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Open Access

Back to the Future: From Platform Economy to Decentralized Economy

Sangtian Guan1Juanjuan Li2( )Siji Ma1Xiaolong Liang2Xiao Xue3Fei-Yue Wang1,4
Faculty of Innovation Engineering, Macau University of Science and Technology, Macau 999078, China
The State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
The College of Intelligence and Computing, Tianjin University, Tianjin 300072, China
Research Center for Chinese Economics and Social Security, The University of Chinese Academy of Sciences, Beijing 100190, China
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Abstract

This paper discusses the technological development from Web 1.0 to Web 3.0, focusing on their corresponding economic models. The study begins by analyzing the Web 1.0 portal economy, followed by an in-depth exploration of the rise of the Web 2.0 platform economy and its associated challenges, including the lemon market, platform monopolies, price discrimination, and algorithmic asymmetries. To address those issues, this study elaborates on the Web 3.0 token economy and emphasizes the crucial role of decentralized technologies like blockchain in bringing new production factors and relationships. This inspires the proposal of the Decentralized Economy (DeEco), a novel user-autonomous economic model that integrates advanced Artificial Intelligence (AI) technologies with blockchain. Furthermore, the key techniques for formulating DeEco are analyzed, including Decentralized Autonomous Organizations and Operations (DAOs), Decentralized Value Systems (DVSs), Decentralized Physical Infrastructure Networks (DePIN) and digital humans. This study not only offers a co-evolutionary perspective of web technologies and economic forms but also introduces an innovative economic paradigm to support open, diverse and intelligent societies.

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International Journal of Crowd Science
Pages 117-127

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Cite this article:
Guan S, Li J, Ma S, et al. Back to the Future: From Platform Economy to Decentralized Economy. International Journal of Crowd Science, 2026, 10(2): 117-127. https://doi.org/10.26599/IJCS.2025.9100009

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Received: 28 September 2024
Revised: 22 April 2025
Accepted: 28 May 2025
Published: 11 June 2026
© The author(s) 2026.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).