Abstract The paper conducts a detailed examination of the existing evaluative frameworks for microfinance institutions to gauge the differences and similarities. Efficiency evaluates how MFIs are meeting the performance standards considering time and budget constraints. Outreach evaluates the effectiveness of MFIs in reaching the beneficiaries. Relative efficiency scores were calculated using data envelopment analysis and outreach was measured in five different dimensions (pentagon model). Further, cluster analysis assisted in categorizing the MFIs into five value clusters. The study compares both outreach performance and relative efficiency scores employing ANOVA and correlation analysis. The study was conducted among the Indian context when the sector was hit by crisis during 2010. Paper brought out important insights about the sample. Indian MFIs were found to be more socially efficient, since the social dimension taken into consideration was number of female clients and majority of Indian MFIs has exclusive female focus. The correlation tests found that relative efficiency scores are positively related to depth (poor focus) and length (sustainability) outreach. The results showed that cluster analysis model basing outreach scores was more comprehensive and captured more information compared to the data envelopment model relative efficiency scores. The study is original in its approach in using cluster analysis for outreach performance and in the objective of comparing the two different models.

中文翻译：

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印度小额信贷机构背景下的绩效评估框架

摘要本文对小额信贷机构现有的评估框架进行了详细的研究，以衡量其异同。效率评估考虑到时间和预算限制，小额信贷机构如何达到绩效标准。外联评估小额信贷机构在惠及受益人方面的有效性。使用数据包络分析计算相对效率得分，并在五个不同维度（五边形模型）中测量范围。此外，聚类分析有助于将小额信贷机构分类为五个价值聚类。该研究使用方差分析和相关分析比较了外展绩效和相对效率得分。这项研究是在2010年该行业受到危机打击的印度背景下进行的。论文为该样本提供了重要见解。人们发现，印度的小额信贷机构在社会上更有效率，因为考虑到的社会因素是女性客户的数量，而印度的小额信贷机构多数只关注女性。相关性测试发现，相对效率得分与深度（重点不佳）和长度（可持续性）的提高呈正相关。结果表明，与数据包络模型相对效率得分相比，基于扩展得分的聚类分析模型更加全面，并捕获了更多信息。该研究的原始方法是将聚类分析用于外展绩效，并比较两个不同的模型。相关性测试发现，相对效率得分与深度（重点不佳）和长度（可持续性）的提高呈正相关。结果表明，与数据包络模型相对效率得分相比，基于扩展得分的聚类分析模型更加全面，并捕获了更多信息。该研究的原始方法是将聚类分析用于外展绩效，并比较两个不同的模型。相关性测试发现，相对效率得分与深度（重点不佳）和长度（可持续性）的提高呈正相关。结果表明，与数据包络模型相对效率得分相比，基于扩展得分的聚类分析模型更加全面，并捕获了更多信息。该研究的原始方法是将聚类分析用于外展绩效，并比较两个不同的模型。