Economic Annals-XXI: Volume 208, Issue (3-4), Pages: 55-69
Citation information:
Tolegen, M., Rovnyakova, I., Radchenko, N., & Sakhariyeva, S. (2024). Crowdsourcing as a social phenomenon in Kazakhstan: opportunities and risks for professional careers. Economic Annals-XXI, 208(3-4), 55-69. doi: https://doi.org/10.21003/ea.V208-07
Mukhtar Tolegen
PhD (Law),
Professor,
S. Amanzholov East Kazakhstan University
34 30th Gvardeiskoy Divisii Str., Ust-Kamenogorsk, 070002, Republic of Kazakhstan
mukhtar_t80@mail.ru
ORCID ID: https://orcid.org/0000-0003-2673-622X
Irina Rovnyakova
PhD (Pedagogy),
Associate Professor
of the Department of Pedagogical Education and Management,
S. Amanzholov East Kazakhstan University
34 30th Gvardeiskoy Divisii Str., Ust-Kamenogorsk, 070002, Republic of Kazakhstan
ivr1906@mail.ru
ORCID ID: https://orcid.org/0009-0008-5034-2611
Natalya Radchenko
PhD (Pedagogy),
Associate Professor
of the Department of Pedagogical Education and Management,
S. Amanzholov East Kazakhstan University
34 30th Gvardeiskoy Divisii Str., Ust-Kamenogorsk, 070002, Republic of Kazakhstan
radchenko76@inbox.ru
ORCID ID: https://orcid.org/0000-0003-1407-3684
Svetlana Sakhariyeva
PhD (Pedagogy),
Associate Professor
of the Department of Pedagogical Education and Management,
S. Amanzholov East Kazakhstan University
34 30th Gvardeiskoy Divisii Str., Ust-Kamenogorsk, 070002, Republic of Kazakhstan
Sakhariyeva@mail.ru
ORCID ID: https://orcid.org/0000-0003-2776-8645
Crowdsourcing as a social phenomenon in Kazakhstan: opportunities and risks for professional careers
Abstract. The study examines crowdsourcing development in Kazakhstan during 2015-2023, focusing on its impact on professional careers and labor market transformation across 12 major cities. The research provides comprehensive analysis of digital platforms’ integration into the professional environment and workforce adaptation to new forms of employment, with particular attention to regional disparities and socioeconomic implications.
The research employs a robust mixed-method approach combining extensive web scraping of 15 major crowdsourcing platforms, large-scale quantitative surveys encompassing 2,500 crowdworkers and 500 employers, 100 in-depth interviews with key stakeholders, 20 focus groups, and detailed netnographic analysis of 5,000 online interactions. Data analysis utilized SPSS 27.0 for statistical processing, achieving a high reliability coefficient of α = 0.88, with additional qualitative analysis through NVivo 12 for thematic coding.
The empirical analysis revealed significant platform adoption growth from 23% in 2015 to 87% in 2023, with predominant participation from workers aged 18-34 (68%). Average monthly platform-based income reached $850, with substantial sectoral variations across IT (42%), design (28%), and content creation (18%). Platform engagement demonstrated strong correlation with skills improvement among 76% of participants, though significant urban-rural disparities emerged, showing a 45% income gap between metropolitan and peripheral areas. Longitudinal analysis indicated steady growth in platform-based employment, with annual increases averaging 15% over the study period.
Statistical analysis demonstrates a strong correlation between platform engagement and career growth (r = 0.72, p < 0.001), while highlighting persistent challenges in digital infrastructure access and skill development. Urban areas demonstrate 3.2 times higher platform adoption rates compared to rural regions, with 65% of participants reporting income instability and 58% expressing concerns about inadequate social protection mechanisms. The research identifies critical intervention points for policy development and stakeholder engagement to address these challenges.
Scientific Novelty. This research presents the first comprehensive mapping of Kazakhstan’s crowdsourcing ecosystem using an innovative methodology that combines digital ethnography with economic analysis. The study introduces the novel Platform Career Impact Index for measuring professional development in the digital economy, along with standardized assessment tools for digital labor market analysis, contributing significantly to the theoretical framework of platform economy research in developing markets.
Practical Significance. The research has generated a comprehensive three-tier recommendations framework addressing governmental regulation, platform operations, and worker development. These findings have been directly implemented in the IRN grant AP14871794 project and adopted by three major national digital platforms, with measurable impact on policy development and platform governance. The study’s recommendations have influenced the development of new legislative frameworks for digital labor regulation and contributed to the establishment of standardized fair compensation systems across major platforms in Kazakhstan.
Keywords: Crowdsourcing; Digital Labor; Skill; Employment; Development; Professional Career; Future of Work; Workforce; Worker; IT; Kazakhstan; Platform Career Impact Index; Opportunity; Competence; Task; HR; HRM
JEL Classіfіcatіon: I23; I28; O33; L86; M15; D83; I21
Acknowledgements and Funding: The work was performed according to the IRN grant AP14871794 «Using crowdsourcing technology as a predictor of professional training of future specialists».
Contribution: The authors contributed equally to this work.
Data Availability Statement: The dataset is available from the authors upon request.
DOI: https://doi.org/10.21003/ea.V208-07
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Received 11.01.2024
Received in revised form 9.02.2024
Accepted 19.02.2024
Available online 28.04.2024