Factors affecting electric vehicle acceptance, energy demand and CO2 emissions in Pakistan

Muhammad Huzaifa Butt, Jai Govind Singh
{"title":"Factors affecting electric vehicle acceptance, energy demand and CO2 emissions in Pakistan","authors":"Muhammad Huzaifa Butt,&nbsp;Jai Govind Singh","doi":"10.1016/j.geits.2023.100081","DOIUrl":null,"url":null,"abstract":"<div><p>This work aims to investigate the factors accelerating electric vehicle (EV) acceptance at the consumer end in Pakistan and analyzes the implications for policymakers for a fast-track EV transition. The study further investigates the high EV penetration scenario resulting from the technology acceptance model (TAM's 80% EV) and its impact on energy demand and CO<sub>2</sub> emissions. The study design used a quantitative analysis method with the survey as an instrument for data collection regarding EV acceptance. The model under investigation was adapted from the famous Technology-Acceptance Models (TAMs) and modified with other significant predictors evidenced in the literature. Correlation and stepwise regression were performed with a multicollinearity check for model hypothesis testing. Out of six predictors, only four factors were significant in accelerating the EV transition. Financial policies were found to be highly significant, followed by environmental concern, facilitating conditions and perceived ease of use. The research then used exponential smoothing forecasts for transport demand and developed an EV penetration scenario based on modified TAM results. The results highlight the significant increase in transport demand and the opportunity for Pakistan to limit passenger transport emissions to 36.6 ​MT instead of 61.6 ​MT by 2040.</p></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"2 3","pages":"Article 100081"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Green Energy and Intelligent Transportation","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2773153723000178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This work aims to investigate the factors accelerating electric vehicle (EV) acceptance at the consumer end in Pakistan and analyzes the implications for policymakers for a fast-track EV transition. The study further investigates the high EV penetration scenario resulting from the technology acceptance model (TAM's 80% EV) and its impact on energy demand and CO2 emissions. The study design used a quantitative analysis method with the survey as an instrument for data collection regarding EV acceptance. The model under investigation was adapted from the famous Technology-Acceptance Models (TAMs) and modified with other significant predictors evidenced in the literature. Correlation and stepwise regression were performed with a multicollinearity check for model hypothesis testing. Out of six predictors, only four factors were significant in accelerating the EV transition. Financial policies were found to be highly significant, followed by environmental concern, facilitating conditions and perceived ease of use. The research then used exponential smoothing forecasts for transport demand and developed an EV penetration scenario based on modified TAM results. The results highlight the significant increase in transport demand and the opportunity for Pakistan to limit passenger transport emissions to 36.6 ​MT instead of 61.6 ​MT by 2040.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
影响巴基斯坦电动汽车接受度、能源需求和二氧化碳排放的因素
这项工作旨在调查加速巴基斯坦消费者接受电动汽车的因素,并分析电动汽车快速转型对政策制定者的影响。该研究进一步调查了技术接受模型(TAM的80%电动汽车)产生的高电动汽车渗透率情景及其对能源需求和二氧化碳排放的影响。研究设计采用了定量分析方法,将调查作为收集电动汽车验收数据的工具。研究中的模型改编自著名的技术接受模型(TAMs),并用文献中证明的其他重要预测因素进行了修改。相关和逐步回归与多重共线性检验进行模型假设检验。在六个预测因素中,只有四个因素对加速电动汽车转型具有重要意义。金融政策非常重要,其次是环境问题、便利条件和易用性。然后,该研究对交通需求进行了指数平滑预测,并根据修正后的TAM结果开发了电动汽车渗透率情景。研究结果突显了运输需求的显著增长,以及巴基斯坦将客运排放量限制在36.6的机会​MT而不是61.6​MT。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
6.40
自引率
0.00%
发文量
0
期刊最新文献
Unveiling the power of data in bidirectional charging: A qualitative stakeholder approach exploring the potential and challenges of V2G A comprehensive overview of the alignment between platoon control approaches and clustering strategies Co-estimation of state-of-charge and state-of-temperature for large-format lithium-ion batteries based on a novel electrothermal model Towards vehicle electrification: A mathematical prediction of battery electric vehicle ownership growth, the case of Turkey A review on reinforcement learning-based highway autonomous vehicle control
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1