Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/326125 
Year of Publication: 
2024
Citation: 
[Journal:] Cogent Business & Management [ISSN:] 2331-1975 [Volume:] 11 [Issue:] 1 [Article No.:] 2322778 [Year:] 2024 [Pages:] 1-9
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
This study aims to answer the impact of digital financial literacy (DFL) and the demographic factors on digital financial inclusion (DFI). This model employed the independent variables that consist of digital financial literacy and demographic factors including gender, age, occupation, marital status, income. By applying purposive sampling, this study collected the data from 160 households who have minimum one banks’ accounts. To answer the research hypotheses, this study analyzed the data using binary logistic regression that categorized sample into DFI or otherwise. Based on the model fit test, the findings showed that DFL and demographic factors affect DFI. The effect of gender and marital status showed an insignificant effect on DFI. Conversely, DFL and other demographic factors including age, income, occupation significantly explain DFI in Indonesian household. The model can predict 84.4% respondents in a correct classification as DFI or otherwise.This study highlights the impact of digital financial literacy (DFL) and demographic factors on digital financial inclusion (DFI) among Indonesian households. It contributes in filling the research gap which is conducted using entrepreneurial households. DFI has become a crucial factor to accelerate the economic growth especially for society who are financially excluded. Therefore, DFI is needed to support entrepreneurial household business activities. These findings underscore the importance of tailored financial literacy initiatives and inclusive policies to promote broader access to digital financial services, driving socioeconomic development in Indonesia and beyond.
Subjects: 
Digital financial inclusion
digital financial literacy
demographic factors
binary logistic regression
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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