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Ad Repetition and Variation in a Competitive Ad Context
Unformatted Document Text:  23 Further contrast analyses indicated that, when responses of ads without repetition were analyzed, the impact of product attribute number approached significant levels (F(1, 41) = 2.79, p = .10, M two attributes = 1.92, M four attributes = 2.66). When responses of ads with repetition were analyzed, the impact of product attribute number was not significant (F(1, 83) = .52, p = .47, M two attributes = 3.14, M four attributes = 2.89). Even though hypothesis 4c was not supported, the means were in the expected directions. Hypothesis 5 argues that, in a competitive ad context, ads with cosmetic variation will generate more correct ad recognition than ads with substantive/cosmetic variation. When responses to the two ad repetition conditions were analyzed, ANOVA indicated that the impact of repetition variation had a significant impact on correct ad recognition and the means were in the expected directions (F(1, 83) = 31.84, p = .01, M substantive/cosmetic = 1.96, M cosmetic = 3.82). Therefore, hypothesis 5 was supported. Hypothesis 6 suggests that when repetition is used, ads with substantive/cosmetic variation are more effective in terms of creating more ad liking and higher ad entertainment ratings than ads with cosmetic variation, yet ads with substantive/cosmetic variation are not more effective in terms of ad informativeness and ad diagnosticity than ads with cosmetic variation. ANOVA indicated that the impact of repetition variation had a significant impact on ad liking (F(1, 83) = 4.10, p = .05, M substantive = 4.16, M cosmetic = 3.63) and ad entertainment ratings (F(1, 83) = 4.98, p = .03, M substantive = 4.02, M cosmetic = 3.42) but not on ad informativeness (F(1, 83) = .37, p = .55, M substantive = 4.19, M cosmetic = 4.00) or ad diagnosticity ratings (F(1, 83) = .02, p = .88, M substantive = 3.26, M cosmetic = 3.22). All the means were in the expected directions. Therefore, hypothesis 6 was supported. Discussion Media spending accounts for a big proportion of advertising expenditure. How to allocate

Authors: Chang, Chingching.
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23
Further contrast analyses indicated that, when responses of ads without repetition were analyzed,
the impact of product attribute number approached significant levels (F(1, 41) = 2.79, p = .10,
M
two attributes
= 1.92, M
four attributes
= 2.66). When responses of ads with repetition were analyzed,
the impact of product attribute number was not significant (F(1, 83) = .52, p = .47, M
two attributes
=
3.14, M
four attributes
= 2.89). Even though hypothesis 4c was not supported, the means were in the
expected directions.
Hypothesis 5 argues that, in a competitive ad context, ads with cosmetic variation will
generate more correct ad recognition than ads with substantive/cosmetic variation. When
responses to the two ad repetition conditions were analyzed, ANOVA indicated that the impact of
repetition variation had a significant impact on correct ad recognition and the means were in the
expected directions (F(1, 83) = 31.84, p = .01, M
substantive/cosmetic
= 1.96, M
cosmetic
= 3.82).
Therefore, hypothesis 5 was supported.
Hypothesis 6 suggests that when repetition is used, ads with substantive/cosmetic variation
are more effective in terms of creating more ad liking and higher ad entertainment ratings than
ads with cosmetic variation, yet ads with substantive/cosmetic variation are not more effective in
terms of ad informativeness and ad diagnosticity than ads with cosmetic variation. ANOVA
indicated that the impact of repetition variation had a significant impact on ad liking (F(1, 83) =
4.10, p = .05, M
substantive
= 4.16, M
cosmetic
= 3.63) and ad entertainment ratings (F(1, 83) = 4.98, p
= .03, M
substantive
= 4.02, M
cosmetic
= 3.42) but not on ad informativeness (F(1, 83) = .37, p = .55,
M
substantive
= 4.19, M
cosmetic
= 4.00) or ad diagnosticity ratings (F(1, 83) = .02, p = .88, M
substantive
=
3.26, M
cosmetic
= 3.22). All the means were in the expected directions. Therefore, hypothesis 6
was supported.
Discussion
Media spending accounts for a big proportion of advertising expenditure. How to allocate


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