Behavioral Biases and Financial Decision-Making in Digital Entrepreneurial Ecosystems: Strategic Insights for Prospective Entrepreneurs
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Background: The rapid expansion of digital financial services and fintech platforms has increased decision-making complexity, leaving prospective entrepreneurs within university startup ecosystems vulnerable to cognitive biases that alter managerial judgment and strategic resource allocation. Objective: This study aims to examine the simultaneous influence of overconfidence bias, anchoring bias, and loss aversion on financial decision-making among undergraduate students as prospective digital entrepreneurs, while controlling for their field of study. Methods: A quantitative explanatory design was adopted using a cross-sectional survey of 143 undergraduate students selected through purposive sampling based on their personal financial and digital service management experience. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4. Results: The structural model demonstrates that overconfidence bias exerts the strongest positive effect on financial decision-making, followed by loss aversion and anchoring bias, whereas field of study shows no statistically significant effect, revealing that cognitive psychological biases override formal academic specialization in financial choices. Conclusion: These findings highlight that enhancing managerial capability in entrepreneurial ecosystems requires moving beyond conventional technical financial education. Incubators and higher education institutions must implement structured behavioral finance interventions, including cognitive debiasing toolkits and evidence-based decision-making frameworks, to mitigate excessive overconfidence, prevent risk-averse innovation inertia, and foster sustainable digital venture performance.
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