Consumer acceptance of the autonomous robot in last-mile delivery: a combined perspective of resource-matching, perceived risk and value theories

Following the expansion of e-commerce, the need for transportation services has increased. Moreover, the pandemic has decreased in-person interaction, necessitating contactless technologies. The autonomous delivery robot (ADR) is one such contactless technology used in last-mile delivery (LMD). Henc...

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Main Authors: Koh, Le Yi, Xia, Zhiyang, Yuen, Kum Fai
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2024
Subjects:
Online Access:https://hdl.handle.net/10356/175841
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1758412024-05-08T01:37:54Z Consumer acceptance of the autonomous robot in last-mile delivery: a combined perspective of resource-matching, perceived risk and value theories Koh, Le Yi Xia, Zhiyang Yuen, Kum Fai School of Civil and Environmental Engineering Engineering Consumer acceptance Last-mile delivery Following the expansion of e-commerce, the need for transportation services has increased. Moreover, the pandemic has decreased in-person interaction, necessitating contactless technologies. The autonomous delivery robot (ADR) is one such contactless technology used in last-mile delivery (LMD). Hence, consumers’ acceptance of ADRs in last-mile service must be studied to promote the use of this innovative technology. This study investigates the factors influencing customers’ acceptance of ADRs in LMD and aid in resource allocation to encourage acceptance. A combination of resource-matching theory, perceived value theory, and perceived risk theory was applied to develop the theoretical model. The central premise is that customers’ intentions are motivated by the characteristics of ADRs, such as compatibility, reliability, privacy security, and convenience, through the channels of enhanced perceived value and lower perceived risk. An online survey with 500 respondents was conducted in Singapore and structural model equation analysis was performed. The findings revealed that the effects of compatibility, convenience, privacy security, and reliability on consumer intention are fully mediated by perceived value and risk. This study enriches the literature on ADR acceptance in LMD by developing a holistic model and providing implications for promoting ADR adoption. National Research Foundation (NRF) This research/project is supported by the National Research Foundation, Singapore under its AI Singapore Programme (AISG Award No: AISG3-GV-2023-015). 2024-05-08T01:37:54Z 2024-05-08T01:37:54Z 2024 Journal Article Koh, L. Y., Xia, Z. & Yuen, K. F. (2024). Consumer acceptance of the autonomous robot in last-mile delivery: a combined perspective of resource-matching, perceived risk and value theories. Transportation Research Part A, 182, 104008-. https://dx.doi.org/10.1016/j.tra.2024.104008 0965-8564 https://hdl.handle.net/10356/175841 10.1016/j.tra.2024.104008 2-s2.0-85186666005 182 104008 en AISG3-GV-2023-015 Transportation Research Part A © 2024 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
Consumer acceptance
Last-mile delivery
spellingShingle Engineering
Consumer acceptance
Last-mile delivery
Koh, Le Yi
Xia, Zhiyang
Yuen, Kum Fai
Consumer acceptance of the autonomous robot in last-mile delivery: a combined perspective of resource-matching, perceived risk and value theories
description Following the expansion of e-commerce, the need for transportation services has increased. Moreover, the pandemic has decreased in-person interaction, necessitating contactless technologies. The autonomous delivery robot (ADR) is one such contactless technology used in last-mile delivery (LMD). Hence, consumers’ acceptance of ADRs in last-mile service must be studied to promote the use of this innovative technology. This study investigates the factors influencing customers’ acceptance of ADRs in LMD and aid in resource allocation to encourage acceptance. A combination of resource-matching theory, perceived value theory, and perceived risk theory was applied to develop the theoretical model. The central premise is that customers’ intentions are motivated by the characteristics of ADRs, such as compatibility, reliability, privacy security, and convenience, through the channels of enhanced perceived value and lower perceived risk. An online survey with 500 respondents was conducted in Singapore and structural model equation analysis was performed. The findings revealed that the effects of compatibility, convenience, privacy security, and reliability on consumer intention are fully mediated by perceived value and risk. This study enriches the literature on ADR acceptance in LMD by developing a holistic model and providing implications for promoting ADR adoption.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Koh, Le Yi
Xia, Zhiyang
Yuen, Kum Fai
format Article
author Koh, Le Yi
Xia, Zhiyang
Yuen, Kum Fai
author_sort Koh, Le Yi
title Consumer acceptance of the autonomous robot in last-mile delivery: a combined perspective of resource-matching, perceived risk and value theories
title_short Consumer acceptance of the autonomous robot in last-mile delivery: a combined perspective of resource-matching, perceived risk and value theories
title_full Consumer acceptance of the autonomous robot in last-mile delivery: a combined perspective of resource-matching, perceived risk and value theories
title_fullStr Consumer acceptance of the autonomous robot in last-mile delivery: a combined perspective of resource-matching, perceived risk and value theories
title_full_unstemmed Consumer acceptance of the autonomous robot in last-mile delivery: a combined perspective of resource-matching, perceived risk and value theories
title_sort consumer acceptance of the autonomous robot in last-mile delivery: a combined perspective of resource-matching, perceived risk and value theories
publishDate 2024
url https://hdl.handle.net/10356/175841
_version_ 1814047090844631040