Research on Company Valuation Methods based on Data Traffic -- Taking Tencent as an Example

DOI

10.2991/978-94-6463-811-0_4How to use a DOI?

Keywords

Data-Driven Valuation; Corporate Valuation; Metcalfe’s Law

Abstract

With the advent of the digital economy era, the valuation of Internet enterprises is encountering novel challenges. Traditional valuation methods, such as the dividend discount model (DDM) and the discounted free cash flow model (DCF), exhibit significant limitations when applied to Internet companies. This is primarily due to the unique characteristics of data traffic, which is the core asset of these enterprises. Data traffic is dynamic, influenced by network effects, and possesses ecological synergistic value, making it difficult to accurately evaluate using conventional approaches. This paper aims to explore a company valuation method based on data traffic. Taking Tencent as an example, it analyses the practical application value of data traffic indicators in the valuation of Internet enterprises. By reviewing mainstream valuation methods and their application scenarios, the paper proposes a valuation logic based on data traffic, with the goal of providing investors with a more forward-looking basis for value judgment.

Copyright

© 2025 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  - Zhuohang Xie
PY  - 2025
DA  - 2025/08/14
TI  - Research on Company Valuation Methods based on Data Traffic -- Taking Tencent as an Example
BT  - Proceedings of the 2025 5th International Conference on Enterprise Management and Economic Development (ICEMED 2025)
PB  - Atlantis Press
SP  - 26
EP  - 36
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-811-0_4
DO  - 10.2991/978-94-6463-811-0_4
ID  - Xie2025
ER  -