Research on Data Asset Assessment Methodology and its Application in the Transformation of New Quality Productivity

DOI

10.2991/978-94-6463-638-3_51How to use a DOI?

Keywords

Data asset valuation; new quality productivity transformation; deep learning; data trading models

Abstract

As data emerges as a critical production factor, research on data asset valuation and its role in productivity transformation has gained significant attention in both academic and business circles. This paper systematically reviews the existing data asset evaluation methods, including the cost, market, and income approaches, discussing their respective strengths, limitations, and suitable application contexts. Building on this foundation, we propose a deep learning-based data asset valuation model that incorporates multi-dimensional feature extraction, dynamic weight allocation, and an error adjustment mechanism, enabling more precise estimation of data assets’ economic potential. Additionally, we develop a model for converting data assets into new productive forces, examining their value-added impact in real-world production and quantifying their contribution to productivity using multi-level regression analysis and deep neural networks. Experimental results reveal a strong correlation between data assets’ value-added outcomes and their transformation efficiency into new productive forces, with dataset characteristics significantly influencing the transformation results.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Weili Li
PY  - 2024
DA  - 2024/12/30
TI  - Research on Data Asset Assessment Methodology and its Application in the Transformation of New Quality Productivity
BT  - Proceedings of the 5th International Conference on Economic Management and Big Data Application (ICEMBDA 2024)
PB  - Atlantis Press
SP  - 521
EP  - 528
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-638-3_51
DO  - 10.2991/978-94-6463-638-3_51
ID  - Li2024
ER  -