An Empirical Investigation of Color Temperature and Gender Effects on Web Aesthetics

Constantinos K. Coursaris, Sarah J. Sweirenga, and Ethan Watrall

Journal of Usability Studies, Volume 3, Issue 3, May 2008, pp. 103-117

Article Contents

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Results

Following from the earlier discussion on the instrument's validity, statistics regarding significant items and construct are reported in Table 5 (on subsequent page).

The proposed structural model shown earlier in Figure 1 was tested by Jackknifing in PLS. This resampling procedure assesses the significance of PLS parameter estimates (Chin, 1998). Jackknifing is just one of several PLS techniques that may be used in evaluating a research model. For example, Bootstrapping is another common PLS approach, but in general, estimations by either one approach should converge (Chin, 1998). All three of the original hypotheses were supported as shown in Figure 3, while Table 6 presents the validation of these hypotheses in more detail. Furthermore, the structural model tested using PLS demonstrated mixed explanatory power for perceived Web site aesthetics. With an R-square of 0.45, 45% of the variance in expressive aesthetics was explained by both the color temperature effects and the classical aesthetics (more heavily so) in this study. Only 3.2% of the variance for classical aesthetics was explained by this manipulation, suggesting that there are other dimensions not captured by the scale (in part explained after the removal of two items), by the exogenous construct's effects, or both.

Figure 3. PLS model
(* significant at 0.05 level, ** significant at 0.01 level, *** significant at 0.001 level)

Table 5. Items and construct statistics

	Mean	Std. dev.	Loading	Error	Item-total correlation	Alpha	Alpha if item deleted
Classical aesthetics	5.342	1.632				0.771	0.783
Clear	5.317	1.433	0.746	0.018	0.495		0.835
Aesthetic	5.230	1.230	0.863	0.024	0.638		0.656
Pleasant	5.479	1.155	0.895	0.025	0.712		0.587
Expressive aesthetics						0.906	0.906
Original	3.412	1.558	0.847	0.319	0.763		0.885
Sophisticated	4.079	1.564	0.849	0.320	0.728		0.893
Fascinating	3.079	1.538	0.896	0.357	0.825		0.871
Creative	3.439	1.555	0.885	0.348	0.816		0.873
Uses special effects	2.460	1.381	0.779	0.270	0.688		0.900

 

Table 6. Validity test results

Hypotheses	From	To	Beta	t-Value	p-Value	Sig	Status
H1	ClassAes	ExprAes	0.586	13.317	< 0.001	***	Supported
H2	Design	ClassAes	0.021	2.110	< 0.05	*	Supported
H3	Design	ExprAes	-0.042	4.666	< 0.01	**	Supported

The next measurement pertains to the ranking of the different Web site designs. Rankings were significantly different (one-sample T-test) suggesting a preference for blues or the cool-cool color design (see Table 7).

Table 7. Web site rankings (of perceived aesthetics) and one-sample of comparison of means (mean reflects average of forced rank between 1 or most aesthetic and 4 or least aesthetic)

Color temperature (primary-secondary)	N	Mean	Std. deviation	Std. error mean	t	Df	Sig. (2-tailed)
Warm-warm	328	2.97	1.171	0.065	45.956	327	0.000
Warm-cool	328	2.62	0.914	0.050	51.959	327	0.000
Cool-warm	328	2.34	0.980	0.054	43.326	327	0.000
Cool-cool	328	2.00	1.135	0.063	31.971	327	0.000

The fourth hypothesis stated that "increasing the color temperature of a Web site design will have a more negative impact on women's perceptions of its aesthetics than those of men." ANOVA test results suggested that there were no significant differences in the reporting of both classical and expressive aesthetics scale items (see Table 8), as well as in the ranking of the four Web site designs (see Table 9). Thus, gender does not appear to be related to users' perceptions of aesthetics as a result of color temperature combinations in the context of hotel Web sites. However, the hypothesized directionality becomes apparent when contrasting the p-values for the two cool Web site designs (i.e., third and fourth design with p-values above 0.88) with the two warm Web site designs (i.e., first and second design with p-values below 0.30). Thus, gender differences regarding color preferences at the warmer end of the spectrum may occur, although the findings of this study do not offer such support.

Table 8. ANOVA for relationships between gender and aesthetics (classical and expressive)

Item		Sum of squares	df	Mean square	f	Sig.
ClassAes2	Between groups	1.451	1	1.451	.707	.401
	Within groups	669.573	326	2.054
	Total	671.024	327
ClassAes3	Between groups	3.280	1	3.280	2.178	.141
	Within groups	491.110	326	1.506
	Total	494.390	327
ClassAes4	Between groups	.233	1	.233	.175	.676
	Within groups	435.617	326	1.336
	Total	435.851	327
ExprAes1	Between groups	.435	1	.435	.179	.673
	Within groups	793.001	326	2.433
	Total	793.436	327
ExprAes2	Between groups	4.632	1	4.632	1.899	.169
	Within groups	795.307	326	2.440
	Total	799.939	327
ExprAes3	Between groups	.027	1	.027	.011	.916
	Within groups	773.912	326	2.374
	Total	773.939	327
ExprAes4	Between groups	.085	1	.085	.035	.852
	Within groups	790.696	326	2.425
	Total	790.780	327
ExprAes5	Between groups	1.286	1	1.286	.674	.412
	Within groups	622.199	326	1.909
	Total	623.485	327

 

Table 9. ANOVA for relationships between gender and aesthetics rankings of four Web site designs (i.e., color temperature combinations)

Item		Sum of squares	df	Mean square	F	Sig.
Rank of site 1	Between groups	2.280	1	2.280	1.665	.198
	Within groups	446.473	326	1.370
	Total	448.753	327
Rank of site 2	Between groups	.931	1	.931	1.115	.292
	Within groups	272.191	326	.835
	Total	273.122	327
Rank of site 3	Between groups	.004	1	.004	.004	.949
	Within groups	314.066	326	.963
	Total	314.070	327
Rank of site 4	Between groups	.027	1	.027	.021	.886
	Within groups	420.970	326	1.291
	Total	420.997	327

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