Brand extensions via complements or substitutes: The moderating role of manufacturing transferability

Abstract

This research investigates how consumer evaluations of brand extensions that either complement or substitute the original parent brand vary depending on the level of manufacturing transferability (i.e., the extent to which the parent brand’s existing resources and skills can be used to make the extension). We propose that a complement extension is processed by consumers at a higher, more abstract level whereas a substitute extension is processed at a lower, more concrete level. Since manufacturing transferability activates concrete cognitions of the production process, an increase in manufacturing transferability tends to result in more favorable evaluations toward substitute extensions than complement extensions. Empirical tests using a multi-method approach reveal support both for the underlying theoretical mechanism and the proposed hypotheses.

Appendix

From Eq. 1in the paper, the total impact of consumption-based fit can be re-arranged as:

$$ {\beta_3}(C) + {\beta_4}(S) + {\beta_7}\left( {Q*C} \right) + {\beta_8}\left( {Q*S} \right) + {\beta_9}\left( {T*C} \right) + {\beta_{{1}0}}\left( {T*S} \right) $$

(A.1)

At mean parent quality, i.e., Q = 0 (data are mean-centered), and re-arranging (A.1), we get:

$$ \left( {{\beta_3} + {\beta_9}*T} \right){\text{C}} + \left( {{\beta_4} + {\beta_{{1}0}}*T} \right)S $$

(A.2)

Let C _H (C _L) represent high (low) levels of complementarity, and S _H (S _L) represents high (low) levels of substitutability. For complement extensions (C _H = 1, S _L = 1), impact of consumption-based fit can be represented as follows:

$$ \left( {{\beta_3} + {\beta_9}*T} \right)\left( {{C_{\text{H}}}} \right) + \left( {{\beta_{{4} }} + {\beta_{{1}0}}*T} \right){S_{\text{L}}} $$

(A.3)

Similarly, the impact of fit when the extension is a substitute (C _L = 1, S _H = 1) is given by:

$$ \left( {{\beta_3} + {\beta_9}*T} \right)\left( {{C_{\text{L}}}} \right) + \left( {{\beta_4} + {\beta_{{1}0}}*T} \right){S_{\text{H}}} $$

(A.4)

The difference between the impact of substitutes and complements is obtained by subtracting (A.4) from (A.3). At high levels of transferability (T _H = 1), this difference is given by:

$$ \left( {{\beta_3} + {\beta_9}*{T_{\text{H}}}} \right)\left( {{C_{\text{L}}}-{C_{\text{H}}}} \right) + \left( {{\beta_4} + {\beta_{{1}0}}*{T_{\text{H}}}} \right)\left( {{S_{\text{H}}} - {S_{\text{L}}}} \right) $$

(A.5)

Similarly, at low levels of manufacturing transferability, the difference can be expressed as:

$$ \left( {{\beta_3} + {\beta_9}*{T_{\text{L}}}} \right)\left( {{C_{\text{L}}}-{C_{\text{H}}}} \right) + \left( {{\beta_4} + {\beta_{{1}0}}*{T_{\text{L}}}} \right)\left( {{S_{\text{H}}} - {S_{\text{L}}}} \right) $$

(A.6)

Substituting the values of β ₃, β ₄, β ₉, and β ₁₀ from Table 1, and setting T _H = 2.99 [1.5*Standard Deviation of transferability (1.99)], we can see that the latter term in (A.5) as expressed by (β ₄ + β ₁₀*T _H) (S _H − S _L) is always positive and (β ₃ + β₉*T _H)(C _L – C _H) ≥ 0. Therefore, (A.5) is always ≥0. Hence, we conclude that the difference between the impact of substitute and complement products at high levels of transferability is always positive. Substituting the values of β ₃, β ₄, β ₉, and β ₁₀ from Table 1, setting T _L = −2.99 and testing whether (A.6) = 0, we find that (β ₃ + β ₉*T _L)(C _L – C _H) + (β ₄ + β ₁₀*T _L) (S _H − S _L) is not different from zero. Hence, it is clear there is no difference between the impact of substitutes and complements at low levels of transferability.