Last-mile delivery by drone is expected to be a promising innovation for future urban logistics. However, in addition to adoption of services by customers, leveraging this delivery method will depend essentially on a positive public perception of such services in urban airspace.

    Objective

    This article provides novel and comprehensive insights into factors driving or impeding citizens' attitudes towards drone delivery.

    Methodology

    The article develops a structural equation model that  derives from a sequential exploratory mixed methods design. In the first step, factors affecting attitudes towards drone delivery were identified within the scope of five focus groups and converted into the development of a questionnaire. In the second step, a German population-representative survey was conducted through telephone interviews, which provided reliable data to test the model (n = 819).

    Results

    Expected risks (particularly stress due to traffic in lower airspace, noise, and visual disturbances), as well as expected benefits (particularly fast and time-flexible delivery), significantly affect attitudes towards drone-based delivery, while the individual level of technological openness (technophilia) does not have a significant association. Moreover, the model reveals that the expected risks of drone deliveries are stronger associated with public attitude than with expected benefits.

    Conclusions

    The provided framework suggests fashioning policies and drone delivery applications that focus on mitigating social, spatial, and visual risks while achieving maximum utility for customers.


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    Titel :

    Modelling public attitude towards drone delivery in Germany


    Weitere Titelangaben:

    Eur. Transp. Res. Rev.


    Beteiligte:
    Kellermann, Robin (Autor:in) / Biehle, Tobias (Autor:in) / Mostofi, Hamid (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    25.10.2023




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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