Startup adaptability and resilience as drivers of entrepreneurial orientation: A quantitative analysis of Greek startups

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Type of the article: Research Article

This paper explores the extent to which adaptability and resilience affect dimensions of entrepreneurial orientation in a sample of 239 Greek startups operating in various sectors registered in Elevate Greece. Α quantitative research design was applied to collect data from November 2024 to May 2025, using a structured 18-item questionnaire developed from existing measurement scales of entrepreneurial orientation and measured on a 5-point Likert scale. Descriptive statistics, chi-square independence tests, hypothesis testing, and multiple regression analyses were applied to examine the relationships between adaptability, resilience-related factors, and dimensions of entrepreneurial orientation. Statistical analysis documents a strong association between entrepreneurial orientation and both adaptability and resilience, as all hypotheses are strongly supported (p < .001). In addition, the findings indicate that adaptability-related factors significantly predict proactiveness (p < .001), while two of the three resilience-related factors (allocation of research and development resources and strategic alliances) appear to have a strong positive effect on innovativeness (p < .001). Autonomy demonstrates partial strong associations with both constructs, through one adaptability factor (organizational structure) and one resilience factor (employees’ connection to work). Finally, resilience-related factors have less predictive effect on risk-taking. Overall, the results indicate that the adaptability and resilience of Greek startups require a combination of internal and external capabilities.

Acknowledgment
This study has been funded by the Democritus University of Thrace.

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    • Table 1. Profile of respondents
    • Table 2. Examination of H1
    • Table 3. Examination of H2
    • Table 4. Examination of H3
    • Table 5. Examination of H4
    • Table 6. Examination of H5
    • Table 7. Multiple regression analysis
    • Conceptualization
      Christina Arfara, Anastasios Karasavvoglou
    • Data curation
      Christina Arfara, Anastasios Karasavvoglou
    • Formal Analysis
      Christina Arfara, Anastasios Karasavvoglou
    • Investigation
      Christina Arfara, Anastasios Karasavvoglou
    • Methodology
      Christina Arfara, Anastasios Karasavvoglou
    • Project administration
      Christina Arfara, Anastasios Karasavvoglou
    • Resources
      Christina Arfara
    • Validation
      Christina Arfara, Anastasios Karasavvoglou
    • Visualization
      Christina Arfara
    • Writing – original draft
      Christina Arfara, Anastasios Karasavvoglou
    • Writing – review & editing
      Christina Arfara, Anastasios Karasavvoglou
    • Funding acquisition
      Anastasios Karasavvoglou
    • Supervision
      Anastasios Karasavvoglou