![]() This research found that green does impact the condominium price. Green factors also included in the analysed as independent variable which represent by the green certification, GBI. The data was analysed quantitively with descriptive analysis and regression analysis. This research was conducted using 1,335 condominium prices between 20 with 18 independent variables. Next, second objective is to analyse the relationship between the factors that influence the green condominium price in Penang. From the discussion among valuer found that integrating green elements in the current valuation practice is not visible. Further, this research also identifies the valuer’s role should elaborate more in demonstrating the awareness and acceptance of sustainability in the property market. Through literature review and interview among 15 valuers in Penang, the objective was achieved. The first objective is to identify the factors influencing the green condominium price in Penang. The scope of research covers a condominium sale transaction in the Penang property market. The aim of this research is to develop a hedonic price model for green condominium market. The theoretical stage provides evidence that substantiates the need for the study and outlines possible ways to address green elements in hedonic price modelling. The research methodology comprises theoretical, empirical, and evaluation stages. This research proposes three objectives to achieve in order to understand the impact of green on condominium market price using quantitative methods. In line with that, the valuer should also acknowledge the green element as a factor that impacts the value of the building. Literature and research grow to understand more on the economics of green using the green building in most countries as case studies. In addition, further analysis is made on the reason of the processing complexity variable of the data algorithm which does not conform to the expected estimation.This research sets out to investigate the impact of green on the condominium market. Data evaluation satisfaction (number of collected users), request parameters (business), return parameters (business), data range, and response speed are positively correlated with data price. According to the analysis of the sample data sources from the data market, the number of free trials, data specification and quantity, data attention (number of data visits), data demand (sales volume), and preferential policies for businesses are negatively correlated with data price. Through testing and estimation, it is considered that the hedonic price models can be fitted by a logarithmic function, taken as the function form of data hedonic price analysis. An empirical analysis is conducted based on 1010 data commodity sample data points from the Jingdong Vientiane platform. From the perspective of data transactions, this paper proposes construction of a data price characteristic index system from three aspects: data objects, data demanders and data suppliers. Data have become an emerging factor of production the development of the data trading market is accelerating, but data pricing remains in the initial exploration stage.īased on hedonic price theory, this paper analyzes the factors influencing data prices.
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