A Study on the Acceptance of Urban Drone Delivery Services Using Text Mining: Utilizing YouTube Comments

In modern society, logistics systems need new innovations due to urban traffic congestion and environmental issues. Drones, or unmanned aerial vehicles, are gaining attention for improving urban logistics efficiency. However, drone delivery faces issues such as costs, regulations, and noise. This study analyzes consumer perceptions of drone delivery services using text mining technology. A total of 16,695 comments from 587 YouTube videos containing the keyword ‘drone delivery’ were analyzed through frequency analysis, topic modeling, and sentiment analysis. The results provided insights into consumer opinions, attitudes, concerns, and preferences regarding drone logistics. Major issues identified include potential accidents, noise, and high costs. Proposed solutions include enhancing safety, developing noise reduction technologies, reducing costs, and achieving social consensus. This study offers insights for improving drone delivery services and developing strategies that reflect consumer demands for future implementations.

Authors

Publication Details

Journal
Korean Production and Operations Management Society
Published
2024-08-31
DOI
https://doi.org/10.32956/kopoms.2024.35.3.337
Citations
2
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
2.60
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article

A Study on the Acceptance of Urban Drone Delivery Services Using Text Mining: Utilizing YouTube Comments

Donghyun Choi, Boyoung Yoon
2 citations
Korean Production and Operations Management Society
UAV Applications and Optimization
2.60
article

A Study on the Acceptance of Urban Drone Delivery Services Using Text Mining: Utilizing YouTube Comments

Donghyun Choi, Boyoung Yoon
article en
2 citations

Abstract

In modern society, logistics systems need new innovations due to urban traffic congestion and environmental issues. Drones, or unmanned aerial vehicles, are gaining attention for improving urban logistics efficiency. However, drone delivery faces issues such as costs, regulations, and noise. This study analyzes consumer perceptions of drone delivery services using text mining technology. A total of 16,695 comments from 587 YouTube videos containing the keyword ‘drone delivery’ were analyzed through frequency analysis, topic modeling, and sentiment analysis. The results provided insights into consumer opinions, attitudes, concerns, and preferences regarding drone logistics. Major issues identified include potential accidents, noise, and high costs. Proposed solutions include enhancing safety, developing noise reduction technologies, reducing costs, and achieving social consensus. This study offers insights for improving drone delivery services and developing strategies that reflect consumer demands for future implementations.

Korean Production and Operations Management SocietyVol. 35(3)
Openalex Percentile: Top 8%
UAV Applications and Optimization
2.60
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