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  4. A framework for preparing cities for the successful implementation of shared autonomous vehicles: An integrative literature review
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A framework for preparing cities for the successful implementation of shared autonomous vehicles: An integrative literature review

Journal
Sustainable Cities and Society
ISSN
2210-6707
Type
journal article
Date Issued
2025-07
Author(s)
Marvin Greifenstein  
;
La Delfa, Alessandro
;
Han, Zheng
DOI
10.1016/j.scs.2025.106515
Abstract
In response to sustainable mobility paradigms and the transition from private ownership to shared utilization, shared autonomous vehicles (SAVs) may play a pivotal role in future mobility systems. However, SAVs are still emerging, and there is a lack of cohesive frameworks and criteria to evaluate cities’ readiness for SAVs. Therefore, this study proposes a new conceptual framework to evaluate city readiness for SAVs, ensuring their integration and bridging an existing research gap. By conducting an integrative literature review, existing research in the field of SAVs is assessed and synthesised in a way that allows new perspectives to emerge. The 34 included publications were inductively coded using Atlas.ti software. As a result, the proposed framework addresses city readiness in five core categories: infrastructure, security & privacy, policy, regulation & legality, innovation, collaboration & economics, and customer/citizen engagement. Infrastructure and policy, regulation & legality were identified as the most crucial of these categories.
Language
English
Keywords
Shared autonomous vehicles (SAVs)
City readiness
Integrative literature review
Conceptual framework
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Elsevier BV
Volume
130
Start page
Art. 106515
URL
https://alexandria.unisg.ch/handle/20.500.14171/143362
Subject(s)

business studies

Division(s)

IMO - Institute for M...

File(s)
Thumbnail Image

open.access

Name

1-s2.0-S2210670725003907-main.pdf

Type

Main Article

Size

1.35 MB

Format

Adobe PDF

Checksum (MD5)

d5c6f2606bd4d19d86f17ffa9f6fbb3e

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