International Journal of Civil and Structural Engineering Research ISSN 2348-7607 (Online) Vol. 10, Issue 1, pp: (38-50), Month: April 2022 - September 2022, Available at: www.researchpublish.com
PRICE DIFFERENTIATION MODEL BETWEEN UNITS FOR VERTICAL HOUSING: A STUDY OF A BUILDING CONSTRUCTION COMPANY Edilson De Souza Vidal1, Sérgio Junichi Idehara2 1,2 1,2
Joinville School of Technology
Federal University of Santa Catarina (UFSC), Joinville, Brazil DOI: https://doi.org/10.5281/zenodo.6475476 Published date: 21-April-2022
Abstract: The use of the internet as a sales channel provides the consumer with information, facilitating the comparison of goods and increasing the already existing competitiveness between companies. The customer chooses by analyzing the products in terms of their attributes and according to the purchasing power. In this sense, an adequate pricing process is essential for any company. In the construction industry, this issue is even more relevant because of the heterogeneity of housing units. Furthermore, the high purchase price compared to other products, together with a variety of subjective attributes in the customer's perception, make the pricing process a complex undertaking. Thus, one question would be how to devise a distribution of prices in vertical housing, where the units in a building vary in size, number of rooms and external views. With the aim of defining a price differentiation model between units, this study was carried out based on the price formation process in a construction company in Santa Catarina state, Brazil. With the collected empirical data, a hedonic multivariate linear regression model was developed, with the aim of constructing an automated price differentiation system. The mathematical model showed good results for the numerical adjustment and in its ability to estimate price differentiation based on quantifiable attributes. Thus, it provides evidence of the applicability of the method in the correlation of the client's subjective attributes with the value of residential units in vertical condominiums. Keywords: Pricing; residential property; numerical method; linear regression.
I. INTRODUCTION According to [1], civil construction represented 6.5% of the national Gross Domestic Product (GDP) in 2012, but following a decrease in national GDP, it fell to 3.7% in 2019. The outbreak of the Coronavirus (COVID-19) further affected the construction industry, but the sector is referred as a way to downturn the situation ([2]). This economic scenario illustrates the importance of civil construction in regional development, as it can lead to an increase in national income levels and give greater access to durable goods with a higher market value [3]. In addition to construction companies, there are a number of other professions—such as designers, realtors and brokers—which are instrumental in developing and selling a property, and the role of the real estate agent is also crucial. Taking into account these factors, the real market value can be estimated [4]. Despite this, numerous other factors and fluctuation in demand may affect the final price, making the pricing process a difficult task. Recently, easier access to information has become evident through the speed at which communication occurs between people and different sectors of the market. This development brings a high degree of competition, since when making a purchase, the customer has access to a variety of possibilities. This starts to regulate the relationship between supply and demand, bringing about a change in real estate prices [5]. As mentioned by [6], the growing use of e-commerce tools and
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