Adoption of Unmanned Aerial Vehicles in Middle- and Last-Mile Distribution: Multiple Case Studies on Influencing and Human Factors

Purpose – The objective of this research is to develop a framework for companies’ adoption of unmanned aerial vehicles (UAVs) in middle- and last-mile logistics through the lenses of sociotechnical systems theory (STS) and human factors (HF). Design/methodology/approach – We employ a two-step methodology. First, a systematic literature review (SLR) is performed to identify the influencing factors (i.e., enablers and barriers) of UAVs adoption according to the STS theory. Thus, a preliminary conceptual framework on UAVs adoption influencing factors in middle- and last-mile logistics is developed, through a process-oriented perspective of the logistics system. Then, the framework is validated and refined by a multiple case study through semi-structured interviews conducted in logistics companies that have implemented or are considering implementing UAVs in their middle- or last-mile logistics, taking a more human-centric point of view through the impact on HF. Expected findings and contributions – This two-stage approach provides a comprehensive framework of influencing factors as it combines the literature state of the art and practitioners’ insights. This approach provides theoretical (i.e., a comprehensive framework on UAVs adoption influencing factors merging two theoretical lenses) and managerial (i.e., knowledge required by logistics practitioners to evaluate UAV adoption adequately) contributions. Research limitations – Potential limitations of this research are represented by some challenges in the multiple case study design. One of the challenges is the lower level of detail over the cases analyzed due to time constraints. Therefore, a relatively small number of cases (reaching saturation) is selected to allow for a more profound and meaningful analysis of each case within a reasonable time. Another challenge is the difficulty in selecting similar cases that differ only in the variables under study. This aspect will be taken into consideration during the phase of case selection.