Integrating Diffusion of Innovations and Theory of Planned Behavior to Predict Intention to Adopt Electric Vehicles

IF 0.6 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Biometrics Pub Date : 2020-10-20 DOI:10.5539/ijbm.v15n11p88
Sun-Jung Moon
{"title":"Integrating Diffusion of Innovations and Theory of Planned Behavior to Predict Intention to Adopt Electric Vehicles","authors":"Sun-Jung Moon","doi":"10.5539/ijbm.v15n11p88","DOIUrl":null,"url":null,"abstract":"Electric vehicles (EVs) are recognized as effective solutions to the global air pollution problem, attracting much attention from businesses, governments, and consumers. Despite the heightened interest, EV penetration rates remain low. This study thus focuses on consumers’ evaluation of EV innovation to provide implications for promoting EV adoption by proposing a theoretical model that integrates the diffusion of innovations theory and the theory of planned behavior to examine the relationship between consumers’ perceived innovation characteristics and the adoption of EVs; the study findings indicate that the evaluation of consumers’ EV innovation has a significant impact on consumers’ attitudes toward and intention for EV adoption. Several important innovation characteristics promote practical implications for spreading EV acceptance.","PeriodicalId":54064,"journal":{"name":"International Journal of Biometrics","volume":"64 1","pages":"88"},"PeriodicalIF":0.6000,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Biometrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5539/ijbm.v15n11p88","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 4

Abstract

Electric vehicles (EVs) are recognized as effective solutions to the global air pollution problem, attracting much attention from businesses, governments, and consumers. Despite the heightened interest, EV penetration rates remain low. This study thus focuses on consumers’ evaluation of EV innovation to provide implications for promoting EV adoption by proposing a theoretical model that integrates the diffusion of innovations theory and the theory of planned behavior to examine the relationship between consumers’ perceived innovation characteristics and the adoption of EVs; the study findings indicate that the evaluation of consumers’ EV innovation has a significant impact on consumers’ attitudes toward and intention for EV adoption. Several important innovation characteristics promote practical implications for spreading EV acceptance.
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
整合创新扩散与计划行为理论预测电动汽车使用意向
电动汽车(ev)被认为是解决全球空气污染问题的有效方法,受到企业、政府和消费者的关注。尽管人们对电动汽车的兴趣高涨,但电动汽车的普及率仍然很低。因此,本研究以消费者对电动汽车创新的评价为研究对象,提出了一个整合创新扩散理论和计划行为理论的理论模型,考察消费者感知创新特征与电动汽车采用的关系,为促进电动汽车采用提供理论启示;研究结果表明,消费者对电动汽车创新的评价对消费者的电动汽车采用态度和意向有显著影响。几个重要的创新特征促进了电动汽车普及的实际意义。
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
International Journal of Biometrics
International Journal of Biometrics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
1.50
自引率
0.00%
发文量
46
期刊介绍: Biometrics and human biometric characteristics form the basis of research in biological measuring techniques for the purpose of people identification and recognition. IJBM addresses the fundamental areas in computer science that deal with biological measurements. It covers both the theoretical and practical aspects of human identification and verification.
期刊最新文献
A Secure Finger vein Recognition System using WS-Progressive GAN and C4 Classifier Exemplar-Based Facial Attribute Manipulation: A Review Arabic Offline writer identification on a new version of AHTID/MW database Recent trends and challenges in human computer interaction using automatic emotion recognition: a review Iris Recognition System Using Deep Learning Techniques
×
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