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La Business Intelligence e la Business Analytics nell?era dei Big Data: una analisi della letteratura

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Listed:
  • Arianna Petrosino
  • Daniela Mancini
  • Stefano Garzella
  • Rita Lamboglia

Abstract

This research project is a preliminary study based on a literature review aiming at understanding the relevance of Business Intelligence (BI) and Business Analytics (BA) in the context of Big Data (BD). We focus our attention on BI and BA as in-struments to support the decision-making processes. The aims of this preliminary analysis is twofold. To draw a picture of the progress of studies regarding BI and BA in the era of BD, identifying the research centres that dealt with this topic, the major journals for the research purpose and the main research lines. To understand the relationship between these three key concept analysing publication and conference proceedings in different disciplinary fields. We consider the Web of Science database, and we select 25 documents. According to this analysis, we identify three main streams of research concerning decision process challenges, the fields of employment of BI and BA technologies, and im-plementation methodologies. We also highlight the importance to develop research on the differences and the interconnections between BI and BA, the field of adop-tion of predictive and prescriptive models.

Suggested Citation

  • Arianna Petrosino & Daniela Mancini & Stefano Garzella & Rita Lamboglia, 2018. "La Business Intelligence e la Business Analytics nell?era dei Big Data: una analisi della letteratura," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(3), pages 31-58.
    • Handle: RePEc:fan:macoma:v:html10.3280/maco2018-003003
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    References listed on IDEAS

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    1. Maria Serena Chiucchi & Marco Gatti, 2015. "Editoriale. L?evoluzione degli studi di management control: un percorso nel segno della variet?," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2015(1), pages 5-8.
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    3. Luciano Marchi, 2018. "Quale metodologia di ricerca sulle tematiche di Management Control?," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(2), pages 5-10.
    4. Daniela Mancini, 2016. "Accounting Information Systems in an Open Society. Emerging Trends and Issues," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2016(1), pages 5-16.
    5. Michele Galeotti & Stefano Garzella & Raffaele Fiorentino & Gaetano della Corte, 2016. "The Strategic Intelligence implications for Information Systems," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2016(1), pages 105-123.
    6. Shao, Benjamin B.M. & Lin, Winston T., 2016. "Assessing output performance of information technology service industries: Productivity, innovation and catch-up," International Journal of Production Economics, Elsevier, vol. 172(C), pages 43-53.
    7. Appelbaum, Deniz & Kogan, Alexander & Vasarhelyi, Miklos & Yan, Zhaokai, 2017. "Impact of business analytics and enterprise systems on managerial accounting," International Journal of Accounting Information Systems, Elsevier, vol. 25(C), pages 29-44.
    8. Jung Cheol Shin & Soo Jeung Lee & Yangson Kim, 2012. "Knowledge-based innovation and collaboration: a triple-helix approach in Saudi Arabia," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(1), pages 311-326, January.
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    1. Marco Montemari & Christian Nielsen, 2021. "Big data for business modeling: Towards the next generation of performance measurement systems?," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2021(suppl. 1), pages 5-10.
    2. Francesco Badia & Fabio Donato, 2022. "Opportunities and risks in using big data to support management control systems: A multiple case study," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2022(3), pages 39-63.

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