<abstract xmlns="http://www.w3.org/1999/xhtml"><bold>Background:</bold> In today’s dynamic environment, electronic banking and electronic commerce have become an inevitable aspect of financial services, so the question of acceptance and use of this kind of technology arises.<bold>Objectives:</bold> The aim of this research is to determine whether the motivation for using the Internet banking in the city of Split, Croatia, can be explained by perceived ease of use and perceived usefulness as the main elements of the technology acceptance model.<bold>Methods/Approach:</bold> For the purposes of the research, a survey analysis was applied to the sample of 282 working residents of Split. The gender and age structure of the sample was harmonized with the population to make the results more credible. In order to test the research hypothesis, logistic regression models were used.<bold>Results:</bold> The results confirmed that both elements of the technology acceptance model significantly influence the acceptance of the Internet banking in the city of Split.<bold>Conclusions:</bold> It is concluded that demographic and economic characteristics and perception of individuals affect the acceptance and use of the Internet banking in the city of Split. The results showed that both elements of the technology acceptance model influence the acceptance of the Internet banking.</abstract>

Background: In today’s dynamic environment, electronic banking and electronic commerce have become an inevitable aspect of financial services, so the question of acceptance and use of this kind of technology arises.Objectives: The aim of this research is to determine whether the motivation for using the Internet banking in the city of Split, Croatia, can be explained by perceived ease of use and perceived usefulness as the main elements of the technology acceptance model.Methods/Approach: For the purposes of the research, a survey analysis was applied to the sample of 282 working residents of Split. The gender and age structure of the sample was harmonized with the population to make the results more credible. In order to test the research hypothesis, logistic regression models were used.Results: The results confirmed that both elements of the technology acceptance model significantly influence the acceptance of the Internet banking in the city of Split.Conclusions: It is concluded that demographic and economic characteristics and perception of individuals affect the acceptance and use of the Internet banking in the city of Split. The results showed that both elements of the technology acceptance model influence the acceptance of the Internet banking.

Technology Acceptance Model for the Internet Banking Acceptance in Split

Business Systems Research Journal

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Technology Acceptance Model for the Internet Banking Acceptance in Split"}

Background: In today’s dynamic environment, electronic banking and electronic commerce have become an inevitable aspect of financial services, so the question...

Technology Acceptance Model for the Internet Banking Acceptance in Split

Publié en ligne: 16 sept. 2019

Pages: 124 - 140

Reçu: 06 juin 2018

Accepté: 03 janv. 2019

DOI: https://doi.org/10.2478/bsrj-2019-022

Mots clés
internet banking, logistic regression, survey analysis, technology acceptance model (TAM)

© 2019 Marija Vuković et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Technology Acceptance Model for the Internet Banking Acceptance in Split

Publié en ligne: 16 sept. 2019

Pages: 124 - 140

Reçu: 06 juin 2018

Accepté: 03 janv. 2019

DOI: https://doi.org/10.2478/bsrj-2019-022

Mots clésinternet banking, logistic regression, survey analysis, technology acceptance model (TAM)

© 2019 Marija Vuković et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
internet banking, logistic regression, survey analysis, technology acceptance model (TAM)