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Big data technologies: An empirical investigation on their adoption, benefits and risks for companies

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  • Raguseo, Elisabetta

Abstract

Companies currently have to deal with profound changes in the way they manage their business, their customers and their business models, since they are overrun by a data-driven revolution in management. This revolution is due to the wide availability of big data and the fast evolution of big data technologies. Big data is recognized as one of the most important areas of future technology, and is fast gaining the attention of many industries, since it can provide high value to companies. This article investigates the adoption levels of big data technologies in companies, and the big data sources used by them. This article also points out the most frequently recognized strategic, transactional, transformational and informational benefits and risks related to the usage of big data technologies by companies. In order to achieve these aims, the paper looks at the differences that exist among companies of different sizes, by comparing medium-sized and large companies, and the differences among companies of different industrial sectors. It provides evidence that only in a few cases these differences are significant. This study could serve as a reference for managers who wish to initiate an evaluation cycle on the adoption and usage of big data technologies.

Suggested Citation

  • Raguseo, Elisabetta, 2018. "Big data technologies: An empirical investigation on their adoption, benefits and risks for companies," International Journal of Information Management, Elsevier, vol. 38(1), pages 187-195.
    • Handle: RePEc:eee:ininma:v:38:y:2018:i:1:p:187-195
    DOI: 10.1016/j.ijinfomgt.2017.07.008
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    References listed on IDEAS

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    1. Prasanna Tambe, 2014. "Big Data Investment, Skills, and Firm Value," Management Science, INFORMS, vol. 60(6), pages 1452-1469, June.
    2. Gandomi, Amir & Haider, Murtaza, 2015. "Beyond the hype: Big data concepts, methods, and analytics," International Journal of Information Management, Elsevier, vol. 35(2), pages 137-144.
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