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  • Peer-reviewed
  • Print ISSN:
    2289-2125
    Online ISSN:
    2637-0301


Volume 12 Issue 1 2026

Advancing the Entrepreneurial Success Components Theory: Developing the Advanced Entrepreneurial Career Success Framework
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Ravi Nagarathanam, Gengeswari Krishnapillai, Dinesh Kumar Saundra Rajan

Entrepreneurial career development is a complex, nonlinear process shaped by cognitive, motivational, and contextual factors. While the Entrepreneurial Success Components Theory (ESCT) provides foundational insights into entrepreneurial readiness, its original structure lacks the depth required to explain how individuals translate entrepreneurial potential into intentional and sustained entrepreneurial behaviour. This conceptual paper introduces the Advanced Entrepreneurial Career Success Framework (AECSF), an expanded and modernised version of ESCT that incorporates key cognitive mediators, refined constructs, and expanded behavioural pathways. The AECSF integrates ten core components (opportunity recognition, market analysis, entrepreneurial ability, entrepreneurship education, previous experience, resource recognition ability, entrepreneurial motivation, social support, entrepreneurial career intentions, and entrepreneurial career behaviour) which provide a holistic view of the entrepreneurial journey. Central to the model are two sequential mediators: opportunity recognition and entrepreneurial career intentions, which explain how foundational success factors evolve into entrepreneurial action. Grounded in the Theory of Planned Behaviour, Social Cognitive Career Theory, and opportunity recognition literature, the AECSF addresses conceptual gaps in the original ESCT and offers stronger explanatory power for entrepreneurial career choice, particularly in emerging economies such as Malaysia. The framework contributes theoretical clarity and practical implications for entrepreneurship education, policy design, and ecosystem development. Future research is recommended to empirically validate the AECSF through qualitative and quantitative methods.


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