2692-4048ISSN (Online)
2770-0070ISSN (Print)
Volume 15 , Issue 1 , PP: 59-65, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Muhammad Eid Balbaa 1 * , Astanakulov Olim Tashtemirovich 2
Doi: https://doi.org/10.54216/FPA.150105
The advent of the gig economy has triggered an unprecedented transformation in labor markets worldwide. Leveraging an intricate network analysis, this paper aims to delve into the multi-layered complexities of labor market metamorphosis within the context of a digital gig economy. We construct a bipartite labor-market network model that allows us to explore the nexus between gig workers and employment platforms using a robust set of parameters – connectivity, centrality, and clustering coefficient. Consequently, our empirical investigation elucidates how traditional labor market paradigms are being disrupted, engendering the emergence of new socio-economic stratifications. The results unveil a counterintuitive network structure where high centrality does not necessarily correlate with enhanced economic benefits for gig workers. Moreover, the findings underscore the potential pitfalls of a skewed clustering coefficient, manifesting as increased vulnerability to systemic shocks. The ubiquity of digital technology has engendered a seismic shift in economic frameworks, predominantly by initiating the concept of the gig economy. Although a plethora of research has been conducted on the gig economy from various disciplinary vantage points, limited endeavors have been undertaken to explore the intricacies of labor market changes via a network analysis paradigm. As a result, this study provides vital insights for policymakers, platform operators, and labor market participants, promoting a nuanced understanding of the gig economy’s implications for labor market architecture.
Gig Economy , Labor Market , Data Analysis , Fusion Examination , Transformation.
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