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Business Intelligence Modelling for Studying Science Parks Externalities

In: Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Valentina Mallamaci

    (Department of Law, Economics and Human Sciences and Decisions Lab, Mediterranea University)

  • Massimiliano Ferrara

    (Department of Law, Economics and Human Sciences and Decisions Lab, Mediterranea University
    ICRIOS, The Invernizzi Centre for Reasearch in Innovation, Organization, Strategy and Entrepreneurship - Bocconi University, Department of Management and Technology)

Abstract

The key to business success for many companies is the correct use of data to make better decisions. Companies need to use robust and efficient tools such as Business Intelligence (BI) as positive catalysts to achieve this goal, which can assist them in mechanizing the tasks of analysis, decision making, strategy formulation and forecasting. Therefore, the main objective of the work is to answer the question whether operationalization of Business Intelligence, Organizational Learning (OL) and Innovation can provide financial performance enhancement for companies. It is an applied research as it examines the theoretical structures in a real context of start-ups located in the Shanghai Zizhu Science-based Industrial Park to demonstrate what kind of externality it generates on participating companies. Research findings demonstrate that Business Intelligence and innovation have a critical influence on the companies conduct. But there was no meaningful relationship between Organizational Learning and financial performance of the same companies.

Suggested Citation

  • Valentina Mallamaci & Massimiliano Ferrara, 2022. "Business Intelligence Modelling for Studying Science Parks Externalities," Springer Books, in: Marco Corazza & Cira Perna & Claudio Pizzi & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 333-339, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-99638-3_54
    DOI: 10.1007/978-3-030-99638-3_54
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