Abstract
Delivery robots can contribute to efficient transportation and handover of goods in urban areas. To realize the full potential of this technology, users need to accept these novel systems. One possibility to increase acceptance is adapting the design of robots. The design of delivery robots, which are meant to function as tools but also interact closely with humans during transportation and delivery, presents both challenges and opportunities for increasing user acceptance. Specifically, anthropomorphic framing, or ascribing human-like characteristics to the robot, may influence acceptance. In addition, the type of goods being transported by the robot may also affect user acceptance. We used a video-based online experiment, to investigate how anthropomorphic framing and product value affect the individual and general acceptance and intention to use robots for transporting goods. In addition, we operationalized the perceived value of the robot’s service through the willingness to pay for this delivery service. The data of 189 participants were retrieved in our between-subjects online study. The study revealed no differences in general acceptance, intention to use, and willingness to pay for the service robot. However, anthropomorphic framing and the prize of the transported goods mattered for the individual acceptance of the delivery robots. In particular, anthropomorphically framed robots and robots transporting inexpensive goods were accepted significantly more. As the services of transporting inexpensive products were accepted more, the successful implementation and actual usage could lead to an extension of the acceptance of more expensive goods transportation. This result could be the basis for a gradual market entry strategy that starts with low-cost product transportation like food delivery.
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Roesler, E., Pickl, J., Siebert, F.W. (2023). Investigating the Impact of Anthropomorphic Framing and Product Value on User Acceptance of Delivery Robots. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. HCII 2023. Lecture Notes in Computer Science, vol 14048. Springer, Cham. https://doi.org/10.1007/978-3-031-35678-0_23
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DOI: https://doi.org/10.1007/978-3-031-35678-0_23
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