Paper Type

ERF

Abstract

The cross-border online gig work, in which the job seekers and the job offering firms , mediated by digital platforms, are globally spread out, present unique challenges. The research intends to model and analyse the impact of tax on the platform; particularly, the effect on the prices charged by the platform, in response to the imposed tax, to the stakeholders on either side of this two-sided marketplace. Using a game theoretic approach, different scenarios are created, with varying price effect and cross-side network effect. The sequential game played out shows the decisions of the different stakeholders as a result of the price change and the resulting sub-game perfect Nash equilibrium. The result shows that it may not always be beneficial for the platform to pass on the tax shock to the entire gig ecosystem, as it may reduce its revenue due to the prevalence of cross-side network effect.

Paper Number

1871

Author Connect URL

https://authorconnect.aisnet.org/conferences/AMCIS2025/papers/1871

Comments

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Aug 15th, 12:00 AM

Impact of Taxation on Cross-Border Digital Gig Work Platforms: A Game theoretic approach

The cross-border online gig work, in which the job seekers and the job offering firms , mediated by digital platforms, are globally spread out, present unique challenges. The research intends to model and analyse the impact of tax on the platform; particularly, the effect on the prices charged by the platform, in response to the imposed tax, to the stakeholders on either side of this two-sided marketplace. Using a game theoretic approach, different scenarios are created, with varying price effect and cross-side network effect. The sequential game played out shows the decisions of the different stakeholders as a result of the price change and the resulting sub-game perfect Nash equilibrium. The result shows that it may not always be beneficial for the platform to pass on the tax shock to the entire gig ecosystem, as it may reduce its revenue due to the prevalence of cross-side network effect.

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