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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


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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