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Human or Robot? Evidence from Last-Mile Delivery Service

Author

Listed:
  • Baorui Li
  • Xincheng Ma
  • Brian Rongqing Han
  • Daizhong Tang
  • Lei Fu

Abstract

As platforms increasingly deploy robots alongside human labor in last-mile logistics, little is known about how contextual features like product attributes, environmental conditions, and psychological mechanisms shape consumer preference in real-world settings. To address this gap, this paper conducts an empirical study on consumer choice between human versus robot service, analyzing 241,517 package-level choices from Alibaba's last-mile delivery stations. We identify how product privacy sensitivity, product value, and environmental complexity affect consumer preference. Our findings reveal that consumers are significantly more likely to choose robot delivery for privacy-sensitive packages (11.49%) and high-value products (0.97% per 1% increase in value), but prefer human couriers under adverse weather conditions (1.63%). These patterns are robust to alternative specifications and controls. These results also underscore that delivery choices are shaped not only by functional considerations but also by psychological concerns, highlighting the need for context-aware service design that aligns strategies with consumer perceptions.

Suggested Citation

  • Baorui Li & Xincheng Ma & Brian Rongqing Han & Daizhong Tang & Lei Fu, 2025. "Human or Robot? Evidence from Last-Mile Delivery Service," Papers 2509.11562, arXiv.org.
  • Handle: RePEc:arx:papers:2509.11562
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    References listed on IDEAS

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    1. Bing Bai & Hengchen Dai & Dennis J. Zhang & Fuqiang Zhang & Haoyuan Hu, 2022. "The Impacts of Algorithmic Work Assignment on Fairness Perceptions and Productivity: Evidence from Field Experiments," Manufacturing & Service Operations Management, INFORMS, vol. 24(6), pages 3060-3078, November.
    2. Pedro Amorim & Nicole DeHoratius & Fredrik Eng-Larsson & Sara Martins, 2024. "Customer Preferences for Delivery Service Attributes in Attended Home Delivery," Management Science, INFORMS, vol. 70(11), pages 7559-7578, November.
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