Marketing Factors And Brand Equity Affecting Consumers' Buying Behaviour Of Facial Care Product
Abstract
The purpose of this research was to determine (1) marketing factors affect buying behaviour for facial care products in Bangkok; (2) brand values affect buying behaviour for facial care products in Bangkok; (3) the relationship between marketing factors and brand values and buying behaviour for facial care products in Bangkok, and (4) the influence of marketing factors and brand values affect buying behavior for facial care products in Bangkok. The sample of 400 cases were drawn from Bangkok collected field data using questionnaires created by researchers during August - October 2020.
The results of this research revealed that: (1) marketing factors include product, price, distribution and marketing promotion in both overall and individual aspects affected buying behaviour for facial care products in Bangkok at a large extent. That is, as a whole (M = 3.86, SD = 0.58) on the product side (M = 3.95, SD = 0.75) Price side (M = 4.03, SD = 0.47) Distribution side (M = 3.85, SD = 0.52) and marketing promotion (M = 3.73, SD = 0.85) (2) Brand value affects buying behavior for facial care on a large scale (M = 4.17, SD = 0.42), As for the brand value in the individual components, it influences buying behavior for facial care products at the high level to the highest. (3) The marketing factors and the brand value of almost all components were statistically significant related to buying behavior for facial care products at .05, except for marketing factors, distribution (iv3) and brand value, other proprietary brand assets (iv9) are insignificantly. (4) Regression Equation to predict buying behavior for facial care in Bangkok In Raw Score; Behavior = 1.20 + 0.36*iv1 +0.11*iv2 +0.27*iv3 +0.24*iv4 +0.18*iv5 +0.29*iv6 +0.40*iv7 +0.35*iv8 +0.19*iv9 . Regression equation in standard score Z Behavior = 1.44*Ziv1 + 0.27*Ziv2 + 0.61*Ziv3+1.23*Ziv4+0.60*Ziv5+0.99*Ziv6+0.76*Ziv7+ 0.67*Ziv8+ 0.34*Ziv8 , Test statistics as F (9, 390) = 272.75,
p = 0.00 , Forecast Coefficient Equals .86 (R2 = 0.86) and Adjusted Forecast Coefficient Equals 0.86 (R2adj = 0.86).
