Emissions from transportation fuel vehicles are polluting the environment more than ever before. Currently, autonomous delivery vehicles (ADVs) are welcomed by logistics service providers and lots of consumers in general for their significant contribution in reducing environmental pollution and increasing delivery efficiency. However, there is a lack of in-depth research on consumers' willingness to adopt ADVs, despite the fact that ADVs are innovative delivery method in the field of last-mile delivery. The purpose of the study is to expand the existing knowledge of consumers' adoption behaviors by developing and testing the extended Value-Belief-Norm (VBN) theory in autonomous delivery literature. In particular, the study adds subjective norms and COVID-19 risk into the original VBN model as a theoretical framework to gain a comprehensive understanding of the consumer decision-making processes with respect to their intentions to use ADVs. Structural equation modeling is conducted using data from a web-based survey of 561 consumers through an online sample platform. The results of the study demonstrated that both subjective norms and COVID-19 risk are all related with consumers’ intention to use ADVs. The casual chain hypotheses of the extend VBN theory mentioned in our study are all supported. The results of the study make significant theoretical and managerial contributions to the field of last-mile delivery and the adoption behaviors of emerging technologies.

Autonomous delivery vehicles (ADVs) that provide contactless services have attracted much academic and practical attention in China in recent years. Despite this, there is a lack of in-depth research on what motivates customers to embrace ADVs. The study integrates the theory of planned behavior (TPB) and normative activation model (NAM) and explores how environmental factors, situational factors, and individual factors affect original TPB constructs and ultimately consumers’ intention to use ADVs. Structural equation modeling was performed on survey data of 561 Chinese consumers through an online sampling platform. The results show that among the factors affecting consumer intention, word-of-mouth recommendations have the greatest impact, followed by perceived enjoyment, COVID-19 risk, ascription of responsibility, subjective norm, attitude, and perceived behavioral control. The results not only make important theoretical contributions to the technology acceptance fields but also provide helpful references to logistics enterprises, ADVs technology providers, and policymakers.

The deployment of autonomous delivery vehicles (ADVs) is undergoing unprecedented expansion in China, fueled by escalating investments from online retail and logistics enterprises. Despite the multifacted benefits of ADVs, i.e. enhanced delivery efficiency, cost savings, and environmental sustainability, academic inquiry into consumes' intention to utilize such innovative technologies remains relatively scarce. To address this research gap, the study enhances and extends the Normative Activation Model (NAM) by integrating two critical constructs: perceived behavioral control (PBC) and perceived risk (PR). Using a structural equation model (SEM), we empirically analyze survey data collected from 354 online consumers via Wenjuanxing, a reputable online sampling platform. The results reveal that personal norms (PN) and PBC significantly affect consumers' intentions to adopt ADVs, while the impact of PR is statistically non-significant. Furthermore, ascription of responsibility (AR) partially mediates in the relationships between awareness of consequences (AC) and PN, and PN serves as a partial mediator in the relationships linking AC, AR, PBC and behavioral intention. These findings provide valuable theoretical and practical insights for logistics service providers - guiding the optimization of ADVs service design and risk mitigation strategies - and relevant government departments - informing the formulation of supportive policies for ADVs deployment and consumer protection regulations.

Autonomous delivery vehicles (ADVs) have attracted much attention since COVID-19. As an emerging last-mile delivery tool, the large-scale implementation of ADVs depends on consumers’ willingness to adopt them. However, until recently, research on user acceptance and adopting emerging technology has been relatively rare. The present study is the first that applies the stimulus-organism-response (S-O-R) model to investigate how stimulating factors (COVID-19 risk and human-computer interaction) affect consumers’ intention to use ADVs in last-mile delivery by triggering consumers’ inner states (delivery risk, price sensitivity, perceived enjoyment, trust in technology). Quantitative data based on university students in Zhejiang, China, was collected through an online survey platform (n = 298), and structural equation modeling was undertaken. The results reveal that COVID-19 risk and human-computer interaction can lead to adoption behaviors by triggering different inner states of consumers. Further, innovation is also considered to be one of the factors determining behavioral intention. The findings have profound theoretical and practical contributions to last-mile delivery and technology acceptance research.