Paper Number

ICIS2025-2774

Paper Type

Complete

Abstract

Since the emergence of generative AI (GenAI), many service providers have launched general-purpose GenAI platforms to assist users with a variety of tasks. In an effort to meet personalized customer demands, some providers have introduced marketplaces that enable users to create custom GenAI services and earn monetary rewards. However, it remains unclear whether such marketplaces are always beneficial—an issue underexplored in existing literature. This paper seeks to fill this gap by employing a game-theoretic framework to examine the impact of these marketplaces on profitability and service design. Our findings suggest that introducing a marketplace may sometimes harm profitability. Furthermore, the providers’ decisions regarding the quality of free services are influenced by the difficulty involved in creating custom services. Additionally, as the value of custom data increases, raising the per-usage payment rate can become sub-optimal. This study offers valuable insights for key stakeholders in the GenAI ecosystem.

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12-GenAI

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Dec 14th, 12:00 AM

The Economics of Marketplaces for User-Generated Custom GenAI Services: Implications for General-Purpose Service Quality and Profitability

Since the emergence of generative AI (GenAI), many service providers have launched general-purpose GenAI platforms to assist users with a variety of tasks. In an effort to meet personalized customer demands, some providers have introduced marketplaces that enable users to create custom GenAI services and earn monetary rewards. However, it remains unclear whether such marketplaces are always beneficial—an issue underexplored in existing literature. This paper seeks to fill this gap by employing a game-theoretic framework to examine the impact of these marketplaces on profitability and service design. Our findings suggest that introducing a marketplace may sometimes harm profitability. Furthermore, the providers’ decisions regarding the quality of free services are influenced by the difficulty involved in creating custom services. Additionally, as the value of custom data increases, raising the per-usage payment rate can become sub-optimal. This study offers valuable insights for key stakeholders in the GenAI ecosystem.

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