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Analysis and Evaluation of the Model for Impact Assessment, for a social impact NGO: Validity Testing in a Real World Context
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This dissertation evaluates the validity and robustness of the Entity B model for measuring social impact in non-profit housing interventions and examines its ability to capture multidimensional change. Guided by two research questions, this study applies a mixed-methods approach structured under the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework. Quantitative analysis was conducted using a multiple linear regression on survey data, while qualitative insights were integrated through sentiment analysis of beneficiaries’ open-ended responses. Results confirm strong internal coherence and explanatory power (R-squared = 0.90), with physical indicators emerging as the dominant predictors of perceived impact. Yet, the social and financial dimensions exhibit weak explanatory capacity, and the professional dimension had to be excluded due to data constraints - indicating that the model only partially achieves its multidimensional ambition. The sentiment analysis corroborates these findings, revealing predominantly positive perceptions associated with housing improvements but limited evidence of relational or economic transformation. Theoretically, this research advances methodological innovation by validating a hybrid framework that combines data mining processes with computational text analysis, offering a replicable approach for multidimensional impact assessment. Practically, it provides actionable recommendations for non-profit organisations: baseline data collection, longitudinal follow-up, and stakeholder triangulation, to strengthen accountability and learning mechanisms. Limitations include the absence of baseline data, reliance on self-reported perceptions, short observation windows, and exclusion of the professional dimension. Future research should address these gaps through longitudinal designs, reintegration of omitted dimensions, refinement of relational indicators, and benchmarking against established frameworks such as Social Return on Investment (SROI) and Most Significant Change (MSC).
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Social Impact Measurement Nonprofit Housing Interventions Mixed-Methods Approach CRISP-DM Framework Multiple Linear Regression Sentiment Analysis