Differences in Generation Y male and female customers’ perceived mobile banking trust, information, and system quality

  • 6 Views
  • 0 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Trust is key to mobile banking adoption, shaping customer confidence in the service. Trusting behaviors and expectations vary between genders and across generational cohorts, influenced by factors like system and information quality. As such, the purpose of this study was to determine whether South African Generation Y male and female banking customers differ in their mobile banking trust, system, and information quality. In accordance with a descriptive research design, self-administered surveys were voluntarily distributed to 334 South African mobile banking participants. Using structural equation modeling, the study found that, among the male participants, the system quality of mobile banking predicts their mobile banking trust (β = 0.72, p < .001) and perceived information quality of the system (β = 0.94, p < .001). However, their mobile banking trust had an insignificant influence on their perceived information quality (β = –0.04, p > .001). For female Generation Y banking customers, mobile banking system quality was a significant predictor of both trust (β = 0.53, p < .001) and information quality (β = 0.69, p < .001). In addition, the path between trust and information quality was statistically significant (β = 0.17, p < .05). Determining the role of trust and its relationship between information and system quality of mobile banking among males and females is essential for understanding customer behavior, enhancing user experience, mitigating perceived risk, and guiding strategic decision-making in the mobile banking industry.

view full abstract hide full abstract
    • Figure 1. Structural paths
    • Table 1. Sample description
    • Table 2. Descriptive statistics and independent samples t-test
    • Table 3. One-sample statistics
    • Table 4. Correlation and collinearity statistics
    • Table 5. Measurement model statistics
    • Table 6. Path analysis
    • Table 7. Mediation analysis
    • Conceptualization
      Marko van Deventer
    • Data curation
      Marko van Deventer
    • Formal Analysis
      Marko van Deventer
    • Methodology
      Marko van Deventer
    • Project administration
      Marko van Deventer
    • Software
      Marko van Deventer
    • Validation
      Marko van Deventer
    • Writing – original draft
      Marko van Deventer
    • Writing – review & editing
      Marko van Deventer