Task Allocation in Customer-led Two-sided Markets with Satellite Constellation Services

Fuente: arXiv
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Main Authors: Qiao, Jianglin, Cao, Zehong, de Jonge, Dave, Kowalczyk, Ryszard
Format: Preprint
Published: 2025
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author Qiao, Jianglin
Cao, Zehong
de Jonge, Dave
Kowalczyk, Ryszard
author_facet Qiao, Jianglin
Cao, Zehong
de Jonge, Dave
Kowalczyk, Ryszard
contents Multi-agent systems (MAS) are increasingly applied to complex task allocation in two-sided markets, where agents such as companies and customers interact dynamically. Traditional company-led Stackelberg game models, where companies set service prices, and customers respond, struggle to accommodate diverse and personalised customer demands in emerging markets like crowdsourcing. This paper proposes a customer-led Stackelberg game model for cost-efficient task allocation, where customers initiate tasks as leaders, and companies create their strategies as followers to meet these demands. We prove the existence of Nash Equilibrium for the follower game and Stackelberg Equilibrium for the leader game while discussing their uniqueness under specific conditions, ensuring cost-efficient task allocation and improved market performance. Using the satellite constellation services market as a real-world case, experimental results show a 23% reduction in customer payments and a 6.7-fold increase in company revenues, demonstrating the model's effectiveness in emerging markets.
format Preprint
id arxiv_https___arxiv_org_abs_2501_13364
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Task Allocation in Customer-led Two-sided Markets with Satellite Constellation Services
Qiao, Jianglin
Cao, Zehong
de Jonge, Dave
Kowalczyk, Ryszard
Computer Science and Game Theory
Multiagent Systems
Multi-agent systems (MAS) are increasingly applied to complex task allocation in two-sided markets, where agents such as companies and customers interact dynamically. Traditional company-led Stackelberg game models, where companies set service prices, and customers respond, struggle to accommodate diverse and personalised customer demands in emerging markets like crowdsourcing. This paper proposes a customer-led Stackelberg game model for cost-efficient task allocation, where customers initiate tasks as leaders, and companies create their strategies as followers to meet these demands. We prove the existence of Nash Equilibrium for the follower game and Stackelberg Equilibrium for the leader game while discussing their uniqueness under specific conditions, ensuring cost-efficient task allocation and improved market performance. Using the satellite constellation services market as a real-world case, experimental results show a 23% reduction in customer payments and a 6.7-fold increase in company revenues, demonstrating the model's effectiveness in emerging markets.
title Task Allocation in Customer-led Two-sided Markets with Satellite Constellation Services
topic Computer Science and Game Theory
Multiagent Systems
url https://arxiv.org/abs/2501.13364