International Journal of Strategic Property Management

Does China’s housing supply-demand relationship impact urban innovation capability

2025-02-18T18:30:39+02:00

Unlike existing literature that explores the impact of house prices on urban innovation, this paper skillfully examines the relationship between the housing market and urban innovation from the perspective of the housing supply-demand (S-D) relationship. Utilizing panel data from 284 prefecture-level cities in China spanning from 2005 to 2020, this study investigates the respective impacts of housing supply, housing demand, and their interplay on urban innovation capacity (UIC). Our findings indicate that housing supply positively influences UIC, with a coefficient of 0.060; specifically, for every 1% increase in housing supply, UIC increases by 0.06%. Similarly, housing demand also significantly affects UIC, with a coefficient of 0.060, suggesting that a 1% increase in housing demand corresponds to a 0.060% rise in UIC. However, we observe a significant negative effect of the housing S-D relationship on UIC, with a coefficient of –0.049, indicating that an increase in the housing S-D ratio detrimentally impacts urban innovation. Furthermore, our analysis reveals that as the housing supply-demand ratio rises, house prices also tend to increase. Additionally, we identify heterogeneity in our results, indicating variations in the housing supply-demand ratio’s impact on the innovation capacity of cities across different regions.

Supply decision of existing apartment: Case study of apartment transactions in Gangdong district, Seoul, Korea

2025-03-04T10:14:15+02:00

Despite its importance, homeowners’ supply type decision has been under-researched due to data limitations. We construct a dataset of 4,037 apartment units in Gangdong district, Seoul, Korea over a 46-quarter period (2011Q1–2022Q2). We simultaneously analyse both the asset and space markets. The results show that the estimated probability and estimated volume of sale from supply type choice models are statistically significant in both the sales and rental price models. The key findings of our study are two. We find that the housing sales and rental markets interact and co-move together. We also demonstrate that the institution of the two-year lease contract period influences the transaction probabilities in both the sales and rental markets. For the supply type decision model, the estimated sale-transaction (rental-transaction) price significantly impacts the sale-transaction (rental-transaction) volume. However, no significant relationship was found between the estimated sale price and rental-transaction volume, nor between the estimated rental price and sale-transaction volume. The results of the forecast-performance comparison show that the integrated supply model_T/probability (calibrated) is the best for sales volume, whereas the two-year lagged value is the best for rental-volume estimation. This demonstrates institutional effects in the rental-housing market in Korea.

Land purchasing behavior of real estate enterprises: An organizational status perspective

2025-03-17T15:30:14+02:00

Based on resource dependency and signaling theories, this study examines how organizational status affects land purchasing behavior in listed real estate enterprises on China’s Shanghai and Shenzhen A-shares from 2006 to 2023. The findings indicate that the organizational status of real estate enterprises positively impacts their land purchase area, price, and quantity. Further analysis reveals that managerial overconfidence mediates this relationship. Heterogeneity analysis shows that the organizational status of state-owned real estate enterprises positively influences all three types of land purchasing behaviors, while for non-state-owned enterprises, it only significantly affects the area and price of land purchases, not the quantity. This study enriches the theory on land purchasing behavior of real estate enterprises, expands the application scope of organizational status, reveals the mechanisms through which organizational status affects land purchasing behavior and provides valuable insights for guiding rational competition among real estate enterprises, optimizing land resource utilization, and promoting the healthy and sustainable development of the real estate industry.

Residential satisfaction indicator: Latin American evidence

2025-03-24T18:31:13+02:00

Latin American construction companies, particularly in Ecuador, operate in a highly competitive environment. In this context, achieving customer satisfaction is a primary objective for the success of real estate projects. This research aims to develop a comprehensive residential satisfaction index that includes sustainability dimensions, based on global satisfaction indices and structural equation modeling. This study will enable residential builders to assess their performance from the customer’s perspective and make strategic decisions aimed at improving quality, which, in turn, will lead to greater customer satisfaction in future projects. The findings of this research will provide valuable input for decision-making in the real estate sector, with a focus on the Latin American context.

Evaluating smart city technology efficiency and citizen satisfaction using data envelopment analysis

2025-04-01T18:31:21+03:00

This study employs Data Envelopment Analysis (DEA) to evaluate the efficiency of the top 20 smart cities in converting Research and Development (R&D) investments into desired outcomes. Using national R&D expenditure (2015–2022) as input and ten criteria from the IMD 2024 Smart City Index report as outputs, the analysis reveals varying levels of efficiency among leading smart cities. Seven cities achieved perfect efficiency scores, while others, including some high-ranking cities, showed unexpected inefficiencies. This study provides valuable insights into resource utilization and identifies specific areas for improvement across structural and technological dimensions. The limitations include the focus on top-performing cities and the use of national R&D data as a proxy for city-specific investments. The findings of this study offer a foundation for policymakers and urban planners to optimize resource allocation and improve smart city initiatives, contributing to the ongoing development of sustainable urban environments in the face of technological advancements and urban challenges.