International Journal of Strategic Property Management

Capitalization effects of rivers in urban housing submarkets – A case study of the Yangtze River

2024-04-04T18:24:59+03:00

The study aims to investigate the heterogeneity of the Yangtze River’s impact on housing prices, using the data of 12,325 residential transactions within 8 kilometers of the Yangtze River in Wuhan, based on submarkets divided according to geographical location and buyer groups. The kernel density plots reveal that properties near the Yangtze River have the highest price and the lowest density, while properties further away from the river exhibit the opposite trend. Then the Spatial Generalized Additive Model and the Spatial Quantile Generalized Additive Model show the following results, respectively: (1) The Yangtze River has an influence range of roughly 5 kilometers on adjacent dwellings, with an average impact of 0.035%. However, within the chosen geographical interval, the impact rises from 1.582% to 2.072%. (2) The Yangtze River has the greatest impact on middle-priced houses, followed by high-priced houses, and the least impact on low-priced houses. (3) The Spatial Generalized Additive Model and the Spatial Quantile Generalized Additive Model have been proven to be effective at capturing spatial and temporal impacts on data. In conclusion, this article advises that the government should pay more attention to non-central locations with limited natural resources.

Alleviating surveyor bias in real estate: An application to vacancy and property prices

2024-04-04T18:24:59+03:00

Although vacancies in the real estate market have always been of key interest to both private and public stakeholders, measuring the impact of vacancy rates on property prices is challenging. This study attempts to quantify the extent of the influence of vacancy rates on the price decline of commercial properties. The dataset used in this study was collected and collated by valuation experts. We attempt to alleviate the bias inherent in the price estimates provided by the surveyors. A Bayesian multilevel estimation model was employed, and the results revealed that while some experts do not show deviations from the standard tendency of a peer group, others do diverge from this norm. Based on these findings, a bias-controlling price decline rate was derived. As many real estate statistics are produced based on survey data compiled by experts, the approach adopted in this study is expected to be applied to various real estate practices to mitigate the inherent and inevitable surveyor bias.

Livability and futures studies of worn-out urban textures: Scenario analysis for evaluating the livability system and achieving sustainability

2024-04-30T18:25:34+03:00

Urban worn-out textures, due to their ancient and historically valuable physical structures, exhibit low adaptability to urban developments and advancements. Tehran, as a city with a rich historical background, also boasts considerable worn-out textures. Due to economic, geographical, and political conditions, a large population resides in these textures. In this regard, the present research aims to investigate the livability status of residents, identify key indicators, and design scenarios in the worn-out textures of Tehran city. This paper proposes a new approach to MicMac that promotes driving forces to scenarios. The results indicate that the livability of residents in worn-out textures of Tehran city, particularly in central regions, is in undesirable conditions. Furthermore, the analysis of the MicMac matrix showed that housing prices, residents’ income, investment, and an increase in economic activities, as well as the role of urban management, are driving forces that have a vital impact on the livability of residents in worn-out textures. These driving forces have depicted three scenarios for the livability of worn-out textures in Tehran city until the year 2032.

A dynamic performance-based payment mechanism for Public-Private Partnership projects: An integrated model for principal-agent and multi-objective optimization models

2024-05-13T08:28:55+03:00

Performance-based payment mechanism is one of the key issues to ensure all stakeholders’ benefits in infrastructure Public-Private Partnership (PPP) projects. However, most existing research on performance-based payment with a fixed incentive coefficient can’t play a good incentive role. This study aims to the intrinsic mechanism between the performance appraisal score and the performance-based payment structure, so as to design the dynamic performance-based payment mechanism for infrastructure PPP projects. Firstly, the multi-objective optimal method is used to calculate the unit-payment. Second, principal-agent theory is used to construct the performance-based payment model with a changeable incentive coefficient. The findings of this study show that, the performance-based payment mechanism can effectively motivate participants to provide high-quality and efficient services, because their remuneration directly depends on their performance. When the outcome does not meet expectations, the amount paid can be adjusted accordingly, thus ensuring the maximum protection of public resources as well as the private sector’s profits. They serve a dual purpose, on one hand, they offer insights to rectify the shortcomings in the current unsatisfactory payment structure. On the other hand, the study provides a theoretical reference for the public sector to effectively incentivize the private sector in enhancing project performance.

Extracting and prioritizing the attractiveness parameters of shopping centers under intuitionistic fuzzy numbers

2024-05-13T18:25:40+03:00

Shopping center plays an important role in distribution system and marketing. These canters provide an appropriate atmosphere for customers; so that, the customers achieve the best service within a short time. However, there is an intense competition among shopping centers to attract more customers for increasing the profit. Therefore, a powerful model assists authorities in identifying the critical competitive aspects and directing their efforts toward performance improvement. However, a number of strategies have been developed to identify the most relevant components. The Delphi technique under intuitionistic fuzzy environment, called intuitionistic fuzzy Delphi method (IFDM) study, is a group-based technique that can simply formulate the uncertainty imposed by decision making circle. On the other hand, multi criteria decision making (MCDM) method such as analytical network process (ANP) is a mathematical tool for taking into account mutual relationships in order to rank a number of criteria. Nonetheless, the ANP is unable to account for the uncertainty involved in the decision-making process. Similarly, the intuitionistic fuzzy set (IFS) can express ambiguity and vagueness by utilizing the given scale. Because the IFS is robust in dealing with complexity and ambiguity, the IFS-GANP (an integrated model of the IFS and ANP methods under group decision) can result in a more specific description of the situation. As a result, the IFS-GANP approach outperforms both conventional ANP and fuzzy ANP. To demonstrate the model’s feasibility, a case study rating the essential aspects impacting the attractiveness of retail centers is shown. The result demonstrates factor C31 (Location) with value of 0.202 plays the greatest role in attracting customers.