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The strategic use of big data analytics: applications in business practice and effects on firm performance

In: Research Handbook on Digital Strategy

Author

Listed:
  • Giovanni Battista Dagnino
  • Guglielmo La Bruna

Abstract

This chapter aims to analyze firms’ strategic use of big data analytics (AAs) in order to understand their applications in business practice and relevant effects on their performance. Actually, after looking closely at the four main types of AAs (i.e., descriptive analytics, predictive analytics, prescriptive analytics, and automated analytics), we feature the key factors driving the performance effects of AAs (some sectors benefit more than others of the positive effects of using AAs, information intensity of each sector is capable of influencing the effect of AAs on firm performance, and large firms are usually the ones having more direct access to AA advantages vis-à-vis SMEs), and discuss the strategic advantages and disadvantages arising from the adoption of AAs. Then, we highlight the main characteristics of the application of AAs in four relevant economic sectors (i.e., Finance and Insurance, Manufacturing, Healthcare, and Logistics and Supply Chain). Finally, we draw some conclusions and gather a few lines for future research in the expanding AA-performance domain.

Suggested Citation

  • Giovanni Battista Dagnino & Guglielmo La Bruna, 2023. "The strategic use of big data analytics: applications in business practice and effects on firm performance," Chapters, in: Carmelo Cennamo & Giovanni B. Dagnino & Feng Zhu (ed.), Research Handbook on Digital Strategy, chapter 19, pages 342-359, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:20348_19
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