Driving Financial Inclusion through Mobile Financial Services Adoption Intention in Bangladesh: Integrating Perceived Trust and Risk with UTAUT
DOI:
https://doi.org/10.67120/jkkniubr.v2.i1.a16Keywords:
Mobile financial services, Financial inclusion, Adoption intention, UTAUT, Perceived trust, Perceived risk, Structural equation modelingAbstract
Research purpose: Although research on mobile financial services (MFS) adoption intention is plentiful, how in an emerging economy like Bangladesh a holistic perspective of MFS adoption intention by combining users and non-users is infrequent, specifically when perceived trust and risk are integrated with UTAUT model. Henceforth, this research efforts to expose the factors affecting behavioral intention (BI) for Bangladesh by including both MFS users and non-users to apprehend the complete market spectrum.
Methodology: This deductive, quantitative study used a cross-sectional design and an integrated UTAUT framework. Data from diverse respondents representing both MFS users and non-users, collected via multistage mixed sampling technique and structured questionnaire survey, have been analyzed using Smart PLS 4.1.0.9 and SPSS version 26.0 software.
Findings: The results presented that behavioral intention is significantly impacted by performance expectancy, effort expectancy, social influence, trust and facilitating conditions. On the contrary, perceived risk is found to be statistically non-significant. The overall predictive relevance of the study is positive.
Originality/value: By incorporating trust and risk as fundamental antecedents, this study goes beyond simply testing UTAUT. By doing this, it develops a stronger socio-technical model that takes into consideration the high risks and trust issue involved in managing finances in a digital setting. A combined sample is used in this study. This offers a distinctive full-spectrum perspective of the state of financial inclusion and a more general result. To approve the model’s out-of-sample predictive relevance, this study employs PLS predict, confirming that findings are robust for practical application in the MFS sector.
Research implications: This study provides a unified model for closing the financial inclusion gap by demonstrating the determinants for adoption intention using a combined sample.
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