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The effect of big data analytics capability on firm performance

Author

Listed:
  • Mahda Garmaki

    (IMT-BS - DSI - Département Systèmes d'Information - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris])

  • Imed Boughzala

    (IMT-BS - DSI - Département Systèmes d'Information - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - UEVE - Université d'Évry-Val-d'Essonne - TEM - Télécom Ecole de Management)

  • Samuel Fosso Wamba

    (NEOMA - Neoma Business School)

Abstract

Big data analytics (BDA) has emerged as an important area of study for both academics and practitioners. Despite of rising potential value of BDA, a few studies have been conducted to investigate the effect of BDA on firm performance. In this research in progress, according to the challenges of BDA dimensions (volume, variety, velocity, veracity and value) we propose the BDA capability dimensions in line with IT capability concept. BDA infrastructure capability, BDA management capability, BDA personnel capability and relational BDA capability provide the overall BDA Capability concept. The study, by employing dynamic capability, proposes that BDA capability impacts on firm financial and market performance by mediated effect of operational performance. The finding of this research by providing essential BDA capability and its effect on firm performance can apply as a roadmap and fill the gap between managers' expectation of BDA and what is emerged of BDA implementation.

Suggested Citation

  • Mahda Garmaki & Imed Boughzala & Samuel Fosso Wamba, 2016. "The effect of big data analytics capability on firm performance," Post-Print hal-01414811, HAL.
    • Handle: RePEc:hal:journl:hal-01414811
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    Citations

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    Cited by:

    1. Haili Zhang & Michael Song & Huanhuan He, 2020. "Achieving the Success of Sustainability Development Projects through Big Data Analytics and Artificial Intelligence Capability," Sustainability, MDPI, vol. 12(3), pages 1-23, January.
    2. Ciampi, Francesco & Demi, Stefano & Magrini, Alessandro & Marzi, Giacomo & Papa, Armando, 2021. "Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation," Journal of Business Research, Elsevier, vol. 123(C), pages 1-13.
    3. Ashaari, Mohamed Azlan & Singh, Karpal Singh Dara & Abbasi, Ghazanfar Ali & Amran, Azlan & Liebana-Cabanillas, Francisco J., 2021. "Big data analytics capability for improved performance of higher education institutions in the Era of IR 4.0: A multi-analytical SEM & ANN perspective," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    4. Kristoffersen, Eivind & Mikalef, Patrick & Blomsma, Fenna & Li, Jingyue, 2021. "Towards a business analytics capability for the circular economy," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    5. Russell Tatenda Munodawafa & Satirenjit Kaur Johl, 2019. "Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies," Sustainability, MDPI, vol. 11(15), pages 1-21, August.
    6. Patrick Mikalef & Ilias O. Pappas & John Krogstie & Michail Giannakos, 2018. "Big data analytics capabilities: a systematic literature review and research agenda," Information Systems and e-Business Management, Springer, vol. 16(3), pages 547-578, August.

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