Effect of digital opportunity recognition on students’ digital entrepreneurial intentions and behavior


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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.

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

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    • Figure 1. Research model
    • Figure 2. Structural equation model for the full sample (n = 2,840)
    • Figure 3. Structural equation model for the male sample (n = 1,134)
    • Figure 4. Structural equation model for the female sample (n = 1,706)
    • Table 1. Measurement model
    • Table 2. Discriminant validity
    • Table 3. Path coefficients (Direct effects)
    • Table 4. Indirect effects (male sample, n = 1,134)
    • Table 5. Indirect effects (female sample, n = 1,706)
    • Table 6. Coefficient of determination
    • Table 7. Multigroup analysis (MGA)
    • Conceptualization
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    • Data curation
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    • Formal Analysis
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    • Funding acquisition
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    • Investigation
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    • Methodology
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    • Project administration
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    • Resources
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    • Software
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    • Validation
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    • Visualization
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    • Writing – original draft
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    • Writing – review & editing
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