Abstract In an innovative approach to traditional house searches, this study leverages Data Envelopment Analysis (DEA) with the Charnes, Cooper and Rhodes (CCR) model. Live Housing data from a diverse pool of houses is analyzed, clustering them based on price ranges. By constructing an efficiency frontier graph, the study identifies optimal housing allocations within each cluster. This method not only refines the house search process but also quantifies the efficiency of houses, enabling a nuanced comparison. The application of DEA provides a robust framework for evaluating housing options, offering a data-driven solution to enhance decision-making in the real estate market.
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GUPTA et al. (2024) studied this question.
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