Unpacking societal barriers to technology adoption: a multi-theoretical analysis of user behavior in last mile delivery applications in urban developing contexts

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Abstract Last-mile delivery (LMD) applications are expanding rapidly in developing urban contexts; however, technology adoption and continued use remain uneven due to societal and geographic barriers. This study investigates how digital literacy-related capabilities and constraints impact LMD app adoption outcomes in Alexandria, with a focus on user behavior as a mediator and district-level differences as a contextual moderator. A cross-sectional survey was conducted across Alexandria’s East, Middle, and West districts ( N = 2120). The measurement and structural models were evaluated using covariance-based structural equation modeling (CB-SEM) in AMOS, which included confirmatory factor analysis, model fit assessment, and multi-group comparisons across districts. The results indicate that digital literacy-related constructs significantly shape user behavior toward LMD apps, which in turn influences subjective well-being and social inclusion. Indirect effects reveal both beneficial and potentially adverse pathways, highlighting the paradoxical role of digital literacy. District-level comparisons indicate meaningful geographic variation in key relationships. By integrating UTAUT and SST, this study explains LMD adoption as both a technological and socially embedded process. The findings offer implications for platform design and public policy aimed at reducing intra-city adoption inequalities and strengthening inclusive digital participation.

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