The effect of variety seeking and status consumption on generation Y consumers’ attitude toward beauty products: The mediating role of innovativeness


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The cosmetic industry is a highly lucrative market in South Africa. Individuals of the Generation Y cohort represent an essential current and future market segment for various industries, including the beauty product industry. The purpose of this study is to determine the direct and indirect effects of variety seeking and status consumption on attitudes through beauty product innovativeness among female Generation Y students. This study used a self-administered questionnaire. The sample includes female Generation Y students at a traditional university, a comprehensive university, and a university of technology in the Gauteng province. The study yielded 610 adequate responses. The data were analyzed using principal component factor analysis, descriptive statistics, Pearson’s product-moment correlation, and path analysis with mediation tests. The study presents a four-factor model: status consumption, variety seeking, beauty product innovativeness, and consumer attitude. Status consumption statistically, significantly, and positively affect beauty product innovativeness (β = 0.350, p = 0.000 < 0.01) and consumer attitude (β = 0.107, p = 0.053 < 0.01). Variety seeking has a statistically significant and positive influence on beauty product innovativeness (β = 0.276, p = 0.000 < 0.01) but an insignificant on consumer attitude (β = 0.043, p = 0.459 > 0.01). Lastly, beauty product innovativeness was a statistically significant predictor of attitude (β = 0.286, p = 0.000 < 0.01). These results suggest that beauty product innovativeness mediates the relationship between variety-seeking and consumer attitudes of the Generation Y cohort toward beauty products.

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    • Figure 1. Structural model
    • Table 1. Sample description
    • Table 2. Descriptive statistics
    • Table 3. Rotated factors
    • Table 4. Correlation coefficients and collinearity statistics
    • Table 5. Measurement model estimates
    • Table 6. Correlation, reliability and construct validity
    • Table 7. Standardized regression estimates and p-values
    • Conceptualization
      Riané C. Dalziel
    • Data curation
      Riané C. Dalziel
    • Formal Analysis
      Riané C. Dalziel, Kirsty-Lee Sharp
    • Investigation
      Riané C. Dalziel, Kirsty-Lee Sharp
    • Methodology
      Riané C. Dalziel, Kirsty-Lee Sharp
    • Writing – original draft
      Riané C. Dalziel, Kirsty-Lee Sharp
    • Writing – review & editing
      Riané C. Dalziel, Kirsty-Lee Sharp