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.

This study aimed to develop and empirically validate an integrated model for continuous smart government service usage. This model integrates constructs from the unified theory of acceptance and use of the technology framework with the expectation-confirmation model, along with an additional construct: trust. Structural equation modeling (SEM) was used to analyze data collected via online questionnaires from 369 people who utilized smart government services in the United Arab Emirates. Next, an artificial neural networks model was used to rank the relative influence of the significant predictors identified through SEM analysis. The findings reveal that, among the significant predictors affecting the continuous use of smart government services, facilitating conditions, satisfaction, and perceived usefulness had the most substantial impact. Furthermore, this study highlights the direct influence of perceived usefulness, confirmation, facilitating conditions, effort expectancy, social influence, and public trust on citizen satisfaction.

Today and in highly competitive and fast-paced arena of the world, industrial companies focus on achieving technological superiority through the effective use of world modern-day technologies in the production and operation process associated with all their available resources. With using this procedure, these industrial companies try to achieve long-term and sustainable competitive advantages. On the other hand, applying world modern technologies does not solely guarantee success of these companies, rather, preparing preliminary grounds associated with the acceptance of technology will be decisive in this field. This article deals with clarifying factors affecting the adoption of new technologies and showing relationship of these factors together. For this purpose, Unified Theory of Acceptance and Use of Technology (UTAUT) Model has been used to study factors affecting the adoption of new technologies. In the same direction, relationship between constituent components of this model has been studied with regard to the acceptance of new technology of Electro-Slag Remelting (ESR) in Esfarayen Steel Industry Complex using FUZZY DEMATEL Technique.