/10.1108/MD-12-2020-1581

McIver, D.; Lengnick-Hall, M. & Lengnick-Hall, C. (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

Moraes, S. & Damian, I. (2021). People Analytics: far beyond the data. Atoz-novas Praticas Em Informacao E Conhecimento, 10 (3), 1-11. https://brapci.inf.br/index.php/res/download/166628

Muhammad, G. & Naz, F. (2022). A moderating role of HR analytics between employee engagement, retention, and organisational performance. International Journal of Business Environment, 13 (4), 345–357. https://doi.org/10.1504/IJBE.2022.126370

Necula, S. & Strimbei, C. (2019). People Analytics of Semantic Web Human Resource Resumes for Sustainable Talent Acquisition. Sustainability, 11 (13), 3520. https://doi.org/10.3390/su11133520

Nocker, M. & Sena, V. (2019). Big Data and Human Resources Management: The Rise of Talent Analytics. Social Sciences-Basel, 8 (10), 273. https://doi.org/10.3390/socsci8100273

Nowicka, J., Pauliuchuk, Y., Ciekanowski, Z., Fałda, B., & Sikora, K. (2024). The use of data analytics in human resource management. European Research Studies. 27(2), 203-215.

Opatha, H. (2020). HR Analytics: a literature review and new conceptual model. International Journal of Scientific and Research Publications, 10 (6), 130-141. http://dx.doi.org/10.29322/IJSRP.10.06.2020.p10217

Page, M.; McKenzie, J.; Bossuyt, P.; Boutron, I.; Hoffmann, T.; Mulrow, C.; Shamseer, L.; Tetzlaff, J.; Akl, E.; Brennan, S.; Chou, R.; Glanville, J.; Grimshaw, J.; Hróbjartsson, A.; Lalu, M.; Li, T.; Loder, E.; Mayo-Wilson, E.; McDonald, S.; McGuinness, L.; Stewart, L.; Thomas, J.; Tricco, A.; Welch, V.; Whiting, P.; Moher, D.; Yepes-Nuñez, J.; Urrútia, G.; Romero-García, M. & Alonso-Fernández, S. (2021). Declaración PRISMA 2020: una guía actualizada para la publicación de revisiones sistemáticas. Revista Española de Cardiología, 74 (9), 790-799. https://doi.org/10.1016/j.recesp.2021.06.016

Pariona-Cabrera, P.; Cavanagh, J. & Halvorsen, B. (2022). Examining the need for HR analytics to better manage and mitigate incidents of violence against nurses and personal care assistants in aged care, Asia Pacific Journal of Human Resources. https://doi.org/10.1111/1744-7941.12361

Peeters, T., Paauwe, J. & Van De Voorde, K. (2020). People analytics effectiveness: developing a framework. Journal of Organizational Effectiveness: People and Performance, 7 (2), 203-219. https://doi.org/10.1108/JOEPP-04-2020-0071

Polyakova, A.; Kolmakov, V. & Pokamestov, I. (2020). Data-driven HR Analytics in a Quality Management System. Quality-Access to Success, 21 (176), 74-80.

Pongpisutsopa, S., Thammaboosadee, S., & Chuckpaiwong, R. (2020). Factors affecting HR analytics adoption: A systematic review using literature weighted scoring approach. Asia Pacific journal of information systems, 30(4), 847-878. https://doi.org/10.14329/apjis.2020.30.4.847

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

Ryan, J. (2020). Retaining, resigning, and firing: bibliometrics as a people analytics tool for examining research performance outcomes and faculty turnover. Personnel Review, 50 (5), 1316–1335. https://doi.org/10.1108/pr-12-2019-0676

Setiawan, I.; Suprihanto, S.; Nugraha, A. & Hutahaean, J. (2020). HR analytics: Employee attrition analysis using logistic Regression. IOP Conf. Series: Materials Science and Engineering, 830, 1-7. https://doi.org/10.1088/1757-899X/830/3/032001

Sharma, A. & Sharma, T. (2017). HR analytics and performance appraisal system A conceptual framework for employee performance improvement. Management Research Review, 40 (6), 684-697. https://doi.org/10.1108/MRR-04-2016-0084

Shet, S.; Poddar, T.; Samuel, F. & Dwivedi, Y. (2021). Examining the determinants of successful adoption of data analytics in human resource management – A framework for implications. Journal of Business Research, 131, 311-326. https://doi.org/10.1016/j.jbusres.2021.03.054

Simbeck, K. (2019). HR analytics and ethics. IBM Journal of Research and Development, 63 (4/5), 9:1-9:12. https://doi.org/10.1147/JRD.2019.2915067

Simon, 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

Sinha, V., Subramanian, K., Bhattacharya, S. & Chaudhuri, K. (2012). The contemporary framework on social media analytics as an emerging tool for behavior informatics, HR analytics and business process. Management: journal of contemporary management issues, 17 (2), 65-84. https://hrcak.srce.hr/file/138312

Sivathanu, B. & Pillai, R. (2020). Technology and talent analytics for talent management – a game changer for organizational performance. International Journal of Organizational Analysis, 28 (2), 457–473. https://doi.org/10.1108/ijoa-01-2019-1634

Suri, N., & Lakhanpal, P. (2024). People analytics enabling HR Strategic partnership: A review. South Asian Journal of Human Resources Management, 11(1), 130-164.

Talukdar, G. (2016). Human Resources Analytics: An Approach Towards Business Intelligence. International Journal of Computer Sciences and Engineering, 4 (7), 125-129. https://www.ijcseonline.org/spl_pub_paper/NCRITET-IJCSE-2016028.pdf

Tsiotsou, R., Koles, B.; Paul, J. & Loureiro, S. (2022). Theory generation from literature reviews: A methodological guidance. International Journal of Consumer Studies, 46 (5), 1505-1516. https://doi.org/10.1111/ijcs.12861

Tursunbayeva, A., Pagliari, C., Di Lauro, S. & Antonelli, G. (2022). The ethics of people analytics: risks, opportunities, and recommendations. Personnel Review, 51 (3), 900-921. https://doi.org/10.1108/PR-12-2019-0680

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

Van den Heuvel, S. & Bondarouk, T. (2017). The rise (and fall?) of HR analytics A study into the future application, value, structure, and system support. Journal of Organizational Effectiveness-People and Performance, 4 (2), 157-178. https://doi.org/10.1108/JOEPP-03-2017-0022

Vargas, R.; Yurova, Y.; Ruppel, C.; Tworoger, L. & Greenwood, R. (2018). Individual adoption of HR analytics: a fine-grained view of the early stages leading to adoption. International Journal of Human Resource Management, 29 (22), 3046-3067. https://doi.org/10.1080/09585192.2018.1446181

Verma, S., Rana, N., & Meher, J. R. (2024). Identifying the enablers of HR digitalization and HR analytics using ISM and MICMAC analysis. International Journal of Organizational Analysis, 32(3), 504-521.

Wang, N. & Katsamakas, E. (2019). A Network Data Science Approach to People Analytics. Information Resources Management Journal, 32(2), 28–51. https://doi.org/10.4018/irmj.2019040102

Wang, N. & Katsamakas, E. (2021). A Recommendation System for People Analytics. International Journal of Business Intelligence Research (IJBIR), 12(2), 1-12. http://doi.org/10.4018/IJBIR.20210701.oa4

Weiskopf, R. & Hansen, H. K. (2023). Algorithmic governmentality and the space of ethics: Examples from ‘People Analytics.’ Human Relations, 0(0). https://doi.org/10.1177/00187267221075346

Williams, R.; Clark, L.; Clark, W. & Raffo, D. (2021). Re-examining systematic literature review in management research: Additional benefits and execution protocols. European Management Journal, 39 (4), 521-533. https://doi.org/10.1016/j.emj.2020.09.007

Williams, S. (2020). A textual analysis of racial considerations in human resource analytics vendors' marketing. Management Research and Practice, 12 (4), 49-63. https://mrp.ase.ro/no124/f5.pdf

Wirges, F. & Neyer, A. (2022). Towards a process-oriented understanding of HR analytics: implementation and application. Review of Managerial Science, https://doi.org/10.1007/s11846-022-00574-0

Worth, C. W. (2011). The future talent shortage will force global companies to use HR analytics to help manage and predict future human capital needs. International journal of business intelligence research, 2(4), 55-65. https://doi.org/10.4018/jbir.2011100105

Wroe, N. (2012). Innovations in Talent Analytics. TD Magazine

Yahia, N.; Hlel, J. & Colomo-Palacios, R. (2021). From Big Data to Deep Data to Support People Analytics for Employee Attrition Prediction. IEEE Access, 9, 60447-60458. https://doi.org/10.1109/ACCESS.2021.3074559