Evolutionary Dynamics of Gig Economy Labor Strategies under Technology, Policy and Market Influence
Kevin Hu, Feng Fu

TL;DR
This paper models the evolutionary dynamics of gig economy labor strategies influenced by technology, policy, and market conditions using a novel game-theoretical approach, revealing distinct patterns for high and low skill workers.
Contribution
It introduces an extended replicator equation with oscillating dynamics and a new payoff framework to analyze gig economy evolution under changing environments and policies.
Findings
Market conditions lead to different gig-labor preferences for high and low skill workers.
Changing policies significantly impact firm and worker strategies in the gig economy.
Technology influences the growth and evolution of gig labor dynamics.
Abstract
The emergence of the modern gig economy introduces a new set of employment considerations for firms and laborers that include various trade-offs. With a game-theoretical approach, we examine the influences of technology, policy and markets on firm and worker preferences for gig labor. Theoretically, we present a new extension to the replicator equation and model oscillating dynamics in two-player asymmetric bi-matrix games with time-evolving environments, introducing concepts of the attractor arc, trapping zone and escape. We demonstrate how changing market conditions result in distinct evolutionary patterns for gig-labor preferences across high and low skill work-forces, which we explain through their differing sensitivities to market-driven consumer demand and financial incentives among other considerations. Informing tensions regarding the future of this new employment category, we…
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Taxonomy
TopicsDigital Economy and Work Transformation · Sharing Economy and Platforms · Digital Platforms and Economics
