Applicability and effectiveness of classifications models for achieving the twin objectives of growth and outreach of microfinance institutions

Manojit Chattopadhyay () and Subrata Kumar Mitra ()
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Manojit Chattopadhyay: Indian Institute of Management Raipur
Subrata Kumar Mitra: Indian Institute of Management Raipur

Computational and Mathematical Organization Theory, 2017, vol. 23, issue 4, No 1, 474 pages

Abstract: Abstract Measuring performance of microfinance institutions (MFIs) is challenging as MFIs must achieve the twin objectives of outreach and sustainability. We propose a new measure to capture the performance of MFIs by placing their twin achievements in a 2 × 2 grid of a classification matrix. To make a dichotomous classification, MFIs that meet both their twin objectives are classified as ‘1’ and MFIs who could not meet their dual objectives simultaneously are designated as ‘0’. Six classifiers are applied to analyze the operating and financial characteristics of MFIs that can offer a predictive modeling solution in achieving their objectives and the results of the classifiers are comprehended using technique for order preference by similarity to ideal solution to identify an appropriate classifier based on ranking of measures of performance. Out of six classifiers applied in the study, kernel lab-support vector machines achieved highest accuracy and lowest classification error rate that discriminates the best achievement of the MFIs’ twin objective. MFIs can use both these steps to identify whether they are on the right path to attaining their multiple objectives from their operating characteristics.

Keywords: Microfinance institution; Growth and outreach; Performance measure; Classification algorithm; TOPSIS (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10588-016-9237-x

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