From Manual Delivery to Autonomous Delivery Robots: A Socio-Technical Push–Pull–Mooring Framework

• Xueli Tan ^[1] ; Dongphil Chun ^[2] ; Shuxian Zhao ^[2] ; Yanfeng Liu ^[1]
  1. [1] School of Northeast Asia Studies, Shandong University,China
  2. [2] Pukyong National University,Busan, Republic of Korea
• Localización: Journal of Theoretical and Applied Electronic Commerce Research, ISSN-e 0718-1876, Vol. 21, Nº. 1, 2026
• Idioma: inglés
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• Resumen

  • Urban delivery demand continues to rise, intensifying last-mile logistics challenges and accelerating the transition from manual delivery to autonomous delivery robots (ADRs). This study investigates the behavioral mechanisms underlying consumers’ migration toward ADRs. Grounded in the socio-technical systems perspective, we integrate the Push–Pull–Mooring (PPM) model with Social Cognitive Theory (SCT) to explain how technological and social stimuli shape switching and continuance intentions through cognitive and emotional pathways. Survey data from 786 Chinese consumers, analyzed using second-order structural equation modeling, support the proposed framework. The results indicate that dissatisfaction with manual delivery (push) and perceived benefits of ADRs (pull) significantly enhance both switching and continuance intentions. Outcome expectancy positively predicts switching intention but negatively predicts continuance intention. Technophobia reduces switching intention but does not significantly influence continuance. Moreover, social norms moderate key relationships, highlighting the role of external social influence in technology transition. This study extends PPM research into the smart logistics context, introduces socio-cognitive mechanisms into technology switching analysis, and conceptually distinguishes switching and continuance intentions as separate constructs. The findings offer practical guidance for ADR developers and policymakers by emphasizing strategies to reduce emotional resistance, enhance social endorsement, and promote the sustainable adoption of autonomous delivery technologies.