Exploring Perceived Usefulness of Using Autonomous Trucks in Logistics

Historically, the U.S. Gulf Coast region carries more burdens than other communities, including generated air pollution, delays and crashes, and frequent floods. Thus, there is a strong need to improve the efficiency of freight transportation and reduce environmental impacts by using emerging technologies. This study aims to explore the perceived usefulness of using Autonomous Trucks in logistics in Florida, Louisiana, Mississippi, and Texas in the U.S. Gulf Coast region. Data were collected using an online survey from 72 members of the Trucking Associations in the U.S. states of Florida, Louisiana, Mississippi, and Texas. The participants' perceptions were captured using 14 pre‐determined perceived usefulness on a five‐point level of agreement. A Likert scale was developed based on the Technology Acceptance Model (TAM). Data were analyzed using the IBM SPSS Statistics Software—Version 29. The results showed mixed perceived usefulness. Items related to efficiency were mostly supported, and items related to effectiveness were mostly neutral. Items related to overall satisfaction were mostly not supported. In addition, some participant groups reported higher levels of agreement with the examined items than others. For example, those who worked in a business with 500 employees or more, had much knowledge of autonomous trucks, worked in sales, had two or fewer years of work experience, and worked in a business with international market coverage. In addition, participants who worked in businesses transporting agriculture, food, and livestock cargo reported higher levels of agreement with the examined perceived usefulness than those who worked in companies transporting construction, fuel, machinery, waste, and mixed freight. This study contributes to the academic literature by adding more insights about the perceived usefulness of autonomous trucks in logistics. The results would benefit academics, researchers, logisticians, supply chain managers, autonomous truck manufacturers, policymakers, and other interested stakeholders. They can also help develop future research projects in a similar domain.