Artificial intelligence and dynamic capabilities: how startups can thrive in entrepreneurial ecosystems amid disruptive change
Antonio Cimino (),
Ciro Troise (),
Vincenzo Corvello () and
Stefano Bresciani ()
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Antonio Cimino: University of Messina, Contrada di Dio S. Agata
Ciro Troise: University of Turin
Vincenzo Corvello: University of Messina, Contrada di Dio S. Agata
Stefano Bresciani: University of Turin
International Entrepreneurship and Management Journal, 2025, vol. 21, issue 1, No 97, 26 pages
Abstract:
Abstract Artificial intelligence has emerged as a leading force among disruptive technologies, significantly reshaping the business landscape. Startups, due to their agility and innovation potential, are uniquely positioned to leverage artificial intelligence’s transformative power. This study investigates how the strategic behavior of startups influences their success within entrepreneurial ecosystems, particularly during periods marked by rapid technological disruption. Employing the dynamic capabilities framework, the research introduces a theoretical model to evaluate entrepreneurial ecosystems success across two dimensions: the organizational level, which pertains to individual startup outcomes, and the ecosystem level, which reflects the broader ecosystem’s performance. The model’s validity was tested through structural equation modeling using a partial least squares approach, based on data from a structured survey of 210 startups listed in Italy’s official Business Register of Innovative Startups. Results reveal a strong, positive relationship between startups’ dynamic capabilities and the performance of entrepreneurial ecosystems in times of disruptive change. Moreover, the integration of artificial intelligence is identified as a key driver of ecosystem-wide success. The paper concludes with practical insights for startups navigating disruptive environments and outlines directions for future research.
Keywords: Disruptive technology; Artificial intelligence; Entrepreneurial ecosystem; Dynamic capability; Innovation performance (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11365-025-01146-w
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