A Semiotic Framework for Data Asset Valuation

Kecheng Liu (), Hua Guo (), Tao Wang () and Haotian Su
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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

A chapter in LISS 2023, 2024, pp 878-887 from Springer

Abstract: 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.

Keywords: Data assets; Data valuation; Semiotic framework; Digital economy; Sense-making; Valuation metrics (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-981-97-4045-1_69

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