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Total interpretive structural modeling of UAV adoption in middle- and last-mile logistics: a sociotechnical systems perspective
Journal article   Peer reviewed

Total interpretive structural modeling of UAV adoption in middle- and last-mile logistics: a sociotechnical systems perspective

Federico Barbieri, Claudia Colicchia, Eric H. Grosse, Marco Lovera and Alessandro Creazza
Technological forecasting & social change, Vol.233, pp.1-22
2026
Scopus ID: 2-s2.0-105049192085
Web of Science ID: WOS:001871778300001

Abstract

Influencing factors Logistics distribution processes Sociotechnical systems theory Systematic literature review Total interpretive structural modeling Unmanned aerial vehicles
Unmanned aerial vehicles (UAVs) have the potential to enhance logistics processes by reducing environmental impacts, improving economic efficiency, and increasing service levels. However, successfully integrating UAVs requires understanding not only their technological capabilities but also the sociotechnical interactions that shape their adoption. Existing research provides a limited overview of UAVs' influencing factors (IFs), primarily emphasizing technological characteristics or consumer acceptance while overlooking their broader interdependencies. Drawing on Sociotechnical Systems (STS) theory, this study investigates UAV adoption as a complex system integrating social and technical components, with a specific focus on middle- and last-mile logistics. A systematic literature review, complemented by an integrative review of grey literature, identified 13 IFs, which were subsequently structured using Total Interpretive Structural Modeling (TISM) and MICMAC analysis and further interpreted through expert interviews. The findings reveal that technological maturity and environmental impact constitute the primary system drivers, influencing regulatory, infrastructural, organizational, and stakeholder-related factors through hierarchical sociotechnical relationships. Furthermore, the results show that social factors primarily affect adoption through indirect mechanisms by shaping organizational readiness, stakeholder collaboration, and the institutional conditions under which technological capabilities translate into successful implementation. By operationalizing STS theory into an explanatory framework, this study advances understanding of why UAV adoption follows different trajectories across logistics contexts. The findings also provide logistics practitioners and policymakers with a structured basis for prioritizing technological investments, infrastructure development, stakeholder engagement, and regulatory coordination to support successful UAV integration.
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