ENHANCING THE ACCURACY OF MALAYSIAN HOUSE PRICE FORECASTING: A COMPARATIVE ANALYSIS ON THE FORECASTING PERFORMANCE BETWEEN THE HEDONIC PRICE MODEL AND ARTIFICIAL NEURAL NETWORK MODEL

The Hedonic Price Model (HPM), a prominent model used in real estate appraisal and economics, has been argued to be marred with nonlinearity, multicollinearity and heteroscedasticity problems that affect the accuracy of price predictions. An alternative method called Artificial Neural Network Model (ANN) was identified as capable of addressing the shortcomings of HPM and produces superior predictive performance. Hence, this study aims to evaluate the forecasting performance between HPM and ANN using Malaysian housing transaction data from the period between 2009 to 2018, sourced from the Valuation and Property Service Department, Johor Bahru. The models’ performance was evaluated and compared based on their statistical and predictive performance. Results showed that ANN outperformed HPM in both statistical and predictive performance. This study benefits the expansion of academic and practical knowledge in enhancing the accuracy of house price forecasting.

Investigating Green Marketing Implementation with the Hedonic Price Model in Residential Projects: The Case of Istanbul

The strategic importance of green marketing (GM) in value creation for the end customer (VCEC) and the contribution of the spatial and structural characteristics of a residential project (RP) to the final price have been acknowledged in the literature. However, GM features that can lead to price increases have not been evaluated from the VCEC perspective. This study examines the impacts of GM strategies on RPs. This study applies Hedonic Price Modelling to newly built RPs in Istanbul and evaluates the results from the perspective of the Attractive Quality Attributes Theory. The results showed that the total price of the RPs was affected more by design-related sustainable features of RPs and revealed that there is a relationship between GM and sustainable design. The study highlights the importance of GM, which companies can use to operate effectively in a competitive market and increase the satisfaction of end customers through value creation. The study’s findings can be considered useful information for policies on creating a sustainable built environment.

Does Pet Policy in a Condominium Building Impact Property Values?

Pets are permitted in some condominium buildings and not in others. Pet owners will therefore be attracted more towards buildings that welcome pets than otherwise. However, the pet-related regulations may altogether restrict all sorts of pets, including small pets, such as cats, while others may include restrictions on the number of pets allowed per unit, certain breeds or set restrictions on the permissible size of a pet. These restrictions may impact the price of condominiums. Using a hedonic price model, this research paper analyses whether and by how much allowance for pets in the building impacts property values in downtown Toronto using condominium sales data from January 2016 to December 2017 and information derived from a pet policy questionnaire. The findings suggest that the price differences are not statistically significant between buildings that allow pets or otherwise. In fact, the real price difference is observed for the degree of pet friendliness. Condominium buildings that allow two or more pets sell for higher prices than those that allow less than two pets. Furthermore, condominium buildings that allow two or more dogs sell for a higher price. Also, condominium buildings that impose weight, size or breed restrictions cost 5.7 percent more than those do not have those restrictions. Keywords: hedonic price model, pet policy, condominiums, GIS, Toronto

Does Pet Policy in a Condominium Building Impact Property Values?

Pets are permitted in some condominium buildings and not in others. Pet owners will therefore be attracted more towards buildings that welcome pets than otherwise. However, the pet-related regulations may altogether restrict all sorts of pets, including small pets, such as cats, while others may include restrictions on the number of pets allowed per unit, certain breeds or set restrictions on the permissible size of a pet. These restrictions may impact the price of condominiums. Using a hedonic price model, this research paper analyses whether and by how much allowance for pets in the building impacts property values in downtown Toronto using condominium sales data from January 2016 to December 2017 and information derived from a pet policy questionnaire. The findings suggest that the price differences are not statistically significant between buildings that allow pets or otherwise. In fact, the real price difference is observed for the degree of pet friendliness. Condominium buildings that allow two or more pets sell for higher prices than those that allow less than two pets. Furthermore, condominium buildings that allow two or more dogs sell for a higher price. Also, condominium buildings that impose weight, size or breed restrictions cost 5.7 percent more than those do not have those restrictions. Keywords: hedonic price model, pet policy, condominiums, GIS, Toronto

Understanding the Effects of Influential Factors on Housing Prices by Combining Extreme Gradient Boosting and a Hedonic Price Model (XGBoost-HPM)

The characteristics of housing and location conditions are the main drivers of spatial differences in housing prices, which is a topic attracting high interest in both real estate and geography research. One of the most popular models, the hedonic price model (HPM), has limitations in identifying nonlinear relationships and distinguishing the importance of influential factors. Therefore, extreme gradient boosting (XGBoost), a popular machine learning technology, and the HPM were combined to analyse the comprehensive effects of influential factors on housing prices. XGBoost was employed to identify the importance order of factors and HPM was adopted to reveal the value of the original non-market priced influential factors. The results showed that combining the two models can lead to good performance and increase understanding of the spatial variations in housing prices. Our work found that (1) the five most important variables for Shenzhen housing prices were distance to city centre, green view index, population density, property management fee and economic level; (2) space quality at the human scale had important effects on housing prices; and (3) some traditional factors, especially variables related to education, should be modified according to the development of the real estate market. The results showed that the demonstrated multisource geo-tagged data fusion framework, which integrated XGBoost and HPM, is practical and supports a comprehensive understanding of the relationships between housing prices and influential factors. The findings in this article provide essential implications for informing equitable housing policies and designing liveable neighbourhoods.

The Influence of Floor Type of Multi-Family Residential on the Transaction Price and the Estimation of Utility Ratio among Floors

In Taiwan’s multi-family residential, there are some problems in the previous research on the utility ratio among floors, including the failure to consider the difference in total number of floors, the excessive research scope and the residential price without deducting the parking space price. This research hopes to improve the problems of previous research, select 1,172 data of multi-family residential with total number of floors of 12, 15 and 22, and use the hedonic price model to establish the utility ratio among floors of residential buildings, and then compare the difference between absolute floors and relative floors on the transaction price. The empirical results found that in the comparative analysis of absolute floors and relative floors, the variable of relative floors is significant, showing that the residential price is significantly different with different total number of floors, and the total number of floors is higher that the residential price is higher; the importance of absolute floors on the residential price isn’t high. In the model of utility ratio among floors of different total number of floors, the utility curves are distributed in zigzag pattern. Taking floor 4 as the base floor, the floor price difference is higher on floor 1 and near the top floors, and the floor price difference of other floors is not significant.