Template-Type: ReDIF-Article 1.0
Author-Name: Monica Mihaela Maer Matei
Author-Email: monica.maer@incsmps.ro
Author-Workplace-Name: Bucharest University of Economic Studies, Romania
Author-Name: Anamaria Nastasa
Author-Email: anamaria.nastasa@incsmps.ro
Author-Workplace-Name: National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania
Author-Name: Andreea-Monica Munteanu
Author-Email: monica.munteanu@csie.ase.ro
Author-Workplace-Name: Bucharest University of Economic Studies, Romania
Author-Name: Adriana AnaMaria Davidescu
Author-Email: adriana.davidescu@incsmps.ro
Author-Workplace-Name: National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania
Author-Email: cristina.mocanu@incsmps.ro
Author-Workplace-Name: National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania
Author-Name: Eliza Olivia Enno
Author-Email: 
Author-Workplace-Name: Mitsui Bussan Secure Directions co. Ltd./ Cyber Resilience DivisionAnalytics & Data Science, Japan
Title: Exploring small business profiles in cybersecurity skills
Abstract: Protecting sensitive data and ensuring secure operations in an interconnected world is crucial for companies, requiring new approaches and skills. This research paper aims to categorise small businesses based on their prioritisation of cybersecurity issues and their practices for handling cybersecurity tasks, with a focus on training and awareness. The Correspondence Analysis and Latent Class Model are used to identify associations between skills and firms' characteristics, respectively, to determine if there are hidden patterns among firms that might affect their responses. Using data collected from the Flash Eurobarometer 547 Cyberskills, we identified three distinct company profiles based on their attitudes towards cybersecurity (disengaged firms - 16%, partially engaged firms - 52% and proactive firms - 32%), influenced by turnover, industry and digital technology use. This research simplifies the data structure to understand small businesses' cybersecurity diversity. The results can inform research and practice by tailoring strategies and uncovering new insights.
Keywords: cybersecurity skills, latent class analysis, correspondence analysis, SMEs, European Union, Flash Eurobarometer 547
Pages: 87-110
Volume: 17
Year: 2026
Month: June
DOI: https://doi.org/10.47743/ejes-2026-0104
File-URL: https://ejes.uaic.ro/articles/EJES2026_1701_04_MAE.pdf
File-Format: Application/pdf
Handle: RePEc:jes:eurint:y:2026:v:17:p:87-110