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Barriers in adoption of FinTech by street vendors and hawkers in India using interpretive structural modeling

    Priti Bakhshi Affiliation
    ; Reena Agrawal   Affiliation
    ; Suhan Mendon   Affiliation
    ; Daniel Frank Affiliation
    ; Cristi Spulbar Affiliation
    ; Ramona Birau Affiliation
    ; Robert Dorin Filip Affiliation

Abstract

The adoption of financial technology (fintech) has the potential to make banking and financial services more accessible and convenient for all, but there are significant barriers preventing the adoption of fintech by street vendors and hawkers in India. This study aims to identify and analyse the barriers to fintech adoption using interpretive structural modelling (ISM). The research identified nine key barriers to fintech adoption, including perceived risk, lack of trust, lack of perceived benefit, social influence, lack of awareness, cash culture, lack of literacy, perceived ease of use, and lack of financial literacy. The study utilizes ISM to develop a hierarchy of these barriers and their interrelationships. The findings suggest that to promote the adoption of fintech, it is essential to build trust and awareness of fintech services through education and out-reach programs. This research provides a comprehensive understanding of the barriers to fintech adoption among street vendors and hawkers in India and offers insights into how these barriers can be overcomed. The study contributes to the development of strategies that can help promote the adoption of fintech among marginalized populations and advance financial inclusion in India.

Keyword : fintech, e-commerce, online banking, digital payments, street vendors, hawkers, Interpretive Structural Modeling

How to Cite
Bakhshi, P., Agrawal, R., Mendon, S., Frank, D., Spulbar, C., Birau, R., & Filip, R. D. (2024). Barriers in adoption of FinTech by street vendors and hawkers in India using interpretive structural modeling. Business: Theory and Practice, 25(1), 231–240. https://doi.org/10.3846/btp.2024.19208
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Apr 25, 2024
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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