Trust dimensions and operational performance in VR-based drone tasks in construction

Purpose The successful deployment of drones in construction increasingly depends on human operators' willingness to work collaboratively with robotic systems. However, limited understanding of how trust develops during human–drone interaction and its relationship to performance outcomes hampers the design of effective human–drone interaction frameworks and adoption strategies. Design/methodology/approach We conducted a within-subjects experiment with 41 participants who completed collaborative drone flight operations in a virtual reality environment. Trust was measured pre- and post-interaction across four dimensions: perceived risk, benevolence, competence and reciprocity. Objective performance was quantified via task completion time and collision count. Findings One-sample t-tests revealed significant increases in trust for benevolence (d = 0.35), competence (d = 0.44) and reciprocity (d = 0.43), with overall trust improving substantially (d = 0.48, p = 0.004). Larger increases in trust were associated with operational performance, inversely correlating with both completion time (r = −0.60, p < 0.001) and collisions (r = −0.71, p < 0.001). Among trust dimensions, perceived reciprocity was the most associated with objective performance in this task, showing significant correlations with reduced collisions (r = −0.32, p = 0.041). Originality/value Collaborative interaction fosters measurable trust gains in humans toward drones, with reciprocity, the perceived sense of mutual responsiveness, showing a significant association with performance in the VR-based inspection task. These findings offer preliminary insights that may help inform the design of collaborative drone systems that consider mutual responsiveness, the development of operator training programs focused on reciprocal interaction patterns and organizational strategies to accelerate autonomous technology adoption in construction.

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Publication Details

Journal
Engineering Construction & Architectural Management
Published
2026-09-11
DOI
https://doi.org/10.1108/ecam-02-2026-0211
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
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article

Trust dimensions and operational performance in VR-based drone tasks in construction

Chukwuma Nnaji, Rahat Hussain, Umme Sabiha Onnesha
Engineering Construction & Architectural Management
Human-Automation Interaction and Safety
article

Trust dimensions and operational performance in VR-based drone tasks in construction

Chukwuma Nnaji, Rahat Hussain, Umme Sabiha Onnesha
article en

Abstract

Purpose The successful deployment of drones in construction increasingly depends on human operators' willingness to work collaboratively with robotic systems. However, limited understanding of how trust develops during human–drone interaction and its relationship to performance outcomes hampers the design of effective human–drone interaction frameworks and adoption strategies. Design/methodology/approach We conducted a within-subjects experiment with 41 participants who completed collaborative drone flight operations in a virtual reality environment. Trust was measured pre- and post-interaction across four dimensions: perceived risk, benevolence, competence and reciprocity. Objective performance was quantified via task completion time and collision count. Findings One-sample t-tests revealed significant increases in trust for benevolence (d = 0.35), competence (d = 0.44) and reciprocity (d = 0.43), with overall trust improving substantially (d = 0.48, p = 0.004). Larger increases in trust were associated with operational performance, inversely correlating with both completion time (r = −0.60, p < 0.001) and collisions (r = −0.71, p < 0.001). Among trust dimensions, perceived reciprocity was the most associated with objective performance in this task, showing significant correlations with reduced collisions (r = −0.32, p = 0.041). Originality/value Collaborative interaction fosters measurable trust gains in humans toward drones, with reciprocity, the perceived sense of mutual responsiveness, showing a significant association with performance in the VR-based inspection task. These findings offer preliminary insights that may help inform the design of collaborative drone systems that consider mutual responsiveness, the development of operator training programs focused on reciprocal interaction patterns and organizational strategies to accelerate autonomous technology adoption in construction.

Engineering Construction & Architectural ManagementVol. 33(15)
Texas A&M University (US)
Openalex Percentile: Top 7%
Human-Automation Interaction and Safety
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