Research on the Application of Consumer Psychology Theory in Real Estate Marketing

Hou, Runhan

doi:10.2991/ebmcsr-18.2018.26

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…Although distributed in different areas around the world, the scaling of the exponent ratio was approximately 3/2 across cities, as indicated by the dashed line in Fig. 5, implying the internal psychological processes associated with house purchasing behaviors were held in common [72]. Moreover, the slope of GCD in the four cities corresponds to the y-axis labeled 9 and the x-axis labeled 6, i.e., the slope = y/ x ≈ 9/6 = 3/2 [37,40].…”

Section: Resultsmentioning

confidence: 96%

Continuous Symmetry Analysis of the Effects of City Infrastructures on Invariant Metrics for House Market Volatilities

Lin¹,

Wang²,

Zhong³

et al. 2022

Computer Modeling in Engineering &Amp; Sciences

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The invariant metrics of the effects of park size and distance to public transportation on housing value volatilities in Boston, Milwaukee, Taipei and Tokyo are investigated. They reveal a Cobb-Douglas-like behavior. The scaleinvariant exponents corresponding to the percentage of a green area (a) are 7.4, 8.41, 14.1 and 15.5 for Boston, Milwaukee, Taipei and Tokyo, respectively, while the corresponding direct distances to the nearest metro station (d) are −5, −5.88, −10 and −10, for Boston, Milwaukee, Taipei and Tokyo, respectively. The multiphysics-based analysis provides a powerful approach for the symmetry characterization of market engineering. The scaling exponent ratio between park area percentages and distances to metro stations is approximately 3/2. The scaling exponent ratio expressed in the perceptual stimuli will remain invariant under group transformation. According to Stevens' power law, the perception-dependent feature spaces for parks and public transportation can be described as two-and three-dimensional conceptual spaces. Based on the prolongation structure of the Schrödinger equation, the SL(2, R) models are used to analyze the house-price volatilities. Consistent with Shepard's law, the rotational group leads to a Gaussian pattern, exhibiting an extension of the special linear group structure by embedding SO(3) ⊗ R(3) in SL(2, R). The influencing factors related to cognitive functioning exhibit substantially different scaleinvariant characteristics corresponding to the complexity of the socio-economic features. Accordingly, the contour shapes of the price volatilities obtained from the group-theoretical analysis not only corroborate the impact of the housing pricing estimation in these cities but also reveal the invariant features of their housing markets are faced with the forthcoming sustainable development of big data technologies and computational urban science research.

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Section: Resultsmentioning

confidence: 96%

Continuous Symmetry Analysis of the Effects of City Infrastructures on Invariant Metrics for House Market Volatilities

Lin¹,

Wang²,

Zhong³

et al. 2022

Computer Modeling in Engineering &Amp; Sciences

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“…"Big data" has penetrated into all walks of life, which subverts the operation thinking and marketing mode of many traditional industries. In this context, big data touches the nerves of the real estate industry, and real estate enterprises can accurately understand the demand of consumers, so as to formulate accurate marketing strategy [5].…”

Section: Introductionmentioning

confidence: 99%

Research on Precision Marketing of Real Estate Market Based on Data Mining

Huang

Mao

2022

Scientific Programming

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As one of the basic industries in China, the real estate industry contributes much to the national GDP every year and plays an important role in stimulating the economy. After years of development, the real estate industry has accumulated a large number of sales data, includes the data of customer and construction. However, the utilization of them is still in the stage of extensive collection and use, which is not sufficient for the accumulated data. Therefore, a precise marketing management system for real estate enterprises based on data mining technology is developed in this paper. Through big data mining, the target customers can be accurately subdivided and portraited, which realizes the matching and prediction of resources. On this basis, accurate marketing and promotion of multichannel collaboration are implemented, which realizes the innovation of real estate marketing mode in the era of big data.

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Research on the Application of Consumer Psychology Theory in Real Estate Marketing

Cited by 2 publications

References 3 publications

Continuous Symmetry Analysis of the Effects of City Infrastructures on Invariant Metrics for House Market Volatilities

Continuous Symmetry Analysis of the Effects of City Infrastructures on Invariant Metrics for House Market Volatilities

Research on Precision Marketing of Real Estate Market Based on Data Mining

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