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Testing a structural model of young driver willingness to uptake Smartphone Driver Support Systems

Overview of attention for article published in Accident Analysis & Prevention, August 2015
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

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7 X users

Citations

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32 Dimensions

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131 Mendeley
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Title
Testing a structural model of young driver willingness to uptake Smartphone Driver Support Systems
Published in
Accident Analysis & Prevention, August 2015
DOI 10.1016/j.aap.2015.07.023
Pubmed ID
Authors

Aoife A. Kervick, Michael J. Hogan, Denis O’Hora, Kiran M. Sarma

Abstract

There is growing interest in the potential value of using phone applications that can monitor driver behaviour (Smartphone Driver Support Systems, 'SDSSs') in mitigating risky driving by young people. However, their value in this regard will only be realised if young people are willing to use this technology. This paper reports the findings of a study in which a novel structural model of willingness to use SDSSs was tested. Grounded in the driver monitoring and Technology Acceptance (TA) research literature, the model incorporates the perceived risks and gains associated with potential SDSS usage and additional social cognitive factors, including perceived usability and social influences. A total of 333 smartphone users, aged 18-24, with full Irish driving licenses completed an online questionnaire examining willingness or Behavioural Intention (BI) to uptake a SDSS. Following exploratory and confirmatory factor analyses, structural equation modelling indicated that perceived gains and social influence factors had significant direct effects on BI. Perceived risks and social influence also had significant indirect effects on BI, as mediated by perceived gains. Overall, this model accounted for 72.5% of the variance in willingness to uptake SDSSs. Multi-group structural models highlighted invariance of effects across gender, high and low risk drivers, and those likely or unlikely to adopt novel phone app technologies. These findings have implications for our understanding of the willingness of young drivers to adopt and use SDSSs, and highlight potential factors that could be targeted in behavioural change interventions seeking to improve usage rates.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
India 1 <1%
United States 1 <1%
Switzerland 1 <1%
Unknown 127 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 16%
Researcher 20 15%
Student > Ph. D. Student 17 13%
Student > Bachelor 12 9%
Student > Doctoral Student 11 8%
Other 24 18%
Unknown 26 20%
Readers by discipline Count As %
Engineering 17 13%
Social Sciences 14 11%
Computer Science 13 10%
Business, Management and Accounting 11 8%
Psychology 11 8%
Other 31 24%
Unknown 34 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 May 2019.
All research outputs
#6,963,279
of 25,373,627 outputs
Outputs from Accident Analysis & Prevention
#1,321
of 4,178 outputs
Outputs of similar age
#74,535
of 276,161 outputs
Outputs of similar age from Accident Analysis & Prevention
#9
of 58 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 4,178 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has gotten more attention than average, scoring higher than 68% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 276,161 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.