Modelling factors influencing customer's intention to accept drone food delivery (DFD) services among youth in Malaysia

• Main Author: NOOR ISLAM JASIM
• Format: text::Thesis
• Language: English
• Published: 2023

Drone technologies have recently received a great deal of attention due to their high mobility, low cost, and flexible deployment. It is anticipated that drones will be part of our daily life, just like smartphones. The wide deployment of drones in different domains such as healthcare, agriculture, traffic monitoring, firefighting, national defense, rescue activity, and delivery services such as food and retail. Drones are expected to have a significant contribution to food delivery services by saving time, cost, environment, and people's life by reducing traffic congestion, wages, carbon emission, and accidents, respectively. Recently, big corporations, such as Amazon and DHL, have deployed drones as an alternative to traditional delivery methods. Amid the Covid-19 pandemic, delivery drones could be used to ensure social and physical distancing. While the attempts to deploy drones in the foodservice industry focus substantially on the technical aspects, research studies from the behavioral perspectives are still in their infancy. When new technology-based services are introduced, it is crucial to examine and understand consumers' perceptions by identifying a set of actions that influence acceptance and fulfilling their target. Therefore, service providers of drone food delivery (DFD) services need to identify significant factors that influence potential consumers to use drone delivery. Although few existing models are significant, these models lack a basic theory that addresses factors that influence consumers' intention and behavior. To overcome this limitation and propose a model, relevant research studies from the domain of drone delivery services and other emerging technology such as IoT, Autonomous Vehicles, and Mobile Banking are identified, reviewed, analyzed, and ten potential factors are subsequently extracted. This study's data were collected from 209 participants, who regularly order food online for delivery, and analyzed using SPSS. Descriptive statistics, descriptive, reliability. Pearson correlation, regression analysis, r-squared, and standardized beta coefficient analyses are carried out to present the study's findings. In terms of the demographic data, the results show that 88.6% of the participants have experienced online food delivery services regularly, while 40.7% of them have heard about DFD services. The functional results show that there is a significant relationship between behavioral intention and the user behavior of DFD. The results also show that social influence has the most substantial impact on behavioral intention, followed by trust, personal innovativeness, facilitating conditions, usefulness, ease of use, hedonic motivation, and price sensitivity. In contrast, privacy risk and performance risk are not significant factors in accepting DFD. Although the participants in this study are yet to experience drone technology in the foodservice domain, the identified factors explain around 32.9% of the variation in the use behavior of DFD services. In the early stage of adoption, it is highly recommended for stakeholders to conduct marketing campaigns through media channels such as television, newspapers, and the internet to bring awareness of this technology.