Initial sales rates are critical for gauging project financing (PF) project risk ex ante, as they determine the realizability of future cash flows. This study approaches initial sales performance not as the outcome of isolated individual factors but as the result of the market’s collective choice regarding the bundles of characteristics offered by housing projects. To frame this perspective, the study adopts Lancaster’s (1966) characteristics-based consumer theory as its theoretical foundation and classifies PF projects using K-means clustering. Moving beyond the question of “which factors are statistically significant on average,” it provides a structural answer to a different question: “Which bundles of characteristics enable housing projects to absorb demand more rapidly and thereby exhibit greater resilience to PF risk?” The K-means results show that the cluster with high initial sales rates is characterized by a combination of mid-sized unit composition, a non-excessive supply scale, price levels comparable to nearby competing projects, and a stable market phase. By shifting the analytical focus from variable-level marginal effects to an attribute-centered perspective, this study offers a more structural interpretation of housing project sales performance and contributes to practical PF risk management.
Eunmi Kim (Wed,) studied this question.