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Evaluating maturity level of big data management and analytics in industrial companies

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  • Corallo, Angelo
  • Crespino, Anna Maria
  • Del Vecchio, Vito
  • Gervasi, Massimiliano
  • Lazoi, Mariangela
  • Marra, Manuela

Abstract

Manufacturing companies usually ignore their current state of big data and analytics implementation, losing the opportunity to achieve high-performance targets. An evaluation through maturity models can support companies to better focalise their initiatives. However, the existing maturity models only focus on big data, and they lack of a scientific development approach and applications. They are also general in scope and not specific for manufacturing scenarios.

Suggested Citation

  • Corallo, Angelo & Crespino, Anna Maria & Del Vecchio, Vito & Gervasi, Massimiliano & Lazoi, Mariangela & Marra, Manuela, 2023. "Evaluating maturity level of big data management and analytics in industrial companies," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:tefoso:v:196:y:2023:i:c:s0040162523005115
    DOI: 10.1016/j.techfore.2023.122826
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    References listed on IDEAS

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    1. Zhao, Guoqing & Xie, Xiaotian & Wang, Yi & Liu, Shaofeng & Jones, Paul & Lopez, Carmen, 2024. "Barrier analysis to improve big data analytics capability of the maritime industry: A mixed-method approach," Technological Forecasting and Social Change, Elsevier, vol. 203(C).

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