Building a Framework for Inclusive Talent Development in Platform-Based Work
Keywords:
Platform-based work, talent development, algorithmic management, digital labor, inclusionAbstract
This study aimed to explore how platform-based workers develop skills and navigate structural, social, and algorithmic challenges to achieve inclusive talent development in the context of digital labor in Tehran. This qualitative research employed an exploratory design using semi-structured interviews with 25 participants engaged in various platform-based occupations, including freelance, ride-hailing, and delivery work. Participants were selected through purposive sampling, ensuring demographic and experiential diversity. Data collection continued until theoretical saturation was reached. All interviews were transcribed and analyzed using NVivo software. Thematic analysis was conducted through open, axial, and selective coding procedures to identify main themes and subthemes related to skill development and inclusion mechanisms. Thematic analysis revealed four central categories: access to skill development opportunities, algorithmic mediation of opportunity, structural barriers to inclusion, and self-driven career navigation. Participants frequently relied on informal learning, peer support, and strategic adaptation to overcome limited access to formal training. Algorithmic visibility and reputational systems significantly influenced work opportunities, often reinforcing inequality and emotional labor demands. Structural constraints such as gender discrimination, digital exclusion, and socioeconomic disadvantage were identified as major obstacles to equitable growth. Nonetheless, participants demonstrated high levels of resilience, self-branding, and long-term planning in navigating fragmented work environments. Peer collaboration and emotional regulation were also key strategies for sustaining engagement and enhancing employability. Findings highlight that inclusive talent development in platform-based work is a multidimensional process shaped by individual agency, platform infrastructure, and broader socio-technical systems. Informal learning and strategic navigation are critical, yet insufficient without platform-level and policy-level reforms. A comprehensive framework for inclusion must address algorithmic transparency, accessible training, and community-based support to promote equitable growth in the digital labor economy.
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