Article(id=1242141986505957507, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242141284979257419, articleNumber=null, orderNo=null, doi=10.3981/j.issn.1000-7857.2024.05.00509, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1715529600000, receivedDateStr=2024-05-13, revisedDate=1731254400000, revisedDateStr=2024-11-11, acceptedDate=null, acceptedDateStr=null, onlineDate=1736092800000, onlineDateStr=2025-01-06, pubDate=1734019200000, pubDateStr=2024-12-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1736092800000, onlineIssueDateStr=2025-01-06, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774079327462, creator=sys-migrate, updateTime=1774079327462, updator=sys-migrate, issue=Issue{id=1242141284979257419, tenantId=1146029695717560320, journalId=1146031591421210625, year='2024', volume='42', issue='23', pageStart='1', pageEnd='144', issueExtLink='null', onlineDate='null', pubDate='1734019200000', pubDateStr='2024-12-13', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=null, issueType=-1, specialIssue=null, createTime=1774079160206, creator='sys-migrate', updateTime=1774079160206, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=85, endPage=97, ext={EN=ArticleExt(id=1242141988485669007, articleId=1242141986505957507, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Adoption under perceived risks: Analysis of face recognition payment technology acceptance, columnId=1242141617201685065, journalTitle=Science & Technology Review, columnName=Exclusive: Cross-domain artificial intelligence technology, runingTitle=null, highlight=null, articleAbstract=The application of artificial intelligence, represented by face recognition payment, has improved efficiency and optimized user experience, but it has also introduced various risks. In order to regulate its development, it is essential to investigate the factors that influence the adoption of face recognition payment. Current research on the impact of perceived risk facets on face recognition payment remains limited. This study, based on the UTAUT model, analyses the key factors influencing the intention to use face recognition payment (performance expectancy, effort expectancy, social influence, and facilitating conditions) and further examines the influence of five perceived risk facets (time risk, privacy risk, legal risk, financial risk, and health risk) on performance expectancy and effort expectancy. A structural equation analysis of 412 valid survey responses shows that the four factors in the UTAUT model have a significant positive impact on the behavioral intention to use face recognition payment. Privacy risk and financial risk are the facets of users' greatest concern, and both have a significant negative impact on performance expectancy and effort expectancy. This study identifies the specific mechanisms through which different risks affect the adoption of face recognition payment, providing reference and empirical evidence for its risk management and governance., authors=LI Wenwen^1,2, HAN Wei³, CHEN An², authorsList=LI Wenwen, HAN Wei, CHEN An, authorCompany=1. University of Chinese Academy of Sciences, Beijing 100049, China;
2. Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China;
3. Development Planning Research Institute, China Electronies Technology Group Corporation (CETC), Beijing 100041, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242141987864912009, articleId=1242141986505957507, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=感知风险下的采用：人脸识别支付接受度分析, columnId=1242141615175836213, journalTitle=科技导报, columnName=专题：跨领域人工智能技术, runingTitle=null, highlight=null, articleAbstract=基于技术接受与使用统一理论（UTAUT）模型，分析了影响人脸识别支付使用意愿的关键因素（绩效期望、努力期望、社会影响和便利条件），考察了5种感知风险维度（时间风险、隐私风险、法律风险、财务风险和健康风险）对绩效期望和努力期望的影响。通过对412份有效问卷数据进行结构方程分析，结果表明，UTAUT模型中的4个影响因素对使用人脸识别支付的使用意愿有显著正向影响。隐私风险和财务风险是用户最为关注的风险维度，对绩效期望和努力期望均产生了显著的负向影响。揭示了不同风险在人脸识别支付采纳中的具体影响机制。, authors=李玟玟^1,2, 韩玮³, 陈安², authorsList=李玟玟, 韩玮, 陈安, authorCompany=1. 中国科学院大学, 北京 100049;
2. 中国科学院科技战略咨询研究院, 北京 100190;
3. 中电科发展规划研究院, 北京 100041, correspAuthors=null, authorNote=李玟玟，博士研究生，研究方向为应急管理，电子信箱：stephanie0220@foxmail.com；陈安（通信作者），研究员，研究方向为应急管理，电子信箱：change1970@163.com, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=vPrP/9fTl4J4legkeu9dkw==, pdfFileSize=1334848, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=国家社会科学基金重点项目（19AZD019）)}, authors=null, keywords=[Keyword(id=1242141987445481605, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242141986505957507, language=CN, orderNo=1, keyword=人脸识别支付技术), Keyword(id=1242141987529367686, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242141986505957507, language=CN, orderNo=1, keyword=UTAUT), Keyword(id=1242141987609059463, 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