Sustainable last-mile delivery: Understanding perceived benefits and risks of AI-automated delivery drones in France

This study investigates the adoption of delivery drones in last-mile logistics by extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) with constructs related to well-being, perceived technology risk, privacy concerns, and environmental concerns. Drawing on a 2x2x2 experimental design involving 3212 French participants, we examine how physical accidents, cyberattacks, product criticality, and environmental values shape consumers' performance expectancy, social influence, risk perception, and behavioral intentions. The findings show that environmental concerns enhance the positive impact of performance expectancy and social influence on well-being, while unexpectedly reducing the negative effect of privacy concerns. Product criticality significantly weakens the relationship between well-being and adoption intention. This paper contributes theoretically by integrating sustainability and perceived risk theory into UTAUT2, thereby advancing understanding of how consumers evaluate novel autonomous technologies under conditions of uncertainty and ecological awareness. • Environmental concerns moderate the impact of perceived risks on well-being. • Higher product criticality weakens the positive influence of well-being on adoption. • Cyberattacks and accidents heighten perceived risks, lowering drone adoption.

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Publication Details

Journal
Technological Forecasting and Social Change
Published
2026-02-03
DOI
https://doi.org/10.1016/j.techfore.2026.124576
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
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article

Sustainable last-mile delivery: Understanding perceived benefits and risks of AI-automated delivery drones in France

Vincent Favarin, Stéphane Salgado, Lars Meyer-Waarden, Julien Cloarec
Technological Forecasting and Social Change
UAV Applications and Optimization
article

Sustainable last-mile delivery: Understanding perceived benefits and risks of AI-automated delivery drones in France

Vincent Favarin, Stéphane Salgado, Lars Meyer-Waarden, Julien Cloarec
article en

Abstract

This study investigates the adoption of delivery drones in last-mile logistics by extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) with constructs related to well-being, perceived technology risk, privacy concerns, and environmental concerns. Drawing on a 2x2x2 experimental design involving 3212 French participants, we examine how physical accidents, cyberattacks, product criticality, and environmental values shape consumers' performance expectancy, social influence, risk perception, and behavioral intentions. The findings show that environmental concerns enhance the positive impact of performance expectancy and social influence on well-being, while unexpectedly reducing the negative effect of privacy concerns. Product criticality significantly weakens the relationship between well-being and adoption intention. This paper contributes theoretically by integrating sustainability and perceived risk theory into UTAUT2, thereby advancing understanding of how consumers evaluate novel autonomous technologies under conditions of uncertainty and ecological awareness. • Environmental concerns moderate the impact of perceived risks on well-being. • Higher product criticality weakens the positive influence of well-being on adoption. • Cyberattacks and accidents heighten perceived risks, lowering drone adoption.

Technological Forecasting and Social ChangeVol. 226
Centre National de la Recherche Scientifique (FR), Chulalongkorn University (TH), Université Toulouse-I-Capitole (FR), University of Clermont Auvergne (FR), Sigma Clermont (FR), Clermont Université (FR), Metropolitan University (BD), Université Jean Moulin Lyon III (FR)
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Openalex Percentile: Top 68%
UAV Applications and Optimization
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Sustainable last-mile delivery: Understanding perceived benefits and risks of AI-automated delivery drones in France — Vincent Favarin, Stéphane Salgado, et al. · Technological Forecasting and Social Change (2026) | TGRS Research Map | TGRS