Drivers of housing purchasing decisions : a data-driven analysis

Purpose: The purpose of this paper is to develop a clear understanding of the features that increase the probability of condos’ sale, with a focus on design-related features. Design/methodology/approach: The present research uses survival analysis (SA) and the Cox proportional-hazards regression (CPHR) to analyze condo sales data provided by the REALTORS® Association of Edmonton (RAE) (Alberta, Canada). Findings: The analysis of the provided data shows that the listed price, building age, appliances and condo fees have less effect on the time a condo spends on the market compared to the condo’s physical features, such as construction material, interior finishing and heating type and source. Research limitations/implications: The data used in the present research comes from one geographical area (i.e. Edmonton, Canada). Furthermore, the data provided by the RAE does not include any real estate transactions not involving a realtor. Additionally, the present research, owing to its focus on design-related features, does not control features related to the external environment, such as community and transportation proximity. Practical implications: The findings of the present research help construction practitioners (e.g. architects, builders and realtors) better understand the features that influence condo buyers’ decisions. This knowledge helps to develop designs and marketing strategies that increase the likelihood of selling and decrease the time listed condos spend on the market. Originality/value: The present research expands our knowledge of the drivers influencing the purchasers’ decisions concerning the building’s physical features that can be controlled during the design stage. Also, analyzing the provided data by using SA and CPHR, as followed in this paper, facilitates the inclusion of records that are listed but not sold, which helps to overcome the survivorship bias and avoid the over-optimism that exists in the present literature.