Evidence map›Paper›PMID 37229167›Full record

ArticleHeliyon2023

Barriers to the sustainable adoption of autonomous vehicles in developing countries: A multi-criteria decision-making approach.

Alireza Shahedi, Iman Dadashpour, Mahdi Rezaei

Abstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Alireza ShahediDepartment of Mechanical, Energy, Management, and Transportation Engineering (DIME), University of Genova, Genova, Italy.
Iman DadashpourSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.
Mahdi RezaeiInstitute for Transport Studies, University of Leeds, 34-40 University Road, Leeds, LS2 9JT, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The acceptance of AI-based intelligent transportation systems requires addressing the existing barriers and the adoption of macro-decisions and policies by policymakers and governments. This study evaluates the potential barriers to the adoption of Autonomous Vehicles (AVs) in developing countries by considering the sustainability dimensions. The barriers are identified by conducting a comprehensive literature review and studying the academic experts' opinions in related industries. By identifying the main barriers to the sustainable adoption of AVs, a synthesized approach of the Rough Best-Worst Method (RBWM) and Interval-Rough Multi-Attributive Border Approximation Area Comparison (IR-MABAC) is utilized for weighting and evaluating each barrier in this context. According to the results of this study, the "inflation rate", "lack of internet connection quality", and "learning challenges and difficulties to use the AVs" are the top challenges and barriers to the AV adoption which need to be considered by policymakers. As the main contribution of this research, we provide efficient insights on a macro policy scale for decision-makers with respect to the main barriers to the implementation of AVs technology. From the AVs literature and to the best of our knowledge, this is the first study of its kind that considers the barriers to the AV technology implementation through the sustainability concept.

Indexed as

Adoption barriersAutonomous vehiclesIR-MABACRough BWMSustainability

Identifiers

PMID37229167
PMCPMC10205502

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.