Heterogeneity in Marginal Willingness to Pay for Urban Space Quality: A Case Study in Beijing

This study evaluated urban space quality in Beijing using service quality and landscape quality based on points of interest (POI) data, street view data, and perception data derived from deep learning and then applied a hedonic price model (HPM) and a spatial lag model (SLM) to calculate people's heterogeneity marginal willingness to pay (MWTP) for urban space quality across categories, locations, and purchasers. The results showed that (1) people are willing to pay for urban space quality, especially urban landscape quality; however, the MWTP for urban space quality decreases as its distance from the main employment center increases; (2) the MWTP for urban space quality has an inverted u-shaped relationship, indicating that individuals with medium income exhibit a higher willingness to pay for urban space quality; and (3) urban space quality exhibits spatial spillover effects on individuals' MWTP in surrounding areas, with a spatial spillover boundary of approximately 22 km. Overall, this study provided important insights into quantifying the economic benefits of urban space quality and highlights the importance of considering different categories, locations, and purchasers when assessing urban space quality.