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Conceptualizing data-driven entrepreneurship: from knowledge creation to entrepreneurial opportunities and innovation.

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Authors: Grimaldi, Mara1 (AUTHOR) margrimaldi@unisa.it, Troisi, Orlando2 (AUTHOR) otroisi@unisa.it, Papa, Armando3,4,5 (AUTHOR) apapa@unisa.it, de Nuccio, Elbano6 (AUTHOR) denuccio@lum.it
Source: Journal of Technology Transfer. Jun2026, Vol. 51 Issue 3, p1341-1392. 52p.
Subject Terms: *Big data, *Entrepreneurship, *Business enterprises, *Business development, *Digital transformation, *Technological innovations, *Intellectual capital, *Statistical decision making
Abstract: Digital transformation and the possibility to collect large amount of data, the so-called big data, from different sources can lead to the redefinition of business processes, models and infrastructures. In this respect, data-driven decision making (DDDM) emphasizes the need to rethink management practices to view data as a driving force that can improve the effectiveness of decisions and nurture innovation. Over time, data-driven principles have been reframed as the foundations for the development of a new mind-set that considers data as a key asset that redesigns entrepreneurship and encompasses orientation, culture and human resources management to help entrepreneurs catch, evaluate and launch entrepreneurial opportunities that can improve technology and knowledge by stimulating innovation. For this reason, the study aims at reconceptualizing entrepreneurship according to a multi-levelled perspective based on the integration of cultural, human, knowledge-based and technological dimension to assess the impact of data-driven management on entrepreneurial opportunities creation and on the development of different kinds of innovation. To assess these goals, empirical research based on constructivist grounded theory and on the administration of semi-structured interviews is performed through the investigation of an Italian public–private Consortium specialized in big data. The findings allow the elaboration of a conceptual framework which classifies the activities of data-driven entrepreneurial processes, the phases of opportunity creation and the different kinds of innovation enabled in the Consortium by guiding entrepreneurs and managers in the elaboration of effective data analysis strategies. [ABSTRACT FROM AUTHOR]
Database: Entrepreneurial Studies Source
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  Data: *<searchLink fieldCode="DE" term="%22Big+data%22">Big data</searchLink><br />*<searchLink fieldCode="DE" term="%22Entrepreneurship%22">Entrepreneurship</searchLink><br />*<searchLink fieldCode="DE" term="%22Business+enterprises%22">Business enterprises</searchLink><br />*<searchLink fieldCode="DE" term="%22Business+development%22">Business development</searchLink><br />*<searchLink fieldCode="DE" term="%22Digital+transformation%22">Digital transformation</searchLink><br />*<searchLink fieldCode="DE" term="%22Technological+innovations%22">Technological innovations</searchLink><br />*<searchLink fieldCode="DE" term="%22Intellectual+capital%22">Intellectual capital</searchLink><br />*<searchLink fieldCode="DE" term="%22Statistical+decision+making%22">Statistical decision making</searchLink>
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  Data: Digital transformation and the possibility to collect large amount of data, the so-called big data, from different sources can lead to the redefinition of business processes, models and infrastructures. In this respect, data-driven decision making (DDDM) emphasizes the need to rethink management practices to view data as a driving force that can improve the effectiveness of decisions and nurture innovation. Over time, data-driven principles have been reframed as the foundations for the development of a new mind-set that considers data as a key asset that redesigns entrepreneurship and encompasses orientation, culture and human resources management to help entrepreneurs catch, evaluate and launch entrepreneurial opportunities that can improve technology and knowledge by stimulating innovation. For this reason, the study aims at reconceptualizing entrepreneurship according to a multi-levelled perspective based on the integration of cultural, human, knowledge-based and technological dimension to assess the impact of data-driven management on entrepreneurial opportunities creation and on the development of different kinds of innovation. To assess these goals, empirical research based on constructivist grounded theory and on the administration of semi-structured interviews is performed through the investigation of an Italian public–private Consortium specialized in big data. The findings allow the elaboration of a conceptual framework which classifies the activities of data-driven entrepreneurial processes, the phases of opportunity creation and the different kinds of innovation enabled in the Consortium by guiding entrepreneurs and managers in the elaboration of effective data analysis strategies. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s10961-024-10176-5
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 52
        StartPage: 1341
    Subjects:
      – SubjectFull: Big data
        Type: general
      – SubjectFull: Entrepreneurship
        Type: general
      – SubjectFull: Business enterprises
        Type: general
      – SubjectFull: Business development
        Type: general
      – SubjectFull: Digital transformation
        Type: general
      – SubjectFull: Technological innovations
        Type: general
      – SubjectFull: Intellectual capital
        Type: general
      – SubjectFull: Statistical decision making
        Type: general
    Titles:
      – TitleFull: Conceptualizing data-driven entrepreneurship: from knowledge creation to entrepreneurial opportunities and innovation.
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            NameFull: Grimaldi, Mara
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            NameFull: Troisi, Orlando
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            NameFull: Papa, Armando
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            NameFull: de Nuccio, Elbano
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            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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            – TitleFull: Journal of Technology Transfer
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