Analysis of selected technology acceptance model constructs and their impact on user behavior


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Nowadays, when the Internet is a regular part of people’s life in competitive conditions, it is essential to emphasize user feelings about the products, especially in the context of web pages. The study aims to clarify the significance of selected Technology Acceptance Model elements concerning user behavior in the web area. The study applied an exploratory method using an anonymous questionnaire in electronic form (Likert scale). This study’s respondents were website users, visitors, or internet users within the EU. Adequacy of the research sample was measured using Cronbach’s alpha and Kaiser-Meyer-Olkin (226 respondents). This paper proposed factors that impact user behavior. The quality of the website content factor contains two other variables: the quality of information (QI-Q5) and its availability (AI-A3). The design quality factor is composed of four elements: appearance (AP1-AP5), website findability (F1-F4), website navigation (N1-N3), and website access and usability (AU1-AU4). In addition, the paper selected the perceived usefulness factor (USEF1), the factor of perceived ease of use (EOU1-EOU3), and the attitude to use the website (ATT1). This study calculated the values of the Pearson correlation coefficients and used the lower triangle method to obtain the resulting coefficient values. The analysis results show that the simplicity of use and page orientation does not affect the actual use of the website. The study’s outcome is a model that identifies the impact of individual factors on user behavior in the context of user experience.

This paper was supported by the Slovak Research and Development Agency under Contract no. APVV-21-0188. This paper was also supported by VEGA 1/0488/22.

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    • Figure 1. Research model
    • Figure 2. Information quality factor
    • Figure 3. Availability of information factor
    • Figure 4. Perceived simplicity factor
    • Figure 5. Final model of user experience
    • Table 1. Findability factor of the website
    • Table 2. Navigation factor of the website
    • Table 3. Access and usability factor of the website
    • Table 4. Perceived usefulness factor
    • Table 5. Attitude factor to use the selected website
    • Table 6. Website content quality factor
    • Table 7. Statistical evaluation
    • Conceptualization
      Igor Fedorko, Beata Gavurova
    • Data curation
      Igor Fedorko
    • Investigation
      Igor Fedorko, Beata Gavurova
    • Methodology
      Igor Fedorko, Radovan Bačik
    • Software
      Igor Fedorko
    • Writing – original draft
      Igor Fedorko, Radovan Bačik, Beata Gavurova
    • Writing – review & editing
      Igor Fedorko, Beata Gavurova
    • Funding acquisition
      Radovan Bačik
    • Resources
      Radovan Bačik, Beata Gavurova
    • Formal Analysis
      Beata Gavurova
    • Visualization
      Beata Gavurova