Navigating the Gig Economy: Talent identification in tripartite work arrangements in Morocco

The gig economy is transforming the traditional employment landscape in Morocco, introducing both challenges and opportunities for talent identification. As online labor platforms such as Upwork, Fiverr, and Uber become increasingly prevalent, they facilitate the connection between freelance workers and SMEs seeking flexible labor solutions. This paper delves into the intricacies of tripartite work arrangements that encompass these platforms, the requesters (SMEs), and the gig workers themselves. By examining these relationships, we uncover the unique aspects of talent identification within the Moroccan gig economy. Our study employs a mixed-method approach, combining qualitative interviews and quantitative surveys to gather comprehensive data from various stakeholders.We identify that while online platforms employ standardized algorithms for talent identification, these methods often overlook local cultural and linguistic nuances critical to the Moroccan context. SMEs in Morocco tend to heavily rely on platform-mediated ratings and reviews, which underscores the trust placed in these digital reputation systems. Furthermore, our findings reveal that gig workers who invest in skill development and actively manage their online reputations are more likely to secure consistent and lucrative opportunities.This research provides a conceptual framework for understanding the complexities of talent identification in Morocco's gig economy, offering valuable insights for enhancing talent management practices. We propose several recommendations for platforms to refine their algorithms, for SMEs to develop more robust evaluation criteria, and for gig workers to focus on continuous skill enhancement. This paper not only contributes to the academic discourse on gig work but also provides practical guidelines for stakeholders to navigate and optimize talent identification processes in Morocco's evolving labor market.