Cracking the code of electric vehicle adoption: Driving a future through the value-belief-norm theory and theory of planned behavior in xanh sm's last mile delivery in Vietnam

Abstract

In recent years, the increasing adoption of e-commerce in consumer purchasing behaviors has profoundly impacted urban freight movements, which has drawn scholarly attention toward the sustainability of last-mile delivery, which refers to the final stage in the delivery process where products are transported from distribution hubs to ultimate consumers. The purpose of this study is to determine the factors that influence consumers' decisions to use the last mile delivery method by using Xanh SM electric vehicles. Using the VBN theory framework, this study examines how the three value orientations - altruistic, biospheric, and egoistic - shape awareness of consequences, the assignment of responsibility, and the development of pro-environmental personal norms. Moreover, in this particular study, we propose a psychological process model based on the Value-Belief-Norm (VBN) theory and the Theory of Planned Behavior (TPB) to examine the adoption of innovative technologies like electric vehicles (EVs), with a more specific focus on their application in last-mile delivery solutions such as Xanh SM. Data were collected through a cross-sectional survey of 317 young generation participants, particularly Millennials and Gen Z, and analyzed using structural equation modeling (SEM). This study highlights key psychological and normative factors influencing consumer decisions to use Xanh SM's electric vehicles for last-mile delivery, emphasizing the role of values, beliefs, and pro-environmental norms. The findings suggest that promoting EVs' environmental benefits and integrating sustainability into corporate strategies, marketing campaigns, and incentive programs can enhance consumer adoption. However, the study's limitations include a small sample size and a focus on Xanh SM, necessitating future research with a larger, more diverse sample and qualitative methods to explore additional adoption factors.