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Urban land-use efficiency (LUE) has become a central concern in the context of increasing land scarcity and urban redevelopment. However, existing evaluation approaches often compare LUE based on realized outcomes or observed efficiency benchmarks, making it difficult to distinguish inefficient land use from differences arising from heterogeneous land functions and spatial contexts. This perspective proposes a context-dependent conceptual framework for interpreting LUE by distinguishing between actual functional outcome (AFO) and expected functional outcome (EFO), where EFO represents the functional outcome that can reasonably be expected under its functional type and spatial context. Building on this distinction, the framework first establishes functionally comparable evaluation units through functional refinement and then interprets LUE as the degree of alignment between actual and context-conditioned expected functional outcomes. It provides a unified conceptual perspective for understanding context-dependent LUE while integrating existing spatial statistical, machine-learning, and efficiency analysis approaches within a common theoretical framework. By shifting attention from comparing realized outcomes alone toward interpreting their relationship with context-conditioned expectations, the proposed framework provides a conceptual basis for identifying relatively inefficient land and advancing the interpretation of urban land-use efficiency under heterogeneous spatial conditions.
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Dong et al. (2026) studied this question.
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