隨著全球經濟成長與科技進步推動都市化快速發展，物流需求不斷攀升，然而部分地區普遍面臨配送效率低落、物流成本高昂與服務可及性不足等挑戰，限制地方發展潛力與居民生活品質，尤其在偏鄉地區。都市地區則因交通壅塞與即時配送需求強烈而增加運作複雜性，顯示「最後一哩」在不同區域條件下皆面臨多元挑戰。既有研究雖採用系統性文獻回顧探討最後一哩配送，但多聚焦於特定運具，缺乏跨運具的比較，且少有進一步統合分析，致使無法獲得通用性的結論。本研究遂以多運具為情境，結合系統性文獻回顧與統合分析，以探索影響最後一哩配送之關鍵因素，彌補研究缺口並提供更一致的理解。蒐集2007年至2025年間收錄於Web of Science、Scopus與Google scholar之100篇中英文文獻，並閱讀文獻後建立資料庫歸納應變數及自變數。另以傳統機動運具(卡車)為基礎，比較與分析其他可能運輸方式(非傳統機動運具、先進運具、公共運具)，歸納各類配送模式於不同區域的適用性與成效，並以多項羅吉斯迴歸模型檢驗影響因素之效果。結果顯示，營運方式、技術與能源類型為關鍵因素。傳統機動運具如卡車適合大宗配送，卻受制於成本與基礎設施；先進運具如無人機與自動配送機器人具突破地形與時效需求的潛力，但仍受法規與技術限制；非傳統機動運具如電動機車與腳踏車則因高機動性適合城市高頻配送；公共運具如公車與計程車則透過客貨共載提升整合效率；另有眾包物流、共享經濟與電子商務等新興模式亦能增進效率並降低成本。隨機效果分析進一步指出，易腐商品與客貨共載為相對穩定的影響因素，具一致性。本研究不僅深化對最後一哩配送運具策略之理解，亦補足過往研究方法與結論不足，並提出具體政策建議，以強化配送系統之可行性、永續性與韌性，促進區域物流均衡與服務公平。

Rapid urbanization driven by global economic growth and technological advancement has intensified logistics demand, yet both rural and urban regions continue to face distinct last-mile delivery challenges, including inefficiency, high costs, and limited accessibility. Existing studies mostly focus on specific transport modes and lack cross-modal comparisons and meta-analytic validation, leading to inconsistent findings. This research integrates a systematic review and meta-analysis to identify key factors influencing last-mile delivery across different transport modes. Based on 100 English and Chinese publications (2007~2025) from Web of Science, Scopus, and Google scholar, data were extracted using conventional motorized vehicles as the baseline to compare non-conventional, advanced, and public transport modes. Results from multinomial logistic regression reveal that operational models, technology, and energy type are critical determinants. Conventional vehicles suit bulk deliveries but face cost and infrastructure limits; advanced modes such as drones and robots offer potential yet face regulatory constraints; non-conventional and public modes enhance mobility and integration through co-loading. Random-effects analysis further highlights perishable goods and passenger–cargo co-loading as stable influencing factors. The study enriches understanding of last-mile transport strategies and provides policy implications to enhance the feasibility, sustainability, and resilience of logistics systems.

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