Modelling factors influencing customer's intention to accept drone food delivery (DFD) services among youth in Malaysia
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, agricul...
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| Format: | text::Thesis |
| Language: | English |
| Published: |
2023
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| Summary: | 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. |
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