TY - JOUR AU - Randeniya, TD AU - Ranasinghe, Gayani AU - Amarawickrama, Susantha PY - 2017/05/15 Y2 - 2024/03/28 TI - A model to Estimate the Implicit Values of Housing Attributes by Applying the Hedonic Pricing Method JF - International Journal of Built Environment and Sustainability JA - Int J. of BES VL - 4 IS - 2 SE - Articles DO - 10.11113/ijbes.v4.n2.182 UR - https://ijbes.utm.my/index.php/ijbes/article/view/182 SP - AB - Many scholars focused on the location based attributes rather than the non-location factors in decision making on land prices. Further, new research studies have identified the importance of the non-location attributes with the location factors. Many studies suggest that, many attributes exist which affects the housing price. Since the attributes involved and dominant for a particular case differs from one situation to the other, there cannot be an exact list of attributes. Yet, identification of factors that determine housing price and their relationships and the level of influence have poorly understood in planning and property development in the context of Sri Lanka. This study attempts to address what make householders to decide on housing price and application of hedonic pricing approach to estimate the implicit price of housing attributes in context of Sri Lanka. A sample study of selected fifty (50) single house transactions in Maharagama urban neighborhood area has been utilized to illustrate the applicability of the hedonic pricing model. As a methodology, correlation analysis has been carried out to study the degree of relationship between the housing price and the independent variables. The attributes which correlate with housing prices, the study identified the most significant attributes. A model was developed to estimate the future house price by applying the pricing model which is incorporated with these attributes. A hedonic house price model derived from multiple liner regression analysis was developed for the purpose. The findings reveal that six attributes as design type of the house, distance to the local road, quality of Infrastructure, garden size, number of the bed rooms and property age are contributed to estimate the implicit value of Housing property. The model developed would be used to identify implicit values of houses located in urban neighborhood area of Sri Lanka. ER -