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Impact of artificial intelligence on decision-making quality in mobile financial services in Bangladesh: the mediating role of risk mitigation

Sabira Kumkum et al.

Journal of Decision Systems2026https://doi.org/10.1080/12460125.2026.2620371article
AJG 1ABDC B
Weight
0.50

Abstract

This empirical study examines the Artificial Intelligence (AI) integration into the Bangladeshi Mobile Financial Services (MFS), focusing on enhancing Decision-Making Quality (DMQ) through the mediating role of Risk Mitigation Effectiveness (RME). Applying the Technology-Organization-Environment (TOE) framework and Partial Least Squares Structural Equation Modelling (PLS-SEM), it analyzes how AI-based Decision Support Systems (DSS) and Risk Identification Tools (RIT) enhance DMQ. The results indicate that while AI-driven DSS directly improves decision quality, RIT’s influence is significantly mediated by risk mitigation effectiveness. By addressing a significant gap in emerging economy literature, this research proposes a modified ‘TOE-RME model,’ extending the foundational TOE framework by establishing risk mitigation as a mandatory mediator. The findings highlight that robust infrastructure development and organizational preparedness are critical for successful integration. Consequently, the study offers key actionable recommendations for MFS providers, financial institutions, and policymakers to optimize AI adoption to achieve superior decision-making and effective strategic risk management.

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https://doi.org/https://doi.org/10.1080/12460125.2026.2620371

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@article{sabira2026,
  title        = {{Impact of artificial intelligence on decision-making quality in mobile financial services in Bangladesh: the mediating role of risk mitigation}},
  author       = {Sabira Kumkum et al.},
  journal      = {Journal of Decision Systems},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/12460125.2026.2620371},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.