{"title":"SMS Advertising in India: Is TAM a Robust Model for Explaining Intention?","authors":"Hemant Bamoriya, Rajendra Singh","doi":"10.15388/OMEE.2012.3.1.14277","DOIUrl":null,"url":null,"abstract":"This study examined mobile users’ intentions to receive SMS advertising in India using Technology Acceptance Model (TAM) as a research framework. 242 respondents completed a structured questionnaire, measuring their responses to the TAM’s five constructs. Using Structural Equation Modeling (SEM) both measurement model and structural model testing was done to analyze the data. The findings suggested that specified TAM model contributed to 81.8% of variance in the intention to receive SMS advertising and was a valid model in explaining the intention to receive SMS advertising. The study indicated that perceived utility was a much better predictor of attitude towards SMS advertising than perceived ease of use and perceived trust. The study suggested that in order to increase acceptance of SMS advertising marketers should focus more on increasing utility of SMS ads, so that users would develop positive attitudes towards SMS advertising.","PeriodicalId":236490,"journal":{"name":"Emerging Markets Economics: Firm Behavior & Microeconomic Issues eJournal","volume":"28 9","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Emerging Markets Economics: Firm Behavior & Microeconomic Issues eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15388/OMEE.2012.3.1.14277","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
This study examined mobile users’ intentions to receive SMS advertising in India using Technology Acceptance Model (TAM) as a research framework. 242 respondents completed a structured questionnaire, measuring their responses to the TAM’s five constructs. Using Structural Equation Modeling (SEM) both measurement model and structural model testing was done to analyze the data. The findings suggested that specified TAM model contributed to 81.8% of variance in the intention to receive SMS advertising and was a valid model in explaining the intention to receive SMS advertising. The study indicated that perceived utility was a much better predictor of attitude towards SMS advertising than perceived ease of use and perceived trust. The study suggested that in order to increase acceptance of SMS advertising marketers should focus more on increasing utility of SMS ads, so that users would develop positive attitudes towards SMS advertising.