The FinTech adoption in rural areas of Pakistan: an application of SEM and ANN approach

Purpose The global emphasis on sustainability is driving organizations to embrace financial technology (FinTech) solutions as a means of enhancing their sustainable performance. Despite the focus on leveraging FinTech for financial inclusion, there is a notable scarcity of research on its role in aiding the unbanked and underserved populations in developing countries. To bridge the research gap, this study proposes a framework exploring key determinants of FinTech adoption namely Perceived Traceability, Accessibility, Security, Financial Literacy, Seamless Transaction, Convenience, Facilitating Conditions and Privacy Risk and their interrelations. Design/methodology/approach For the empirical validation of our model, we adopted a dual approach combining structural equation modeling (SEM) and artificial neural networks (ANN), thereby enhancing the robustness of our framework. Given the SEM–ANN approach’s requirement for a larger sample size, we gathered data from 489 respondents in areas of Pakistan. Following data screening, 22 cases were discarded, leaving 467 for analysis. Initial examination and hypothesis testing utilized Smart-PLS 4.0 and SPSS-23. To deepen the validation and evaluate the significance of the factors identified, an ANN approach was subsequently applied as a robustness check. Findings The results conclusively demonstrated that Perceived Traceability, Accessibility, Security, Financial Literacy, Seamless Transaction, Convenience, Facilitating Conditions and Perceived Privacy Risk are significant drivers of FinTech adoption in rural areas. The study also revealed that Perceived Privacy Risk acts as a moderating factor in the dynamics between Perceived Traceability, Security and FinTech Adoption, although this moderating effect was not observed in the relationship between Perceived Accessibility and FinTech Adoption. Additionally, the ANN analysis results matched the PLS-SEM outcomes, reinforcing the significance of the identified factors. The study found variations in factor impact across methodologies, suggesting future research directions. Originality/value This study offers essential guidance for decision-makers in rural FinTech adoption, focusing on improving accessibility, security, convenience and financial literacy. It enhances understanding of FinTech’s key drivers in rural contexts, contributing to the field’s literature. Additionally, it provides actionable recommendations for policymakers and organizations to advance financial inclusivity in these regions.

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Institutions

Publication Details

Journal
Asia-Pacific Journal of Business Administration
Published
2025-04-21
DOI
https://doi.org/10.1108/apjba-02-2024-0111
Citations
3
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
6.85
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article

The FinTech adoption in rural areas of Pakistan: an application of SEM and ANN approach

Imdadullah Hidayat-ur-Rehman, Mohammad Nurul Alam, Abul Bashar Bhuiyan, Norhayah Zulkifli
3 citations
Asia-Pacific Journal of Business Administration
FinTech, Crowdfunding, Digital Finance
6.85
article

The FinTech adoption in rural areas of Pakistan: an application of SEM and ANN approach

Imdadullah Hidayat-ur-Rehman, Mohammad Nurul Alam, Abul Bashar Bhuiyan, Norhayah Zulkifli
article en
3 citations

Abstract

Purpose The global emphasis on sustainability is driving organizations to embrace financial technology (FinTech) solutions as a means of enhancing their sustainable performance. Despite the focus on leveraging FinTech for financial inclusion, there is a notable scarcity of research on its role in aiding the unbanked and underserved populations in developing countries. To bridge the research gap, this study proposes a framework exploring key determinants of FinTech adoption namely Perceived Traceability, Accessibility, Security, Financial Literacy, Seamless Transaction, Convenience, Facilitating Conditions and Privacy Risk and their interrelations. Design/methodology/approach For the empirical validation of our model, we adopted a dual approach combining structural equation modeling (SEM) and artificial neural networks (ANN), thereby enhancing the robustness of our framework. Given the SEM–ANN approach’s requirement for a larger sample size, we gathered data from 489 respondents in areas of Pakistan. Following data screening, 22 cases were discarded, leaving 467 for analysis. Initial examination and hypothesis testing utilized Smart-PLS 4.0 and SPSS-23. To deepen the validation and evaluate the significance of the factors identified, an ANN approach was subsequently applied as a robustness check. Findings The results conclusively demonstrated that Perceived Traceability, Accessibility, Security, Financial Literacy, Seamless Transaction, Convenience, Facilitating Conditions and Perceived Privacy Risk are significant drivers of FinTech adoption in rural areas. The study also revealed that Perceived Privacy Risk acts as a moderating factor in the dynamics between Perceived Traceability, Security and FinTech Adoption, although this moderating effect was not observed in the relationship between Perceived Accessibility and FinTech Adoption. Additionally, the ANN analysis results matched the PLS-SEM outcomes, reinforcing the significance of the identified factors. The study found variations in factor impact across methodologies, suggesting future research directions. Originality/value This study offers essential guidance for decision-makers in rural FinTech adoption, focusing on improving accessibility, security, convenience and financial literacy. It enhances understanding of FinTech’s key drivers in rural contexts, contributing to the field’s literature. Additionally, it provides actionable recommendations for policymakers and organizations to advance financial inclusivity in these regions.

Asia-Pacific Journal of Business AdministrationVol. 18(1)
University of Selangor (MY), Sunway University (MY), College of Business Administration (LV)
Openalex Percentile: Top 4%
FinTech, Crowdfunding, Digital Finance
6.85
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