Flying to the customer: a meta-analysis of consumer adoption of drone delivery
Year: 2026
Type: review
Study designs: Systematic Review, Meta-Analysis
Abstract: Purpose The growing popularity of electronic commerce has led to the emergence of drone delivery services (DDS), which enhance efficiency while reducing costs, delivery time and carbon footprint. Numerous studies have examined factors influencing the intention to adopt DDS, with varied results. This study aims to reconcile these inconsistent findings through meta- analysis and by investigating the moderating role of culture. Design/methodology/approach The study conducts a meta-analysis of 58 studies to identify and examine antecedents of DDS adoption intention. Findings The findings suggest that all these antecedents, except performance risk, positively influence DDS adoption intention, while privacy risk negatively influences it. Furthermore, the moderator analysis offers several valuable insights, highlighting how the cultural dimensions of uncertainty-avoidance and masculinity affect various relationships within DDS adoption intention. Research limitations/implications The study examined only two moderators; hence, future researchers should focus on additional firm-level, cultural and contextual moderators. Some constructs were studied in only a limited number of primary studies, so their relationships could not be examined through moderator tests. Practical implications Firms should highlight the functional and experiential benefits of DDS, focus on designing simple and engaging DDS platforms and provide educational content to strengthen trust and enhance DDS adoption. They should also clearly communicate environmental benefits and address privacy and safety concerns, while tailoring their marketing strategies to specific cultural contexts. Originality/value To the best of the authors’ knowledge, this study is the first meta-analysis to examine the factors influencing DDS adoption intention.
Authors: Nikshit Gautam, Sumedha Chauhan, Poonam Kumar
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7221987386