{"title":"电子货币:接受和使用技术的统一理论(utaut)模型","authors":"Irma Christiana, Hastina Febriaty, Linzzy Pratami Putri","doi":"10.32502/mti.v9i1.7989","DOIUrl":null,"url":null,"abstract":"Purpose – This research aims to identify any variables that can influence e-money user behavior mediated by behavioral intentions using the UTAUT model Design/methodology –. This research uses a quantitative-descriptive approach. Sampling used a purposive sampling method to achieve a sample size based on the Slovin formula. Data was collected by distributing a questionnaire in the form of a Google Form. The data analysis technique uses the Partial Least Squares-Structural Equation Model (PLSSEM) with the SmartPLS3 application. Findings - The results of hypothesis testing show that performance expectations do not influence behavioral intentions. Effort expectancy, social influence, and facilitating conditions influence the intention to use e-money. Facilitating conditions influence user behavior. Behavioral intentions are able to mediate the influence of performance expectations, business expectations, and social influences, as well as facilitate conditions on e-money user behavior.","PeriodicalId":509822,"journal":{"name":"MOTIVASI","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PENERIMAAN E-MONEY: PENERAPAN UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY (UTAUT) MODEL\",\"authors\":\"Irma Christiana, Hastina Febriaty, Linzzy Pratami Putri\",\"doi\":\"10.32502/mti.v9i1.7989\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose – This research aims to identify any variables that can influence e-money user behavior mediated by behavioral intentions using the UTAUT model Design/methodology –. This research uses a quantitative-descriptive approach. Sampling used a purposive sampling method to achieve a sample size based on the Slovin formula. Data was collected by distributing a questionnaire in the form of a Google Form. The data analysis technique uses the Partial Least Squares-Structural Equation Model (PLSSEM) with the SmartPLS3 application. Findings - The results of hypothesis testing show that performance expectations do not influence behavioral intentions. Effort expectancy, social influence, and facilitating conditions influence the intention to use e-money. Facilitating conditions influence user behavior. Behavioral intentions are able to mediate the influence of performance expectations, business expectations, and social influences, as well as facilitate conditions on e-money user behavior.\",\"PeriodicalId\":509822,\"journal\":{\"name\":\"MOTIVASI\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MOTIVASI\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32502/mti.v9i1.7989\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MOTIVASI","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32502/mti.v9i1.7989","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PENERIMAAN E-MONEY: PENERAPAN UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY (UTAUT) MODEL
Purpose – This research aims to identify any variables that can influence e-money user behavior mediated by behavioral intentions using the UTAUT model Design/methodology –. This research uses a quantitative-descriptive approach. Sampling used a purposive sampling method to achieve a sample size based on the Slovin formula. Data was collected by distributing a questionnaire in the form of a Google Form. The data analysis technique uses the Partial Least Squares-Structural Equation Model (PLSSEM) with the SmartPLS3 application. Findings - The results of hypothesis testing show that performance expectations do not influence behavioral intentions. Effort expectancy, social influence, and facilitating conditions influence the intention to use e-money. Facilitating conditions influence user behavior. Behavioral intentions are able to mediate the influence of performance expectations, business expectations, and social influences, as well as facilitate conditions on e-money user behavior.