Sura Al-Ayed

This study aims to examine the effect of digital opportunity recognition on students’ intentions and behavior related to digital entrepreneurship. The study measures the influence of digital opportunity recognition on antecedents of the theory of planned behavior and indirect influence on digital entrepreneurial intentions and behavior. This study employed a cross-sectional design. Data were collected from 2,840 students enrolled in professional management and entrepreneurship directions at universities in Saudi Arabia. The target sample consisted of individuals who have plans to become entrepreneurs. The findings indicated that digital opportunity recognition has a direct and significant effect on attitude, subjective norms, perceived self-efficacy, and an indirect effect on intentions and behavior toward digital entrepreneurship. Furthermore, this study checked multigroup differences between male and female samples: males show more favorable behavior toward digital entrepreneurship compared to females in Saudi Arabia. Collectively, the antecedents of the theory of planned behavior and digital opportunity recognition explained 65.1% of the variance in digital entrepreneurial behavior, with males at 68.2% and females at 63.2%. The research implication is that policymakers should prioritize integrating digital entrepreneurship into education curricula and providing support mechanisms to nurture the potential of digital-native students.

Acknowledgments
The author extends his appreciation to the Arab Open University for funding this work through Research Fund No. (AOUKSA-524008).

This study aims to investigate the relationships between artificial intelligence in human resources (HR), technology competence, and HR system strength within organizations. Employing a cross-sectional methodology, survey data were collected from 272 employees working in HR departments in the private sector of Saudi Arabia. Partial least squares structural equation modeling was utilized for analysis to evaluate these relationships. The results indicate a significant positive relationship between artificial intelligence in HR and both technology competence (β = 0.444, p < 0.001) and HR system strength (β = 0.539, p < 0.001). Additionally, there is a positive impact of technology competence on HR system strength (β = 0.272, p = 0.021). These findings underscore the importance of investing in AI technologies and enhancing employees’ technological skills to improve HR system effectiveness. Furthermore, the study emphasizes the necessity for organizations to prioritize agility and adaptability in HR strategies while addressing ethical and social considerations surrounding AI in HR practices. Moreover, the study elucidates the role of artificial intelligence in fostering innovation and sustainability within HR practices, contributing to organizational resilience and competitiveness.

Acknowledgment
The author extends her appreciation to the Arab Open University for funding this work through Research Fund No. (AOUKSA-524008).

The study aims to investigate how artificial intelligence (AI) influences women-led startups in Saudi Arabia, aiming to understand their unique experiences, challenges, and opportunities within the AI technology landscape. This study used a qualitative method, conducting 16 in-depth interviews with women entrepreneurs operating businesses in Saudi Arabia. The analysis was performed using thematic analysis with NVivo 12, uncovering key themes and insights. The findings reveal that cultural norms, societal expectations, limited awareness, and financial constraints are directly associated with women’s involvement in AI-driven businesses. Cultural biases emerged as impediments, underscoring the need for targeted interventions such as awareness campaigns and educational initiatives to dismantle ingrained biases and foster an environment that recognizes and celebrates the contributions of women in the tech and AI sectors. Educational programs, collaborations between academia and industry, and mentorship initiatives were identified as pivotal components to prepare women entrepreneurs to navigate the intricate landscape of AI adoption. Financial inclusion emerged as a critical pillar, advocating for equitable access to funding and resources tailored specifically for women-led AI startups. The study further emphasizes the importance of fostering supportive ecosystems that extend beyond financial aid. Creating networks for mentorship, guidance, and collaboration provides women entrepreneurs with platforms to share experiences and resources, enhancing resilience and the potential for success in the AI landscape.

Acknowledgment
The authors extend their appreciation to the Arab Open University for funding this work through research fund No. AOUKSA-524008.