{"title":"Understanding social media users' information avoidance intention: a C-A-C perspective","authors":"Tao Zhou, Yingying Xie","doi":"10.1108/ajim-10-2022-0471","DOIUrl":null,"url":null,"abstract":"PurposeBased on the C-A-C framework, this article examined users' information avoidance intention in social media platforms.Design/methodology/approachThe authors conducted data analysis using a mixed method of the SEM and fsQCA.FindingsThe results indicated that information overload, functional overload and social overload influence fatigue and dissatisfaction, both of which further determine users' information avoidance intention. The results of the fsQCA identified two paths that trigger users' information avoidance intention.Originality/valueExtant studies have examined the information avoidance in the contexts of healthcare, academics and e-commerce, but have seldom explored the mechanism underlying users' information avoidance in social media. To fill this gap, this article will empirically investigate users' information avoidance in social media platforms based on the C-A-C framework.","PeriodicalId":53152,"journal":{"name":"Aslib Journal of Information Management","volume":" ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aslib Journal of Information Management","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1108/ajim-10-2022-0471","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
PurposeBased on the C-A-C framework, this article examined users' information avoidance intention in social media platforms.Design/methodology/approachThe authors conducted data analysis using a mixed method of the SEM and fsQCA.FindingsThe results indicated that information overload, functional overload and social overload influence fatigue and dissatisfaction, both of which further determine users' information avoidance intention. The results of the fsQCA identified two paths that trigger users' information avoidance intention.Originality/valueExtant studies have examined the information avoidance in the contexts of healthcare, academics and e-commerce, but have seldom explored the mechanism underlying users' information avoidance in social media. To fill this gap, this article will empirically investigate users' information avoidance in social media platforms based on the C-A-C framework.
期刊介绍:
Aslib Journal of Information Management covers a broad range of issues in the field, including economic, behavioural, social, ethical, technological, international, business-related, political and management-orientated factors. Contributors are encouraged to spell out the practical implications of their work. Aslib Journal of Information Management Areas of interest include topics such as social media, data protection, search engines, information retrieval, digital libraries, information behaviour, intellectual property and copyright, information industry, digital repositories and information policy and governance.