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Modeling the efficiency of financial inclusion in Bihar: A data envelopment analysis

Archila Kushwaha et al.

International Journal of Accounting, Business and Finance2025https://doi.org/10.55429/ijabf.v3i2.147article
ABDC C
Weight
0.37

What the paper says

The study aims to evaluate the effectiveness of financial inclusion in Bihar from 2016-2017 to 2020-2021 and analyze the variations across different districts. The study uses secondary data from the State Level Bankers Committee Report and employs the CCR 1978 model and the Super Radial Efficiency model of DEA to measure overall technical efficiency. The analysis considers 10 indicators representing 4 dimensions of financial inclusion. The study identifies districts with improving financial inclusion levels and identifies efficient districts as benchmarks for others to emulate. Some districts show stagnation or decline, indicating the need for targeted interventions and policy measures. Policymakers can use the efficiency scores to identify districts requiring more support for enhancing financial inclusion. Financial institutions can learn from the practices of efficient districts to improve their services in less efficient areas. The focus on district-level analysis highlights the importance of decentralization in financial inclusion planning and implementation.

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https://doi.org/https://doi.org/10.55429/ijabf.v3i2.147

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@article{archila2025,
  title        = {{Modeling the efficiency of financial inclusion in Bihar: A data envelopment analysis}},
  author       = {Archila Kushwaha et al.},
  journal      = {International Journal of Accounting, Business and Finance},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.55429/ijabf.v3i2.147},
}

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Modeling the efficiency of financial inclusion in Bihar: A data envelopment analysis

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Evidence weight

0.37

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

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
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.