The hidden machinery of entrepreneurial culture: a data mining approach of ecosystem-level drivers

Purpose This study investigates the main contextual determinants of entrepreneurial culture (EC) in emerging ecosystems, interpreting EC as an intangible resource that affects the dynamics of Intellectual Capital within entrepreneurial ecosystems. It analyzes how factors based on the pillars of such ecosystems influence perceptions regarding structural conditions associated with creativity and innovation in a given region. Design/methodology/approach A quantitative data mining approach was applied to survey data from 193 ventures funded by the São Paulo Research Foundation in Brazil, considering six EE pillars: financial support, regulatory environment, government assistance, infrastructure, social factors and education and training. After preprocessing and feature selection, classification was performed using a combination of machine learning techniques, evaluated through fivefold cross-validation with accuracy and ROC curve. A sensitivity analysis, based on feature exclusion and performance comparison, further validated the robustness of the predictive approach. Findings The feature importance analysis revealed that the most influential factors of an EC in the ecosystem were social perceptions of entrepreneurship, financial accessibility and physical infrastructure conditions. These elements indicate a strong interplay between EC and elements associated with human, structural, and relational manifestations of intellectual capital in the dynamics of entrepreneurial ecosystems. Originality/value This study contributes conceptually by demonstrating that elements traditionally viewed as supporting structures are, in fact, core drivers of EC in ecosystems. Methodologically, it validates the use of data mining techniques to analyze and predict behavioral patterns within entrepreneurial ecosystems. From a practical standpoint, the findings inform policy interventions aimed at strengthening financing systems, infrastructure and regulatory environments, while also guiding entrepreneurs and investors in overcoming barriers to digital transformation and fostering entrepreneurial innovation.

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Publication Details

Journal
Journal of Intellectual Capital
Published
2025-12-09
DOI
https://doi.org/10.1108/jic-04-2025-0125
Primary Topic
Entrepreneurship Studies and Influences
Type
article
Field-Weighted Citation Impact
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article

The hidden machinery of entrepreneurial culture: a data mining approach of ecosystem-level drivers

Journal of Intellectual Capital
Entrepreneurship Studies and Influences
article

The hidden machinery of entrepreneurial culture: a data mining approach of ecosystem-level drivers

article en

Abstract

Purpose This study investigates the main contextual determinants of entrepreneurial culture (EC) in emerging ecosystems, interpreting EC as an intangible resource that affects the dynamics of Intellectual Capital within entrepreneurial ecosystems. It analyzes how factors based on the pillars of such ecosystems influence perceptions regarding structural conditions associated with creativity and innovation in a given region. Design/methodology/approach A quantitative data mining approach was applied to survey data from 193 ventures funded by the São Paulo Research Foundation in Brazil, considering six EE pillars: financial support, regulatory environment, government assistance, infrastructure, social factors and education and training. After preprocessing and feature selection, classification was performed using a combination of machine learning techniques, evaluated through fivefold cross-validation with accuracy and ROC curve. A sensitivity analysis, based on feature exclusion and performance comparison, further validated the robustness of the predictive approach. Findings The feature importance analysis revealed that the most influential factors of an EC in the ecosystem were social perceptions of entrepreneurship, financial accessibility and physical infrastructure conditions. These elements indicate a strong interplay between EC and elements associated with human, structural, and relational manifestations of intellectual capital in the dynamics of entrepreneurial ecosystems. Originality/value This study contributes conceptually by demonstrating that elements traditionally viewed as supporting structures are, in fact, core drivers of EC in ecosystems. Methodologically, it validates the use of data mining techniques to analyze and predict behavioral patterns within entrepreneurial ecosystems. From a practical standpoint, the findings inform policy interventions aimed at strengthening financing systems, infrastructure and regulatory environments, while also guiding entrepreneurs and investors in overcoming barriers to digital transformation and fostering entrepreneurial innovation.

Journal of Intellectual Capital
National Research University Higher School of Economics (RU), Hospital de Clínicas da Unicamp (BR)
Reduced inequalities
Openalex Percentile: Top 30%
Entrepreneurship Studies and Influences
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