A study of demographic difference in external visual preference evaluation of Chinese detached house

Figures & data

Figure 1. Location and map of Jiangsu.

Figure 2. The quantity of detached houses.

Table 1. The statistics of architectural styles of detached houses in Jiangsu province.

Architectural styles of detached houses	quantity	Percentage
French Style	62	23.85%
Modern Style	57	21.92%
Chinese architectural style	48	18.46%
Mediterranean style	34	13.08%
British style	24	9.23%
Medieval style	17	6.54%
Postmodern style	11	4.23%
Neoclassical style	5	1.92%
Minimalist style	2	0.77%

Figure 3. The photos used in the experiment and their numbers.

Table 2. The height-width ratio statistics of detached houses.

Photo No.	height-width ratio of façade A	height-width ratio of façade B	average height-width ratio
1	0.36	0.89	0.63
2	0.41	0.69	0.55
3	0.82	1.81	1.32
4	0.71	1.12	0.92
5	0.52	2.1	1.31
6	0.68	1.87	1.28
7	1.23	2.89	2.06
8	1.18	1.33	1.26
9	0.86	1.12	0.99
10	0.96	1.62	1.26

Figure 4. The schematic diagram of the relative area of windows of detached houses.

Table 3. The window-wall ratio statistics of detached houses.

Photo No.	window-wall ratio of façade A	window-wall ratio of façade B	average window-wall ratio
1	33.5	13.7	23.6
2	42.6	16.9	29.7
3	31.7	9.5	20.6
4	26.4	16.7	21.5
5	34.7	31.5	33.1
6	42.3	22.4	32.5
7	24.6	8.2	16.4
8	22.1	18.3	20.5
9	27.2	16.3	21.7
10	21.3	7.3	14.3

Table 4. The variables of demographic characteristics and corresponding set values.

demographic characteristics	variable	Set value
gender	female	1
	male	2
age	below 17 years old	1
	18–34	2
	35–59	3
	Over 60	4
Have/have no design experience	yes	1
	no	2
Life experience in countryside	yes	1
	no	2

Table 5. The scores and corresponding meaning.

score	Meaning
0	Very dislike
1	Dislike
2	Mild dislike
3	Mild like
4	Like
5	Very like

Table 6. The statistics of participants’ demographic characteristics.

demographic characteristics	variables	The number of Participant	proportion	Overall proportion in Jiangsu province
gender	female	147	48.12%	49.67%
	male	150	51.78%	50.33%
age	below17	57	19.35%	16.02%
	18–34	65	21.90%	22.25%
	35–59	127	42.96%	38.97%
	Over 60	58	19.78%	5.53%
Have/have no design experience	No	248	83.6%
	yes	49	17.7%
occupation	Entrepreneur	35	12%
	Financial staff	56	19%
	Sale staff	93	31%
	Technical staff	113	38%

Figure 5. The photo with the highest average score.

Figure 6. The photo with the lowest average score.

Table 7. Kendall rank correlation analysis.

		Score	Gender	Age	Experience
Gender	Coefficients	−0.16
	Significance	0.01
Age	Coefficients	0.42	0.61
	Significance	0.025	0.31
Experience	Coefficients	−0.29	0.38	−0.18
	Significance	0.000	0.25	0.32
Occupations	Coefficients	0.52	0.17	−0.22	0.59
	Significance	0.03	0.39	0.15	0.17

Table 8. Stepwise multiple linear regression analysis.

	Unstandardized Coefficients		Standardized Coefficients			Collinearity Statistics
	B	Std. Error	Beta	t	Sig.	Tolerance	VIF
(Constant)	3.481	0.03		14.389	0.000
Age	0.25	0.013	0.421	4.785	0.012	0.97	1.031
Gender	−0.47	0.011	−1.344	−5.033	0.001	0.453	2.206
Occupations	−0.749	0.02	−0.754	−2.97	0.025	0.451	2.218
Experience	0.52	0.015	−1.96	−6.632	0.000	0.672	6.621

Table 9. The linear analysis of photo physical properties for different gender groups.

		Unstandardized Coefficients		Standardized Coefficients			Collinearity Statistics
Dependent		B	Std. Error	Beta	t	Sig.	Tolerance	VIF
Scores for male	Constant	2.658	0.253		4.125	0
(R^2 = 0.62, N = 150)	A	0.532	2.692	0.421	2.944	0.01	0.698	2.243
	S	1.562	1.692	0.425	1.362	0.02	1.36	0.981
Scores for female	Constant	6.724	1.221		6.698	0
(R^2 = 0.58, N = 147)	S	0.897	0.328	0.932	4.121	0.001	0.698	4.128
	L	1.939	0.632	0.758	1.365	0.002	0.369	5.521

Table 10. The linear analysis of photo physical properties for different age groups.

		Unstandardized Coefficients		Standardized Coefficients			Collinearity Statistics
Model		B	Std. Error	Beta	t	Sig.	Tolerance	VIF
0–17 years old	(Constant)	3.478	0.287		5.128	0
R^2 = 0.713 n = 57	H	0.365	2.569	0.698	4.128	0.001	0.521	3.258
18–35 years old	(Constant)	4.754	0.374		5	0
R^2 = 0.638 n = 65	H	0.258	0.741	0.478	4.325	0.001	0.474	3.524
36–59 years old	(Constant)	9.261	0.362		4.547	0
R^2 = 0.681 n = 127	S	5.154	1.221	2.478	4.214	0	0.785	5.365
60 years old or older	(Constant)	7.369	0.524		6.698	0
R^2 = 0.714 n = 55	S	0.698	1.585	0.687	4.258	0	0.523	4.123
	L	2.678	0.874	1.458	2.125	0.05	0.854	3.697

Table 11. The linear analysis of photo physical properties for participants having/having no design experience.

		Unstandardized Coefficients		Standardized Coefficients			Collinearity Statistics
Model		B	Std. Error	Beta	t	Sig.	Tolerance	VIF
Design experience	(Constant)	4.125	0.412		7.684	0
R^2 = 0.711 n = 49	S	0.963	2.698	0.714	4.697	0	0.367	6.258
	A	0.426	1.482	0.347	2.528	0.02	0.521	4.528
No design experience	(Constant)	4.528	0.582		2.257	0
R^2 = 0.509 n = 248	S	0.471	1.052	0.428	4.747	0	0.782	3.127
	L	1.698	1.258	0.697	2.874	0.05	0.638	2.587

Table 12. The linear analysis of photo physical properties for participants of different occupations.

		Unstandardized Coefficients		Standardized Coefficients			Collinearity Statistics
Model		B	Std. Error	Beta	t	Sig.	Tolerance	VIF
Entrepreneur	(Constant)	6.158	0.352		6.982	0
R^2 = 0.632 n = 35	L	0.426	2.698	0.312	4.021	0.02	0.367	6.258
	H	0.426	1.482	0.398	4.812	0.01	0.521	4.528
Financial staff	(Constant)	5.812	0.493		5.932	0
R^2 = 0.589 n = 56	S	0.471	1.052	0.428	4.747	0	0.782	3.127
Sales staff	(Constant)	7.128	0.823		6.213	0
R^2 = 0.589 n = 93	S	0.412	1.052	0.336	4.581	0.015	0.782	3.127
Technical staff	(Constant)	6.323	0.631		5.521	0
R^2 = 0.589 n = 113	S	0.322	1.052	0.319	3.215	0.03	0.782	3.127
	A	0.285	0.982	0.487	2.258	0.01	0.681	6.987

Figure 7. The preference of different gender groups for architectural style of detached houses.

Figure 8. The preference of participants of 36–59 years old for architectural style of detached houses.

Figure 9. The preference of participants of different occupations for architectural style of detached houses.