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A Semiotic Framework for Data Asset Valuation

In: Liss 2023

Author

Listed:
  • Kecheng Liu

    (University of Reading)

  • Hua Guo

    (Queen Mary University of London)

  • Tao Wang

    (Shanxi University of Finance and Economics)

  • Haotian Su

    (Shanxi University of Finance and Economics)

Abstract

The valuation of data assets is a critical task in the digital economy, enabling organizations to make informed decisions and allocate resources effectively. However, traditional economic approaches to data asset valuation have limitations in capturing the distinct characteristics and challenges of data assets. In this paper, we propose a semiotic framework for data asset valuation, drawing inspiration from organizational semiotics. Our framework acknowledges that data valuation is a process of sense-making, known as semiosis, and identifies three key semiotic aspects - syntactics, semantics, and pragmatics - that shape the value realization of data assets. By incorporating crucial factors such as subjectivity, context dependency, and purpose dependency, we offer a structured approach comprising aspects, factors, and metrics for data asset valuation. The proposed framework not only contributes to advancing the field of data asset valuation but also serves as a foundation for further studies and exploration in this area.

Suggested Citation

  • Kecheng Liu & Hua Guo & Tao Wang & Haotian Su, 2024. "A Semiotic Framework for Data Asset Valuation," Lecture Notes in Operations Research, in: Daqing Gong & Yixuan Ma & Xiaowen Fu & Juliang Zhang & Xiaopu Shang (ed.), Liss 2023, pages 878-887, Springer.
    • Handle: RePEc:spr:lnopch:978-981-97-4045-1_69
    DOI: 10.1007/978-981-97-4045-1_69
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