Disrupción tecnológica en la gestión del Talento Humano

Autores/as

  • Roberto Santiago Salazar Pazmiño Universidad Internacional del Ecuador, Business School
  • Andrés Santiago Toledo Andrade Universidad Internacional del Ecuador, Business School
  • Fausto Fabian Andrade Montalvo Universidad de las Americas-UDLA, Facultad de Posgrados, Escuela de Negocios

Palabras clave:

Innovaciones en recursos humanos, capacidades de innovación, selección de personal, gestión de recursos humanos, personal idóneo.

Resumen

La selección y retención del talento humano son procesos críticos para el éxito de cualquier empresa u organización, debiendo adaptarse la gestión del talento al cambio constante de las tendencias tecnológicas y sociales del entorno donde se desarrolla. En esta investigación se presentan las más recientes publicaciones donde las nuevas tecnologías contribuyen a estos procesos, como: automatizando tareas repetitivas y tediosas en el proceso de selección del talento, como la revisión de currículums y la programación de entrevistas, identificación de candidatos que se ajustan para el puesto y la cultura organizacional de la empresa; como pueden ser programadas para ser "ciegas" a características como la edad, el género, la raza, etc., y considerando en todo momento la ética y la diversidad; se reduce el riesgo de sesgos inconscientes en la selección de candidatos; pueden ayudar a las empresas u organizaciones a descubrir candidatos potenciales que de otra manera podrían haber pasado desapercibidos, buscando en redes sociales y sitios web de empleo, así como también pueden utilizarse para evaluar la experiencia y las habilidades de los candidatos en base a su actividad en línea; las tecnologías en línea, permiten evaluar y seleccionar a candidatos de diferentes partes del mundo, sin tener que desplazarse físicamente, reduciendo costos y aumentando la eficiencia en el proceso de selección; la realidad virtual y aumentada, pueden ayudar a las empresas a evaluar habilidades técnicas y prácticas, especialmente en puestos que requieren habilidades.

Descargas

Los datos de descargas todavía no están disponibles.

Citas

Amsolik, P., & Chomatek, L. (2022). Supporting the identification of promising candidates in the recruitment for IT jobs. Procedia Computer Science. 207: 2263-2272.

Bansal, A., Panchal, T., Jabeen, F., Mangla, S., & Singh, G. (2023). A study of human resource digital transformation (HRDT): A phenomenon of innovation capability led by digital and individual factors. Journal of Business Research. 153: 113611.

Bingley, W., Curtis, C., Lockey, S., Bialkowski, A., Gillespie, N., Haslam, A., Ko, R., Steffens, N., Wiles, J., & Worthy, P. (2023). Where is the human in human-centered AI? Insights from developer priorities and user experiences. Computers in Human Behavior. 141:107617.

Braun, P., Grafelmann, M., Gill, f., Stolz, H., Hinckeldeyn, J., & Lange, A. (2022). Virtual reality for immersive multi-user firefighter-training scenarios. Virtual Reality & Intelligent Hardware. 4(5): 406–417.

Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023). Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human Resource Management Review. 33(1): 100899.

Delecraz, S., Eltarr, L., Becuwe, M., Bouxin, H., Boutin, N., & Oullier, O. (2022). Responsible Artificial Intelligence in Human Resources Technology: An innovative inclusive and fair by design matching algorithm for job recruitment purposes. journal of Responsible Technology. 11:100041.

Fumagalli, E., Rezaei, S., & Salomons, A. (2022). OK computer: Worker perceptions of algorithmic recruitment. Research Policy. 51(2): 104420.

Garcia, R., Huang, Y., & Kwok, L. (2023). Virtual interviews vs. LinkedIn profiles: Effects on human resource managers’ initial hiring decisions. Tourism Management. 94: 104659.

Glasauer, C. (2023). The Prevent-Model: Human and Organizational Factors Fostering Engineering of Safe and Secure Robotic Systems. Journal of Systems and Software. 195:111548,

Hauptman, A., Schelble, B., McNeese, N., & Madathil, K. (2023). Adapt and overcome: Perceptions of adaptive autonomous agents for human-AI teaming. Computers in Human Behavior. 138:107451.

Kaliannan, M., Darmalinggam, D., Dorasamy, M., & Abraham, M. (2023) Inclusive talent development as a key talent management approach: A systematic literature review. Human Resource Management Review. 33(1): 100926.

Kent, S., Houghton, L., & Licorish, S. (2023). Towards an understanding of the relationship between institutional theory, affective events theory, negative discrete emotions, and the development of feral systems when using human resource information systems. Computers in Human Behavior Reports. 9:100264.

Koch, J., Plattfaut, R., & Kregel, I. (2021). Looking for Talent in Times of Crisis – The Impact of the Covid-19 Pandemic on Public Sector Job Openings. International Journal of Information Management Data Insights. 1(2):100014.

Longo, F., Padovano, A., Felice, F., Petrillo, A., & Elbasheer, M. (2023). From “prepare for the unknown” to “train for what's coming”: a digital twin-driven and cognitive training approach for the workforce of the future in smart factories. Journal of Industrial Information Integration. 100437.

Marin, G., & Nilă, C. (2021). Branding in social media. Using LinkedIn in personal brand communication: A study on communications/marketing and recruitment/human resources specialists’ perception. Social Sciences & Humanities Open. 4(1): 100174.

McDonald, P., & Korber, M. (2023). Employer preferences for vocational over general education: evidence from an employer survey experiment. Research in Social Stratification and Mobility. 83:100756.

Melão, N., & Reis, J. (2021). Social networks in personnel selection: profile features analyzed and issues faced by hiring professionals. Procedia Computer Science. 181: 42-50.

Montero, J., Danvila-del-Valle, I., & Méndez, M. (2023). The impact of digital transformation on talent management. Technological Forecasting and Social Change. 188:122291.

Nørskov, S., Damholdt, M., Ulhøi, J., Jensen, M., Mathiasen, M., Ess, C., & Seibt, J. (2022). Employers’ and applicants’ fairness perceptions in job interviews: using a teleoperated robot as a fair proxy. Technological Forecasting & Social Change. 179: 121641.

Novian, R., & Sukardi, T. (2023). Investigation study of integrated vocational guidance on work readiness of mechanical engineering vocational school students. Heliyon. 9: e13333.

Parida, B. KumarPatra, P., & Mohanty, S. (2022). Prediction of recommendations for employment utilizing machine learning procedures and geo-area based recommender framework. Sustainable Operations and Computers. 3: 83-92.

Pringle, J., Stimpson, I., Jeffery, A., Wisniewski, K., Grossey, T., Hobson, L., Heaton, V., Zholobenko, V., & Rogers, S. (2022). Extended reality (XR) virtual practical and educational eGaming to provide effective immersive environments for learning and teaching in forensic science. Science & Justice. 62: 696–707.

Rodgers, W., Murray, J., Stefanidis, A., Degbey, W., & Tarba, S. (2023). An artificial intelligence algorithmic approach to ethical decision-making in human resource management processes. Human Resource Management Review. 33(1):100925.

Smaldone, F., Ippolito, A., Lagger, J., & Pellicano, M. (2022). Employability skills: Profiling data scientists in the digital labour market. European Management Journal. 40(5): 671-684.

Spahrkäs, S., Looijmans, A., Sanderman, R., & Hagedoorn, M. (2021). Recruiting participants for an international mHealth study via Facebook Ads: Experiences from the Untire App RCT. Internet Interventions. 23:100362.

Spain, R., Hedge, J., Ohse, D., & White, A. (2022). The need for research-based tools for personnel selection and assessment in the forensic sciences. Forensic Science International: Synergy. 4:100213.

Suen, H., & Hung, K. (2023). Building trust in automatic video interviews using various AI interfaces: Tangibility, immediacy, and transparency. Computers in Human Behavior. 143:107713.

Toniolo, A., Cerutti, F., Norman, T., Oren, N., Allen, J., Srivastava, M., & Sullivan, P. (2023). Human-machine collaboration in intelligence analysis: An expert evaluation. Intelligent Systems with Applications. 17:200151.

Turulja, L., Vugec, D., & Bach, M. (2023). Big Data and Labour Markets: A Review of Research Topics. Procedia Computer Science. 217: 526-535.

Wehner, C., Grip, A., & Pfeifer, H. (2022). Do recruiters select workers with different personality traits for different tasks? A discrete choice experiments. Labour Economics. 78:102186.

Wesche, J., & Sonderegger, A. (2021). Repelled at first sight? Expectations and intentions of job-seekers reading about AI selection in job advertisements. Computers in Human Behavior. 125: 106931.

Wongsansukcharoen, J., & Thaweepaiboonwong, J. (2023). Effect of innovations in human resource practices, innovation capabilities, and competitive advantage on small and medium enterprises’ performance in Thailand. European Research on Management and Business Economics. 29(1): 100210.

Descargas

Publicado

2023-01-04
Estadísticas
Resumen 494

Cómo citar

Salazar Pazmiño, R. S., Toledo Andrade, A. S., & Andrade Montalvo, F. F. (2023). Disrupción tecnológica en la gestión del Talento Humano. Journal of Science and Research, 8(1), 178–197. Recuperado a partir de https://revistas.utb.edu.ec/index.php/sr/article/view/2857

Número

Sección

Artículo de Investigación