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1.

Factors affecting cybersecurity awareness: A qualitative study in Saudi Arabia Pages 751-762 Right click to download the paper Download PDF

Authors: Tariq Saleh, Raed Kanaan, Rania Alzubaidi, Ghassan Ghazi Kanaan, Marko Nino

DOI: 10.5267/j.uscm.2024.12.005

Keywords: Cybersecurity awareness, Information security, Unified theory of acceptance and use of technology, Technology acceptance model, Thematic analysis, Protection motivation theory

Abstract:
The objective of this research was to gain a deeper comprehension of how individuals perceive and respond to cybersecurity and how various internal and external factors influence these behaviors and attitudes. Conducted at ABC organization in Saudi Arabia, the study employed the qualitative methodology. Two online focus groups were employed featuring open-ended questions. The data were subsequently analyzed thematically using inductive and deductive coding techniques. Several theories were used as theoretical lenses to analyze the data. After the collected data had been analyzed, three main themes emerged: (a) perceived safeguards and threats, (b) personal and professional experience in information security, and (c) necessity of education and raising awareness. Additionally, two sub-themes were revealed: (a) costs and benefits and (b) necessity of safeguard measures and attaining trust. The study’s identified themes and sub-themes offer a thorough comprehension of the demographic, social, cultural, and internalized factors influencing cybersecurity-related behavior. The identified themes could potentially be applicable to other settings. Future qualitative research could further explore the transferability of these findings by conducting similar studies in different organizational, cultural, and linguistic contexts. It is also recommended for future quantitative research to delve deeper than surface-level data and consider underlying meaning, factors, connections, or relationships that may skew the results. It is crucial to delve into hidden meanings, not just accept data at face value.
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Journal: USCM | Year: 2025 | Volume: 13 | Issue: 4 | Views: 895 | Reviews: 0

 

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