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Uncommon methods and metrics for local entrepreneurial ecosystems

Author

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  • Feldman, Maryann
  • Fleming, Lee
  • Heaton, Sohvi
  • Desai, Sameeksha
  • Teece, David

Abstract

Scholars are always searching for better data, new models and novel theories. This special issue presents new empirical approaches for studying local entrepreneurial ecosystems. Our objective is to provide insights into the state of the art of the new methodologies and uncommon data to study the dynamics and functioning of local entrepreneurial ecosystems. ‘Uncommon data’ refers to curated data from digital sources, with bespoke indicators derived from social media and interpretations derived from observation. The papers propose new methods and measures and draw upon a wide variety of empirical evidence, from large sample analyses of archival data to detailed qualitative investigations. The authors outline the need for multidisciplinary approaches and dynamic research designs that incorporate firm-level dynamics as a key dimension of entrepreneurial ecosystems. Taken together, the papers provide important insights into the major issues facing policymakers and researchers of entrepreneurship.

Suggested Citation

  • Feldman, Maryann & Fleming, Lee & Heaton, Sohvi & Desai, Sameeksha & Teece, David, 2022. "Uncommon methods and metrics for local entrepreneurial ecosystems," Research Policy, Elsevier, vol. 51(9).
    • Handle: RePEc:eee:respol:v:51:y:2022:i:9:s004873332200107x
    DOI: 10.1016/j.respol.2022.104583
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    References listed on IDEAS

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    4. Rabelo Neto, José & Figueiredo, Claudia & Gabriel, Bárbara Coelho & Valente, Robertt, 2024. "Factors for innovation ecosystem frameworks: Comprehensive organizational aspects for evolution," Technological Forecasting and Social Change, Elsevier, vol. 203(C).

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