<?xml version="1.0" encoding="UTF-8"?>
<doi_batch version="5.3.1" xmlns="http://www.crossref.org/schema/5.3.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:jats="http://www.ncbi.nlm.nih.gov/JATS1" xmlns:ai="http://www.crossref.org/AccessIndicators.xsd" xsi:schemaLocation="http://www.crossref.org/schema/5.3.1 http://www.crossref.org/schema/deposit/crossref5.3.1.xsd">
 <head>
  <doi_batch_id>aspg-3-2522-1791419449</doi_batch_id>
  <timestamp>20261008003049</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
  </depositor>
  <registrant>American Scientific Publishing Group</registrant>
 </head>
 <body>
  <journal>
   <journal_metadata language="en">
    <full_title>Fusion: Practice and Applications</full_title>
    <abbrev_title>FPA</abbrev_title>
    <issn media_type="print">2770-0070</issn>
    <issn media_type="electronic">2692-4048</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2024</year>
    </publication_date>
    <journal_volume>
     <volume>15</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Utilizing Big Data Analysis for the Fusion Examination of Labor Market Evolution within the Gig Economy</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Muhammad Eid</given_name>
      <surname>Balbaa</surname>
      <affiliations>
       <institution>
        <institution_name>Tashkent State University of Economics, Uzbekistan</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Astanakulov Olim</given_name>
      <surname>Tashtemirovich</surname>
      <affiliations>
       <institution>
        <institution_name>International Islamic Academy of Uzbekistan, Uzbekistan</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>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.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2024</year>
    </publication_date>
    <pages>
     <first_page>59</first_page>
     <last_page>65</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">2522</item_number>
    </publisher_item>
    <ai:program name="AccessIndicators">
     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
    </ai:program>
    <doi_data>
     <doi>10.54216/FPA.150105</doi>
     <resource>https://www.americaspg.com/journal/3/article/2522</resource>
     <collection property="text-mining">
      <item>
       <resource mime_type="application/pdf">https://www.americaspg.com/storage/11708978273.pdf</resource>
      </item>
     </collection>
    </doi_data>
   </journal_article>
  </journal>
 </body>
</doi_batch>
