# Flattening Supply Chains: When do Technology Improvements lead to Disintermediation?

arXiv: https://arxiv.org/abs/2502.20783 · HTML: https://mlsanity.com/paper/2502.20783/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 27 references that are in the map.
- First posted on arXiv 28 Feb 2025.

## Builds on (most cited first, 14 of 14)

- [Modeling Content Creator Incentives on Algorithm-Curated Platforms](https://mlsanity.com/paper/2206.13102/) (2022)
- [A Game-Theoretic Approach to Recommendation Systems with Strategic Content Providers](https://mlsanity.com/paper/1806.00955/) (2018)
- [Supply-Side Equilibria in Recommender Systems](https://mlsanity.com/paper/2206.13489/) (2022)
- [Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach](https://mlsanity.com/paper/2008.00104/) (2020)
- [How Bad is Top-K Recommendation under Competing Content Creators?](https://mlsanity.com/paper/2302.01971/) (2023)
- [Human vs. Generative AI in Content Creation Competition: Symbiosis or Conflict?](https://mlsanity.com/paper/2402.15467/) (2024)
- [The Impact of Large Language Models on Open-source Innovation: Evidence from GitHub Copilot](https://mlsanity.com/paper/2409.08379/) (2024)
- [Competition and Diversity in Generative AI](https://mlsanity.com/paper/2412.08610/) (2024)
- [Learning with Exposure Constraints in Recommendation Systems](https://mlsanity.com/paper/2302.01377/) (2023)
- [Braess's Paradox of Generative AI](https://mlsanity.com/paper/2409.05506/) (2024)
- [Selective Response Strategies for GenAI](https://mlsanity.com/paper/2502.00729/) (2025)
- [Matching of Users and Creators in Two-Sided Markets with Departures](https://mlsanity.com/paper/2401.00313/) (2023)
- [How to Strategize Human Content Creation in the Era of GenAI?](https://mlsanity.com/paper/2406.05187/) (2024)
- [Supply Network Formation and Fragility](https://mlsanity.com/paper/2001.03853/) (2020)

## Built on by (most cited first, 2 of 2)

- [Modeling the Economic Impacts of AI Openness Regulation](https://mlsanity.com/paper/2507.14193/) (2025)
- [LLM Detection as an Intervention: Downstream Impact under Strategic User Behavior](https://mlsanity.com/paper/2607.19300/) (2026)

## Abstract (arXiv)

In the digital economy, technological innovations make it cheaper to produce high-quality content. For example, generative AI tools reduce costs for creators who develop content to be distributed online, but can also reduce production costs for the users who consume that content. These innovations can thus lead to disintermediation, since consumers may choose to use these technologies directly, bypassing intermediaries. To investigate when technological improvements lead to disintermediation, we study a game with an intermediary, suppliers of a production technology, and consumers. First, we show disintermediation occurs whenever production costs are too high or too low. We then investigate the consequences of disintermediation for welfare and content quality at equilibrium. While the intermediary is welfare-improving, the intermediary extracts all gains to social welfare and its presence can raise or lower content quality. We further analyze how disintermediation is affected by the level of competition between suppliers and the intermediary's fee structure. More broadly, our results take a step towards assessing how production technology innovations affect the survival of intermediaries and impact the digital economy.