<![CDATA[This study aims to analyze the determinants of Last Mile Delivery at PT Pos Indonesia Jakarta Oceania Main Branch through the mediating role of Distribution. This quantitative study employed the Structural Equation Modeling–Partial Least Squares (SEM-PLS) approach using SmartPLS 4. The study population consisted of 171 employees, while 121 respondents were selected as the research sample using the Slovin formula. The findings indicate that Distribution has a positive and significant effect on Last Mile Delivery (β = 0.359; t = 5.483; p < 0.001). Line Haul Transportation significantly influences Distribution (β = 0.328; t = 4.807; p < 0.001) and Last Mile Delivery (β = 0.252; t = 3.069; p = 0.002). Likewise, Mail Processing Centre has a positive and significant effect on Distribution (β = 0.444; t = 7.350; p < 0.001) and Last Mile Delivery (β = 0.249; t = 3.868; p < 0.001). Pickup Service also significantly affects Distribution (β = 0.155; t = 2.135; p = 0.033) and Last Mile Delivery (β = 0.141; t = 2.040; p = 0.042). Furthermore, Distribution significantly mediates the effects of Line Haul Transportation (β = 0.118; t = 3.698; p < 0.001), Mail Processing Centre (β = 0.160; t = 4.361; p < 0.001), and Pickup Service (β = 0.172; t = 4.861; p < 0.001) on Last Mile Delivery. The adjusted R² values of 0.394 for Distribution and 0.620 for Last Mile Delivery indicate that the proposed structural model possesses satisfactory explanatory power. These findings demonstrate that improving operational performance in Mail Processing Centre, Line Haul Transportation, and Pickup Service enhances Distribution effectiveness, which subsequently strengthens Last Mile Delivery performance within courier logistics services.]]>
