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家门口的机器人:对未来近景自动化包裹投递技术的接受程度。

Robots at your doorstep: acceptance of near-future technologies for automated parcel delivery.

机构信息

Department of Civil and Environmental Engineering, Northwestern University, A308 Technological Institute, 2145 Sheridan Road, Evanston, IL, 60208, USA.

Department of Civil and Environmental Engineering, Northwestern University, A312 Technological Institute, 2145 Sheridan Road, Evanston, IL, 60208, USA.

出版信息

Sci Rep. 2023 Oct 29;13(1):18556. doi: 10.1038/s41598-023-45371-1.

DOI:10.1038/s41598-023-45371-1
PMID:37899375
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10613628/
Abstract

The logistics and delivery industry is undergoing a technology-driven transformation, with robotics, drones, and autonomous vehicles expected to play a key role in meeting the growing challenges of last-mile delivery. To understand the public acceptability of automated parcel delivery options, this U.S. study explores customer preferences for four innovations: autonomous vehicles, aerial drones, sidewalk robots, and bipedal robots. We use an Integrated Nested Choice and Correlated Latent Variable (INCLV) model to reveal substitution effects among automated delivery modes in a sample of U.S. respondents. The study finds that acceptance of automated delivery modes is strongly tied to shipment price and time, underscoring the importance of careful planning and incentives to maximize the trialability of innovative logistics options. Older individuals and those with concerns about package handling exhibit a lower preference for automated modes, while individuals with higher education and technology affinity exhibit greater acceptance. These findings provide valuable insights for logistics companies and retailers looking to introduce automation technologies in their last-mile delivery operations, emphasizing the need to tailor marketing and communication strategies to meet customer preferences. Additionally, providing information about appropriate package handling by automated technologies may alleviate concerns and increase the acceptance of these modes among all customer groups.

摘要

物流和配送行业正在经历一场技术驱动的转型,机器人、无人机和自动驾驶车辆预计将在应对最后一英里配送的日益增长的挑战方面发挥关键作用。为了了解公众对自动化包裹投递选择的接受程度,这项美国研究探讨了客户对以下四项创新的偏好:自动驾驶车辆、空中无人机、人行道机器人和双足机器人。我们使用综合嵌套选择和相关潜在变量 (INCLV) 模型,揭示了美国受访者样本中自动化配送模式之间的替代效应。研究发现,对自动化配送模式的接受程度与运输价格和时间密切相关,这突显了精心规划和激励措施以最大化创新物流选项的试用性的重要性。年龄较大的人和对包裹处理有顾虑的人对自动化模式的偏好较低,而受教育程度较高和对技术有亲和力的人则更能接受。这些发现为希望在其最后一英里配送业务中引入自动化技术的物流公司和零售商提供了有价值的见解,强调需要根据客户偏好调整营销和沟通策略。此外,提供有关自动化技术进行适当包裹处理的信息可能会减轻所有客户群体对这些模式的担忧并提高其接受度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1a1/10613628/f48d2ea285c0/41598_2023_45371_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1a1/10613628/ca0b3819b1a2/41598_2023_45371_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1a1/10613628/33e369abf019/41598_2023_45371_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1a1/10613628/6cb594fd1ca7/41598_2023_45371_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1a1/10613628/53f6fb14b026/41598_2023_45371_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1a1/10613628/3c872361ac2d/41598_2023_45371_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1a1/10613628/f48d2ea285c0/41598_2023_45371_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1a1/10613628/ca0b3819b1a2/41598_2023_45371_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1a1/10613628/33e369abf019/41598_2023_45371_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1a1/10613628/6cb594fd1ca7/41598_2023_45371_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1a1/10613628/53f6fb14b026/41598_2023_45371_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1a1/10613628/3c872361ac2d/41598_2023_45371_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1a1/10613628/f48d2ea285c0/41598_2023_45371_Fig6_HTML.jpg

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本文引用的文献

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Shifting Mobility Behaviors in Unprecedented Times: A Multigroup MIMIC Model Investigating Intentions to Use On-Demand Ride Services During the COVID-19 Pandemic.前所未有的时期中出行行为的转变:一个多组MIMIC模型,研究在新冠疫情期间使用按需乘车服务的意愿
Transp Res Rec. 2023 Apr;2677(4):704-722. doi: 10.1177/03611981221147520. Epub 2023 Feb 8.
2
In-person, pick up or delivery? Evolving patterns of household spending behavior through the early reopening phase of the COVID-19 pandemic.亲自前往、自取还是送货上门?新冠疫情早期解封阶段家庭消费行为的演变模式。
Travel Behav Soc. 2023 Apr;31:295-311. doi: 10.1016/j.tbs.2023.01.003. Epub 2023 Jan 9.
3
For whom did telework not work during the Pandemic? understanding the factors impacting telework satisfaction in the US using a multiple indicator multiple cause (MIMIC) model.
在疫情期间,远程工作对哪些人不起作用?使用多指标多原因(MIMIC)模型理解影响美国远程工作满意度的因素。
Transp Res Part A Policy Pract. 2022 Jan;155:387-402. doi: 10.1016/j.tra.2021.11.025. Epub 2021 Dec 10.
4
Is the Covid-19 pandemic strong enough to change the online order delivery methods? Changes in the relationship between attitude and behavior towards order delivery by drone.新冠疫情是否强大到足以改变在线订单配送方式?无人机订单配送的态度与行为之间关系的变化。
Technol Forecast Soc Change. 2021 Aug;169:120829. doi: 10.1016/j.techfore.2021.120829. Epub 2021 Apr 28.
5
Adoption of delivery services in light of the COVID pandemic: Who and how long?鉴于新冠疫情采用递送服务:哪些人以及使用多久?
Transp Res Part A Policy Pract. 2021 Dec;154:270-286. doi: 10.1016/j.tra.2021.10.012. Epub 2021 Nov 2.
6
Autonomous delivery vehicles to fight the spread of Covid-19 - How do men and women differ in their acceptance?用于抗击新冠疫情传播的自动送货车辆——男性和女性在接受度上有何差异?
Transp Res Part A Policy Pract. 2021 Jun;148:183-198. doi: 10.1016/j.tra.2021.02.020. Epub 2021 Mar 24.