Evidence map›Paper›PMID 36624834›Full record

ArticleCase studies on transport policy2023

Investigating influencing factors for ICT adoption that changes travel behavior in response to the COVID-19 outbreak in Indonesia.

Muhamad Rizki, Tri Basuki Joewono, Muhammad Zudhy Irawan, Prawira Fajarindra Belgiawan, Faza Fawzan Bastarianto, Dwi Prasetyanto

Abstract read
In one paragraph

Article in Case studies on transport policy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Muhamad RizkiDepartment of Civil Engineering, Institut Teknologi Nasional Bandung, Bandung, Indonesia.
Tri Basuki JoewonoDepartment of Civil Engineering, Faculty of Engineering, Parahyangan Catholic University, Bandung, Indonesia.
Muhammad Zudhy IrawanDepartment of Civil and Environmental Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia.
Prawira Fajarindra BelgiawanSchool of Business and Management, Institut Teknologi Bandung, Ganesha No. 10, Bandung, Indonesia.
Faza Fawzan BastariantoDepartment of Civil and Environmental Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia.
Dwi PrasetyantoDepartment of Civil Engineering, Institut Teknologi Nasional Bandung, Bandung, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mobility and out-of-home activities restrictions from the COVID-19 pandemic have forced people to maximize their in-home activities. Considering the increase in Information and Communication Technology (ICT) adoption during the outbreak, this paper tries to shed light on the factors that influence changing travel behavior. For these purposes, the study uses data collected through an online questionnaire during the outbreak in Indonesia, which was then analyzed using cluster and discriminant analyses. The study found that online adaptation during the outbreak was affected by income level, whereby high-income individuals are associated with high online adaptation. Residential location also influences ICT adaptation during the outbreak. Cities with higher access to the internet and ICT platforms as well as higher income per capita tend to have higher ICT adoption. People with more experience with online platforms or services also record higher online in-home activity adoption during the outbreak. Furthermore, while the lower-income group tends to reduce their travel, the higher-income group still continues to travel to fulfil their household needs during the outbreak, such as in-store shopping. Since the lower-income group and less accessible areas tend to have difficulty in accessing ICT as a substitute for travel, this study recommends that the government and ICT stakeholders ensure equal access to ICT to support physical distancing and to limit mobility in order to flatten the peak of the pandemic.

Indexed as

COVID-19Developing countryICT adaptationTravel behavior

Identifiers

PMID36624834
PMCPMC9812828

What OpenQuestion holds

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Registered trials

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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.