Modeling the Prediction of Continued Usage of COVID-19 mhealth App in India

R. Mittal, A. Mittal, Arun Aggarwal
{"title":"Modeling the Prediction of Continued Usage of COVID-19 mhealth App in India","authors":"R. Mittal, A. Mittal, Arun Aggarwal","doi":"10.1109/CCGE50943.2021.9776421","DOIUrl":null,"url":null,"abstract":"Indian m-health app Aarogya Setu has made a significant contribution in terms of contactability tracing and disease management during the initial days of the COVID-19 pandemic, with its contact tracking approach to infectious individuals and its health tips for eliminating new coronaviruses. The goal of this study is to forecast whether or not Indian consumers will continue to use this app. According to previous studies, the context or setting has a substantial impact on the customer's perceived value. The current study's unique setting is to investigate the parameters impacting Indians' ongoing use of the mobile mHealth app AarogyaSetu. An extended technology adoption model (TAM) has been proposed and tested to achieve this wide goal, with the addition of three additional constructs: social influence, health consciousness, and trust in the app developer.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGE50943.2021.9776421","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Indian m-health app Aarogya Setu has made a significant contribution in terms of contactability tracing and disease management during the initial days of the COVID-19 pandemic, with its contact tracking approach to infectious individuals and its health tips for eliminating new coronaviruses. The goal of this study is to forecast whether or not Indian consumers will continue to use this app. According to previous studies, the context or setting has a substantial impact on the customer's perceived value. The current study's unique setting is to investigate the parameters impacting Indians' ongoing use of the mobile mHealth app AarogyaSetu. An extended technology adoption model (TAM) has been proposed and tested to achieve this wide goal, with the addition of three additional constructs: social influence, health consciousness, and trust in the app developer.
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
对印度COVID-19移动医疗应用程序持续使用情况的建模预测
在COVID-19大流行的最初几天,印度移动健康应用程序Aarogya Setu通过对感染者的接触者追踪方法和消除新型冠状病毒的健康提示,在接触性追踪和疾病管理方面做出了重大贡献。本研究的目的是预测印度消费者是否会继续使用这款应用程序。根据之前的研究,环境或设置对客户的感知价值有重大影响。当前研究的独特设置是调查影响印度人持续使用移动移动健康应用程序AarogyaSetu的参数。为了实现这一广泛的目标,已经提出并测试了一个扩展的技术采用模型(TAM),并增加了三个额外的结构:社会影响、健康意识和对应用程序开发人员的信任。
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
自引率
0.00%
发文量
0
期刊最新文献
Stock Market Analysis using Time Series Data Analytics Techniques [Agendas] Irrigation to Smart Irrigation and Tube Well Users A Feature Cum Intensity Based SSIM Optimised Hybrid Image Registration Technique Flood Level Control and Management Using Instrumentation and 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