Adaptive Multi-Method Valuation of Technological Intangible Assets in Asset-Light Firms: Exploratory Evidence from Public Technology Transactions and Listed-Company Cases

Xiaohan Yang

doi:10.54691/9z6g7243

Authors

Xiaohan Yang Dongbei University Of Finance And Economics, Dalian, China

DOI:

https://doi.org/10.54691/9z6g7243

Keywords:

Asset-light firms, technological intangible assets, patent valuation, multi-method valuation, adaptive weighting.

Abstract

The role of technological intangible assets in the asset-light company is key to value creation, but limitations of the traditional valuation approaches exist at the various stages of commercialisation. This study presents an adaptive multi-method valuation framework by using both cost, income and market approaches in conjunction with historical-error-based weighting and leave-one-out validation. The three approaches have mean relative deviations of 25.14%, 10.01%, and 8.27%, respectively, based on 15 observations of the valuations. Results indicate that, valuation performance differs between assets and information conditions. The framework prevents leakage of information about the benchmark, offers the option of choosing a method when one method has a clear advantage, and offers a reproducible and interpretable tool for technology transfer, investment, financing and intangible-asset management.

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References

[1] Xu, A., Cheng, C., & Zhu, Y. (2022). A new comprehensive measurement method for patent value and its application. The Journal of Quantitative & Technical Economics, 39(3), 130–151.

[2] Xu, A., Cheng, C., & Zhu, Y. (2022). Measuring patent value in China based on an improved patent renewal model: Statistical characteristics of high-value invention patents. Statistical Research, 39(3), 3–20.

[3] Qi, Y., & Wang, H. (2017). Factors influencing the value of technological achievements based on a hedonic price model. Science Research Management, 38(3), 94–103.

[4] Wan, X., & Zhu, X. (2008). An evaluation indicator system and fuzzy comprehensive evaluation of patent value. Science Research Management, (2), 185–191.

[5] Xue, M., & Liu, L. (2013). Determinants of patent value in the context of patent-pledge lending. Science Research Management, (2), 120–127.

[6] Fischer, T., & Leidinger, J. (2014). Testing patent value indicators on directly observed patent value: An empirical analysis of Ocean Tomo patent auctions. Research Policy, 43(3), 519–529.

[7] Harhoff, D., Scherer, F. M., & Vopel, K. (2003). Citations, family size, opposition and the value of patent rights. Research Policy, 32(8), 1343–1363.

[8] Grimaldi, M., Cricelli, L., Di Giovanni, M., & Rogo, F. (2015). The patent portfolio value analysis: A new framework to leverage patent information for strategic technology planning. Technological Forecasting and Social Change, 94, 286–302.

[9] Song, H., Hou, J., & Zhang, Y. (2023). The measurements and determinants of patent technological value: Lifetime, strength, breadth, and dispersion from the technology diffusion perspective. Journal of Informetrics, 17(1), 101370.

[10] Hu, Z., Zhou, X., & Lin, A. (2023). Evaluation and identification of potential high-value patents in the field of integrated circuits using a multidimensional patent indicators pre-screening strategy and machine learning approaches. Journal of Informetrics, 17(2), 101406.