Received:
2026-01-11 | Accepted:
2026-03-17 | Published:
2026-06-30
Title
Use and perception of technologies at work by generation Z: empirical study
Abstract
New technologies are fundamentally transforming the work environment, influencing communication patterns, work processes, and information management. This article presents the results of an empirical study focused on the perception and use of technical systems and digital devices by Generation Z employees within Slovak organizations. Data were collected in the first half of 2025 from a sample of 98 respondents across large and medium-sized enterprises. The findings reveal that a vast majority (91.8% of respondents) use technology daily and perceive it as an indispensable tool for efficiency, flexibility, and information access. Statistical testing confirmed a significant positive correlation (rs = 0.412, p = 0.001) between the frequency of technology use and the subjective feeling of self-fulfilment at work. Conversely, the study identified a significant negative correlation (rs = -0.394, p < 0.001) between perceived insufficient management support for digitalization and the willingness of employees to retain in their positions upon reaching financial independence. Despite high adaptability, respondents expressed concerns regarding technological failures and the lack of systematic training. The results emphasize that for Generation Z, technology is not merely a tool but a catalyst for motivation, provided it is accompanied by adequate organizational support.
Keywords
generation Z, technological adaptability, technology perception, work environment
JEL classifications
L20
, L60
, L80
, M19
, O30
URI
http://jssidoi.org/jesi/article/6638
DOI
Pages
40-51
Funding
Funded by the EU NextGenerationEU through the Recovery and Resilience Plan for Slovakia under the project No. 09I03-03-V05-00005.
This is an open access issue and all published articles are licensed under a
Creative Commons Attribution 4.0 International License
References
Abdussamad, Z., Agyei, I. T., Dongul, E. S., Abdussamad, J., Raj, R., & Effendy, F. (2022). Impact of Internet of Things (IOT) on Human Resource Management: A review. Materials Today-Proceedings, 56, 3534–3543 https://doi.org/10.1016/j.matpr.2021.11.247
Search via ReFindit
Acknowledgement: Funded by the EU NextGenerationEU through the Recovery and Resilience Plan for Slovakia under the project No. 09I03-03-V05-00005. /jesi/article/6638
Search via ReFindit
Afrin, S., Roksana, S., & Akram, R. (2025). AI-Enhanced Robotic Process Automation: A Review of Intelligent Automation Innovations. Ieee Access, 13, 173–197 https://doi.org/10.1109/ACCESS.2024.3513279
Search via ReFindit
Andruszkiewicz, K., Grzybowska-Brzezińska, M., Grzywińska-Rąpca, M., & Wiśniewski, P. D. (2023). Attitudes and Pro-Environmental Behavior of Representatives of Generation Z from the Example of Poland and Germany. Sustainability, 15(20), 15068 https://doi.org/10.3390/su152015068
Search via ReFindit
Annapurna, Guruprasad, A., & Murty, Y. S. (2020). Technology-Driven Workplace Transformation. In P. K. Suri & R. Yadav (Eds.), Transforming Organizations Through Flexible Systems Management (pp. 163–175). Springer-Verlag Singapore Pte Ltd https://doi.org/10.1007/978-981-13-9640-3_9
Search via ReFindit
de Moraes, C. R., da Cunha, P. R., & Ramos, I. (2022). Designing digital workplaces for employee engagement: Practical guidelines from a systematic literature review. In T. X. Bui (Ed.), Proceedings of the 55th Annual Hawaii International Conference on System Sciences (pp. 6341–6350). Hicss. /jesi/article/6638
Search via ReFindit
Galanti, T., Ferrara, B., Benevene, P., & Buonomo, I. (2023). Rethinking the Unthinkable: A Delphi Study on Remote Work during COVID-19 Pandemic. Social Sciences-Basel, 12(9), 497 https://doi.org/10.3390/socsci12090497
Search via ReFindit
Hessari, H., Bai, A., & Daneshmandi, F. (2024). Generative AI: Boosting Adaptability and Reducing Workplace Overload. Journal of Computer Information Systems https://doi.org/10.1080/08874417.2024.2417672
Search via ReFindit
Jo, H., & Park, D.-H. (2024). AI in the Workplace: Examining the Effects of ChatGPT on Information Support and Knowledge Acquisition. International Journal of Human-Computer Interaction, 40(23), 8091–8106 https://doi.org/10.1080/10447318.2023.2278283
Search via ReFindit
Jokonya, O. (2015). Validating Technology Acceptance Model (TAM) during IT adoption in Organizations. 2015 Ieee 7th International Conference on Cloud Computing Technology and Science (Cloudcom), 509–516 https://doi.org/10.1109/CloudCom.2015.56
Search via ReFindit
Jurenka, R., Stareček, A., Vraňaková, N., & Cagáňová, D. (2018). The learning styles of the generation group Z and their influence on learning results in the learning process. In 2018 16th IEEE International Conference on Emerging eLearning Technologies and Applications (ICETA) (pp. 237-242). IEEE https://doi.org/10.1109/ICETA.2018.8572186
Search via ReFindit
Kiedik, D., Grzebieluch, J., Chomątowska, B., Janiak-Rejno, I., & Żarczyńska-Dobiesz, A. (2023). Representatives of generation ‘Z’ as future doctors – priorities and competences. Annals of Agricultural and Environmental Medicine, 30(1), 178–183 https://doi.org/10.26444/aaem/156575
Search via ReFindit
Kim, Y., Blazquez, V., & Oh, T. (2024). Determinants of Generative AI System Adoption and Usage Behavior in Korean Companies: Applying the UTAUT Model. Behavioral Sciences, 14(11), 1035 https://doi.org/10.3390/bs14111035
Search via ReFindit
Kucharčíková, A., & Mičiak, M. (2018). Human Capital Management in Transport Enterprises with the Acceptance of Sustainable Development in the Slovak Republic. Sustainability, 10(7), 2530 https://doi.org/10.3390/su10072530
Search via ReFindit
Luis Romero-Gazquez, J., Canavate-Cruzado, G., & Bueno-Delgado, M.-V. (2022). IN4WOOD: A Successful European Training Action of Industry 4.0 for Academia and Business. Ieee Transactions on Education, 65(2), 200–209 https://doi.org/10.1109/TE.2021.3111696
Search via ReFindit
Moravcova-Skoludova, J., & Vlckova, A. (2018). The Factors Influencing Satisfaction of Generation Y in the Workplace in the Czech Republic. In H. Ribeiro, D. Naletina, & A. L. DaSilva (Eds.), Economic and Social Development (esd 2018): 35th International Scientific Conference (pp. 335–341). Varazdin Development & Entrepreneurship Agency. /jesi/article/6638
Search via ReFindit
Palazzan, L. (2022). The Future of Work in the Era of Emerging Technologies. Pensamiento, 78(298), 777–784 https://doi.org/10.14422/pen.v78.i298.y2022.026
Search via ReFindit
Rana, N. P., Alomar, J. A., Kumar, K., Epie, R., & Ovais, M. (2025). The Role of Technical and Top Management Support in the Continuance of Intention to Use Business Analytics. Journal of Global Information Management, 33(1), 379721 https://doi.org/10.4018/JGIM.379721
Search via ReFindit
Schmid, Y., & Dowling, M. (2022). New work: New motivation? A comprehensive literature review on the impact of workplace technologies. Management Review Quarterly, 72(1), 59–86 https://doi.org/10.1007/s11301-020-00204-7
Search via ReFindit
Selimovic, J., Pilav-Velic, A., & Krndzija, L. (2021). Digital workplace transformation in the financial service sector: Investigating the relationship between employees’ expectations and intentions. Technology in Society, 66, 101640 https://doi.org/10.1016/j.techsoc.2021.101640
Search via ReFindit
Silberg, S., Stehlík, L., Silberg, M., & Duriš, R. (2021). The factors affecting team performance and ability to innovate in a globalized world. SHS Web of Conferences, 129, 05013 https://doi.org/10.1051/shsconf/202112905013
Search via ReFindit
Smerek, L. (2025). Integrating Artificial Intelligence in Human Resource Management: A Comprehensive Review. In: Madzík, P., Lukáš, C., Karol, Č. (eds) Data-Centric Business and Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 253. Springer, Cham https://doi.org/10.1007/978-3-031-89718-4_22
Search via ReFindit
Spencer, D. A. (2023). Technology and work: Past lessons and future directions. Technology in Society, 74, 102294 https://doi.org/10.1016/j.techsoc.2023.102294
Search via ReFindit
Starecek, A., Bednarikova, M., Koltnerova, K., Vranakova, N., Gyurnak Babelova, Z., Caganova, D., & Chlpekova, A. (2018). The Level of Cognitive Abilities of Generational Group Y and Educational Process. 2018 16th International Conference on Emerging eLearning Technologies and Applications (ICETA), 511–518 https://doi.org/10.1109/ICETA.2018.8572200
Search via ReFindit
Trifan, V. A., & Pantea, M. F. (2023). The Receptivity of Younger Generation Romanian Employees to New Technology Implementation and Its Impact on the Balance Between Work and Life. Journal of Business Economics and Management, 24(3), 489–505 https://doi.org/10.3846/jbem.2023.19500
Search via ReFindit
Tursunbayeva, A., & Chalutz-Ben Gal, H. (2024). Adoption of artificial intelligence: A TOP framework-based checklist for digital leaders. Business Horizons, 67(4), 357–368 https://doi.org/10.1016/j.bushor.2024.04.006
Search via ReFindit
Żarczyńska-Dobiesz, A., & Chomątowska, B. (2014). Pokolenie Z na rynku pracy – wyzwania dla zarządzania zasobami ludzkimi. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, (350), 405–415 https://doi.org/10.15611/pn.2014.350.36
Search via ReFindit