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Acceptance of Autonomous Delivery Vehicles for Last Mile Delivery in Germany: Extension of the Technology Acceptance Model to an Autonomous Delivery Vehicles Acceptance Model
Jönköping University, Jönköping International Business School.
Jönköping University, Jönköping International Business School.
2020 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The steady growth of the e-commerce sector and the associated logisticalchallenges in the last mile, as well as the equally increasing expectations ofconsumers for parcel delivery call for innovation in the last mile. Drones androbots seem to be a reasonable alternative delivery option to meet thesechallenges. Before these technologies are used as means of transport in the lastmile, it is necessary to investigate whether it will be accepted by potentialconsumers.

This thesis aims to identify the factors influencing conumser’ acceptance ofautonomous delivery vehicles for delivery in Germany. To determine thebehaviour of potential consumers, the Technology Acceptance Model wasextended by several factors from different acceptance models that seemedrelevant from a consumer perspective.

In order to investigate consumer acceptance, a quantitative approach wasconducted using questionnaires. The propsed hypotheses were tested usingstructural equation modelling. Further, a multi-group analysis was conducted toindentify sociodemographic differences.

The results show that price sensitivity, perceived usefulness, hedonic motivation,and perceived ease of use influence the behavioural intention of consumers inGermany to use autonomous delivery vehicles, whereas privacy security andfacilitating conditions do not have a significant effect. Further no significantdifferences were found in the multigroup analysis.

Place, publisher, year, edition, pages
2020. , p. 91
Keywords [en]
Last Mile, Autonomous Delivery Vehicles, Delivery Drones, Delivery Robots, Consumer Acceptance, Technology Acceptance Model
National Category
Business Administration
Identifiers
URN: urn:nbn:se:hj:diva-48879ISRN: JU-IHH-FÖA-2-20201143OAI: oai:DiVA.org:hj-48879DiVA, id: diva2:1435733
Subject / course
JIBS, Business Administration
Supervisors
Available from: 2020-06-24 Created: 2020-06-05 Last updated: 2025-10-13Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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