The moderating impact of gender differences on the relationship between barriers and behavioral intentions to use mobile fintech services

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Drawing on an extended Innovation Resistance Theory, this study examines how various barriers – namely, usage, value, risk, tradition, image, information, and privacy – affect the behavioral intention to use mobile fintech services among bottom of the pyramid consumers. Moreover, it investigates the moderating role of gender difference on these relationships using Multi-Group Analysis. Primary data were collected through a self-administered online survey and gaining 200 responses from low-income users in urban city in Indonesia who already have smartphones but possess minimal experience or knowledge of mobile fintech services usage. Data analysis was conducted using Structural Equation Modeling-Partial Least Squares, with assistance from SmartPLS 4.0 software. The findings indicated that five barriers (usage, value, risk, tradition, and privacy) had a significant negative impact on the intention to use fintech services, while the other two (image and tradition) showed no significant effect. Additionally, it is revealed that gender did not affect the impact of usage and risk barriers, whereas differences were identified for the other barriers. These insights highlight the importance of addressing gender-specific needs in designing mobile fintech solutions for low-income consumers in emerging economies.

Acknowledgment
We would like to acknowledge and thank the Balai Pembiayaan Pendidikan Tinggi (Center of Financing Higher Education) – BPPT, The Ministry of Education, Culture, Research, and Technology, Republic of Indonesia, and the Lembaga Pengelola Dana Pendidikan (Indonesia Endowment Fund for Education) – LPDP, Ministry of Finance Indonesia, for providing funding for this research publication.

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    • Figure 1. Research model
    • Table 1. Operational definitions of innovation barriers
    • Table 2. Assessment of the outer model
    • Table 3. Discriminant validity assessment using Heterotrait-monotrait ratio (HTMT)
    • Table 4. The results of structural model analysis
    • Table 5. Multi-Group Analysis test results
    • Conceptualization
      Muhammad Ashoer, Andi Faisal Bahari, Masdar Mas’ud
    • Investigation
      Muhammad Ashoer
    • Methodology
      Muhammad Ashoer
    • Supervision
      Muhammad Ashoer, Masdar Mas’ud
    • Writing – original draft
      Muhammad Ashoer, Masdar Mas’ud
    • Writing – review & editing
      Muhammad Ashoer, Andi Faisal Bahari, Amar Sani, Moch Ridho Ghazali Rahman
    • Project administration
      Andi Faisal Bahari, Moch Ridho Ghazali Rahman
    • Resources
      Andi Faisal Bahari
    • Formal Analysis
      Amar Sani
    • Software
      Amar Sani, Moch Ridho Ghazali Rahman
    • Validation
      Amar Sani
    • Funding acquisition
      Masdar Mas’ud
    • Data curation
      Moch Ridho Ghazali Rahman
    • Visualization
      Moch Ridho Ghazali Rahman