The rise of crowdsourced delivery has transformed last-mile logistics by leveraging gig workers and community resources to meet the growing demands of e-commerce and urbanization. This narrative review aims to synthesize current research on operational efficiency, consumer adoption, workforce dynamics, technological innovation, sustainability, and regulatory challenges. Literature was systematically identified from databases such as Scopus, Web of Science, and Google Scholar using targeted keywords and Boolean operators, with inclusion criteria focusing on peer-reviewed studies between 2010 and 2025. The review highlights that optimization algorithms, including machine learning and reinforcement learning, substantially improve routing and scheduling efficiency. Consumer adoption is strongly influenced by trust, transparency, and usability, while gig workers face challenges of precarious employment, inconsistent compensation, and customer injustice. Technological innovations such as blockchain, smart contracts, digital twins, and hybrid drone-human delivery models enhance transparency, security, and operational responsiveness. Sustainability outcomes are notable, with evidence of reduced emissions and strengthened community-based logistics. Nevertheless, systemic barriers remain, including fragmented regulatory frameworks, uneven technological readiness, and unresolved labor protections. These findings underscore the urgency of policy interventions to ensure fair labor standards, incentivize sustainable practices, and strengthen digital infrastructure. Future research should expand geographic coverage, investigate worker equity, and adopt interdisciplinary approaches. This review concludes that balancing efficiency, consumer trust, worker rights, and regulatory clarity is essential for developing resilient and sustainable crowdsourced delivery systems.
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