Evidence map›Paper›PMID 39767357›Full record

ArticleBehavioral sciences (Basel, Switzerland)2024

Factors Influencing Consumer Willingness to Use AI-Driven Autonomous Taxis.

Tingyu Liu, Yizhou Zhang, Mengze Zhang, Min Chen, Shangchun Yu

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Tingyu LiuDepartment of Economics, Sejong University, Seoul 05006, Republic of Korea.ORCID 0009-0003-8125-8344
Yizhou ZhangDepartment of Global Business, Anyang University, Anyang-si 14028, Republic of Korea.ORCID 0000-0001-9286-3126
Mengze ZhangDepartment of Economics, Sejong University, Seoul 05006, Republic of Korea.ORCID 0000-0003-1370-0391
Min ChenDepartment of Economics, Sejong University, Seoul 05006, Republic of Korea.ORCID 0009-0002-5946-2229
Shangchun YuDepartment of Economics, Sejong University, Seoul 05006, Republic of Korea.ORCID 0009-0003-9151-8904

Funding

the Higher Education Teaching Reform and Research Project of Jiangsu Province, China 230JSJG787
6 · The paper itself

Abstract

The advancement of autonomous driving technology, particularly Tesla's launch of its new Robotaxi, marks a transformation in transportation. Understanding the theoretical mechanisms that drive consumers' intention to use autonomous taxis is essential. This study develops a structural equation model (SEM), extending the applicability of the TAM and TPB model, and incorporates external factors like attitudes, subjective norms, traffic efficiency, and perceived cost-benefit into the model to analyze their impact on consumers' perceived characteristics (perceived usefulness and perceived ease of use). A survey of 427 valid responses revealed that attitudes, subjective norms, and perceived cost-benefit all have significant positive impacts on perceived usefulness and ease of use, which, in turn, are the primary drivers of consumers' intention to use. Additionally, perceived risk significantly weakens the positive effects of perceived usefulness and ease of use on the intention to use, underscoring its critical moderating role in the technology acceptance process. This paper suggests strategies to enhance consumer acceptance, including strengthening user perception through marketing and public experience activities, optimizing technology to improve user experience, reinforcing safety and privacy measures to reduce perceived risk, and highlighting the insurance mechanism, convenience, and economic benefits of autonomous taxis in marketing.

Indexed as

autonomous taxisintention to useperceived riskTechnology Acceptance Model (TAM)Theory of Planned Behavior (TPB)

Identifiers

PMID39767357
PMCPMC11673982

What OpenQuestion holds

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LicenceCC BY
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.