The use of advanced driver assistance systems (ADAS) to improve transport and road safety has been growing rapidly. For any significant reduction in crashes and fatalities, drivers must use these systems. Thus, the need to understand factors that will impact their adoption and acceptance. This study aims to test the efficacy of the Unified Theory of Acceptance and Use of Technology (UTAUT) model in the investigation of acceptance of an advisory Intelligent Speed Assistance (ISA) by Nigerian drivers. This involves the examining of factors which might influence acceptance of an Advisory ISA system among a group of commercial Nigerian drivers. A test survey involving 20 participants was carried out before and after the use of a smart phone advisory speed limit system. The results indicate that the predictive power of the model was only significant after participants had used the system (Time 2), explaining 36% of the variance in Intention to use, with the construct of Performance Expectancy serving as the strongest predictor of intention. Overall, the findings suggest high acceptance levels from the drivers, as participants demonstrated strong beliefs and positive Intention to Use the system. The findings also show that participants’ acceptability levels reduced after using the ISA system. However, the results suggest that they could be other factors responsible for predicting intention to use the ISA system and thus should be further investigated. Based on these findings, the paper provides several implications for the implementation of ADAS and suggestions for future research.
| Published in | Engineering and Applied Sciences (Volume 7, Issue 6) |
| DOI | 10.11648/j.eas.20220706.15 |
| Page(s) | 115-122 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2022. Published by Science Publishing Group |
Intelligent Speed Assistance, Acceptance, UTAUT Model, Speeding
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APA Style
Anderson Aja Etika. (2022). Predicting the Acceptance of an Advisory Intelligent Speed Assistance System: A Case of Nigerian Drivers. Engineering and Applied Sciences, 7(6), 115-122. https://doi.org/10.11648/j.eas.20220706.15
ACS Style
Anderson Aja Etika. Predicting the Acceptance of an Advisory Intelligent Speed Assistance System: A Case of Nigerian Drivers. Eng. Appl. Sci. 2022, 7(6), 115-122. doi: 10.11648/j.eas.20220706.15
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Download@article{10.11648/j.eas.20220706.15,
author = {Anderson Aja Etika},
title = {Predicting the Acceptance of an Advisory Intelligent Speed Assistance System: A Case of Nigerian Drivers},
journal = {Engineering and Applied Sciences},
volume = {7},
number = {6},
pages = {115-122},
doi = {10.11648/j.eas.20220706.15},
url = {https://doi.org/10.11648/j.eas.20220706.15},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.eas.20220706.15},
abstract = {The use of advanced driver assistance systems (ADAS) to improve transport and road safety has been growing rapidly. For any significant reduction in crashes and fatalities, drivers must use these systems. Thus, the need to understand factors that will impact their adoption and acceptance. This study aims to test the efficacy of the Unified Theory of Acceptance and Use of Technology (UTAUT) model in the investigation of acceptance of an advisory Intelligent Speed Assistance (ISA) by Nigerian drivers. This involves the examining of factors which might influence acceptance of an Advisory ISA system among a group of commercial Nigerian drivers. A test survey involving 20 participants was carried out before and after the use of a smart phone advisory speed limit system. The results indicate that the predictive power of the model was only significant after participants had used the system (Time 2), explaining 36% of the variance in Intention to use, with the construct of Performance Expectancy serving as the strongest predictor of intention. Overall, the findings suggest high acceptance levels from the drivers, as participants demonstrated strong beliefs and positive Intention to Use the system. The findings also show that participants’ acceptability levels reduced after using the ISA system. However, the results suggest that they could be other factors responsible for predicting intention to use the ISA system and thus should be further investigated. Based on these findings, the paper provides several implications for the implementation of ADAS and suggestions for future research.},
year = {2022}
}
TY - JOUR T1 - Predicting the Acceptance of an Advisory Intelligent Speed Assistance System: A Case of Nigerian Drivers AU - Anderson Aja Etika Y1 - 2022/12/23 PY - 2022 N1 - https://doi.org/10.11648/j.eas.20220706.15 DO - 10.11648/j.eas.20220706.15 T2 - Engineering and Applied Sciences JF - Engineering and Applied Sciences JO - Engineering and Applied Sciences SP - 115 EP - 122 PB - Science Publishing Group SN - 2575-1468 UR - https://doi.org/10.11648/j.eas.20220706.15 AB - The use of advanced driver assistance systems (ADAS) to improve transport and road safety has been growing rapidly. For any significant reduction in crashes and fatalities, drivers must use these systems. Thus, the need to understand factors that will impact their adoption and acceptance. This study aims to test the efficacy of the Unified Theory of Acceptance and Use of Technology (UTAUT) model in the investigation of acceptance of an advisory Intelligent Speed Assistance (ISA) by Nigerian drivers. This involves the examining of factors which might influence acceptance of an Advisory ISA system among a group of commercial Nigerian drivers. A test survey involving 20 participants was carried out before and after the use of a smart phone advisory speed limit system. The results indicate that the predictive power of the model was only significant after participants had used the system (Time 2), explaining 36% of the variance in Intention to use, with the construct of Performance Expectancy serving as the strongest predictor of intention. Overall, the findings suggest high acceptance levels from the drivers, as participants demonstrated strong beliefs and positive Intention to Use the system. The findings also show that participants’ acceptability levels reduced after using the ISA system. However, the results suggest that they could be other factors responsible for predicting intention to use the ISA system and thus should be further investigated. Based on these findings, the paper provides several implications for the implementation of ADAS and suggestions for future research. VL - 7 IS - 6 ER -
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