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Innovation Management: Is Big Data Necessarily Better Data?

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  • JAHAN Sakila Akter

    (Independent University, Bangladesh)

  • SAZU Mesbaul Haque

    (Case Western Reserve University, USA)

Abstract

This study explores the relationship between firms’ application of data analytics (specifically it’s attributes) with the innovative performance of business. The other objective is to assess if large volume of data is necessarily more effective to drive business innovation. The study collected data through questionnaire survey from management staffs of 250 companies in both developed and developing economies. Statistical tools such as T-test and multiple regression methods were used to analyse the data. The study found suggestive proof demonstrating that data analytics is a pertinent determinant of a firm being innovator and bring innovative products and services to the market. The study also found that large volume of data is not necessarily better data to drive innovation. The findings imply that firms must utilize big data analytics to stay innovative and have a competitive advantage. Unlike previous studies that approached big data as whole, this study addresses various components of big data such as variety, volume, velocity, and their individual impacts on innovation in businesses across the developed economies.

Suggested Citation

  • JAHAN Sakila Akter & SAZU Mesbaul Haque, 2022. "Innovation Management: Is Big Data Necessarily Better Data?," Management of Sustainable Development, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 14(2), pages 27-33, December.
    • Handle: RePEc:blg:msudev:v:14:y:2022:i:2:p:27-33:n:6
    DOI: https://doi.org/10.54989/msd-2022-0013
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    References listed on IDEAS

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    1. Ghasemaghaei, Maryam & Calic, Goran, 2020. "Assessing the impact of big data on firm innovation performance: Big data is not always better data," Journal of Business Research, Elsevier, vol. 108(C), pages 147-162.
    2. Hau L. Lee, 2018. "Big Data and the Innovation Cycle," Production and Operations Management, Production and Operations Management Society, vol. 27(9), pages 1642-1646, September.
    3. Shengbin Hao & Haili Zhang & Michael Song, 2019. "Big Data, Big Data Analytics Capability, and Sustainable Innovation Performance," Sustainability, MDPI, vol. 11(24), pages 1-15, December.
    4. Bresciani, Stefano & Ciampi, Francesco & Meli, Francesco & Ferraris, Alberto, 2021. "Using big data for co-innovation processes: Mapping the field of data-driven innovation, proposing theoretical developments and providing a research agenda," International Journal of Information Management, Elsevier, vol. 60(C).
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