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V-Matrix: A wave theory of value creation for big data

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  • Geerts, Guido L.
  • O'Leary, Daniel E.

Abstract

This paper examines the “V-Matrix” and provides a wave theory life cycle model of organizations’ adoption of big data. The V-Matrix is based on the big data five “V’s”: Volume, Velocity, Variety, Veracity, and Value and captures and enumerates the different potential states that an organization can go through as part of its adoption and evolution towards big data. We extend the V-Matrix to a state space approach in order to provide a characterization of the adoption of big data technologies in an organization. We develop and use a wave theory of implementation to accommodate a firm’s movement through the V-Matrix. Accordingly, the V-Matrix provides a life cycle model of organizational use of the different aspects of big data. In addition, the model can help organizations’ plan for decision-making use of big data as they anticipate movement from one state to another, as they add big data capabilities. As part of this analysis, the paper examines some of the issues that occur in the different states, including synergies and other issues associated with co-occurrence of different V’s with each other. Finally, this paper integrates the V-Matrix with other data analytic life cycles and examines some of the implications of those models.

Suggested Citation

  • Geerts, Guido L. & O'Leary, Daniel E., 2022. "V-Matrix: A wave theory of value creation for big data," International Journal of Accounting Information Systems, Elsevier, vol. 47(C).
    • Handle: RePEc:eee:ijoais:v:47:y:2022:i:c:s1467089522000276
    DOI: 10.1016/j.accinf.2022.100575
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    References listed on IDEAS

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    1. Daniel E. O'Leary, 2013. "‘Big Data’, The ‘Internet Of Things’ And The ‘Internet Of Signs’," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(1), pages 53-65, January.
    2. Martin Hilbert, 2016. "Big Data for Development: A Review of Promises and Challenges," Development Policy Review, Overseas Development Institute, vol. 34(1), pages 135-174, January.
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